| Entries |
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| 20080209269 | Active Probing for Real-Time Diagnosis - Improved problem diagnosis techniques for use in accordance with computing systems, e.g., distributed computing systems, are disclosed. In one aspect of the invention, a technique for diagnosing a problem associated with a computing system comprises the following steps/operations. One or more probes are executed in accordance with at least a portion of a previously selected probe schedule. When a result of one or more of the probes of the previously selected probe schedule indicates, at least, a potential problem associated with the computing system, one or more probes which optimize at least one criterion are selected in real-time. The one or more selected probes are executed so as to diagnose the potential problem. | 08-28-2008 |
| 20080244313 | Overriding Daughterboard Slots Marked with Power Fault - Having detected an anomalous fault in a peripheral I/O slot, a processor entity may need to perform some remedial action, wherein the peripheral slot may have a fault line. First a voltage may be detected on the slot. Processor entity may set a fault if a voltage is found. A hotplug controller which may provide outputs that the processing entity may store as a fault syndrome word. The service processor or operating system, either during initial program load, or at another time, may detect that the fault could be a false fault depending on a set of predefined conditions and following the mechanism described here can then clear the fault earlier set. If an action from a previous device list is set, then there may be a clearing of the voltage fault based on determining that the action is set. | 10-02-2008 |
| 20080263399 | DIAGNOSTIC SYSTEM AND ARTICLE - Articles and systems comprise a diagnostic symptom tree system for diagnosing a failing system element causing a symptom in a system-under-test. A diagnostic symptom tree comprises symptom roots and dependent lower function nodes and sub-function nodes. Element nodes depend from the function or sub-function nodes, and a plurality of penultimate failure mode leaves depend from the element nodes. The function and sub-function nodes and the failure mode leaves comprise test information. Responsive to positive test results, the diagnostic symptom tree is configured to identify a function or sub-function or element node associated to a lowest symptom tree node or failure mode leaf for which a test is positive, or advise that no failing function or sub-function or element is found. In one aspect of the invention, nodes may include parameter values allowing successive selections of the nodes of the symptom tree for test iterations according to the parameter values. | 10-23-2008 |
| 20080282108 | PROGRAM SYNTHESIS AND DEBUGGING USING MACHINE LEARNING TECHNIQUES - One embodiment is directed to synthesizing code fragments in a software routine using known inputs and corresponding expected outputs. A computer system provides a software routine with known inputs and corresponding expected outputs, infers software routine instructions based on the known inputs and corresponding expected outputs, and synthesizes a correctly functioning code fragment based on the inferred instructions. Another embodiment is directed to automatically resolving semantic errors in a software routine. A computer system provides the software routine with known inputs and corresponding expected outputs for portions of a program fragment where an error has been localized. The computer system learns a correctly functioning program fragment from pairs of input-output descriptions of the program fragment, determines the program statements that can transform given input states into given output states after execution of those program statements, and alters portions of the software routine with the learned program fragments. | 11-13-2008 |
| 20080288821 | Automated Diagnosis for Electronic Systems - Systems for providing automated diagnosis of problems for an electronic network include a central diagnosis engine configured to include modules that rank identified policy/configuration changes into potential causes, verify the ranked potential causes and determine whether any of the ranked potential causes is a likely cause or contributor to the problem. An estimator module is configured to calculate distances associated with the ranked potential causes such that a list of potential causes of the problem can be presented in order of likelihood. Other systems and methods are also provided. | 11-20-2008 |
| 20090019310 | COLLECTING AND REPRESENTING KNOWLEDGE - Problem determination knowledge is provided by an extraction tool that extracts tag information recorded in identified problem tracking tools, where the tags relate to problem knowledge. The extracted tag information is examined to produce a catalog of symptom definitions that can be utilized by tools such as problem submission, logging and/or analysis tools. | 01-15-2009 |
| 20090037772 | FUZZY CLASSIFICATION APPROACH TO FAULT PATTERN MATCHING - A method and apparatus are provided for diagnosing faults in a monitored system. Estimates of parameter data are generated from the system with reference parameter data characteristic of known behavior of the system. The generated estimates of the parameter data are compared with measured parameter data. A residual is determined for each of the parameters based on a relationship between the estimates of the parameter data and the measured parameter data. A fuzzy classification rule is implemented to determine a likelihood that a predetermined fault exists by using residuals for parameters used to indicate the existence of the predetermined fault. | 02-05-2009 |
| 20090044054 | DYNAMIC CRITICAL PATH DETECTOR FOR DIGITAL LOGIC CIRCUIT PATHS - Method for correcting timing failures in an integrated circuit and device for monitoring an integrated circuit. The method includes placing a first and second latch near a critical path. The first latch has an input comprising a data value on the critical path. The method further includes generating a delayed data value from the data value, latching the delayed data value in the second latch, comparing the data value with the delayed data value to determine whether the critical path comprises a timing failure condition, and executing a predetermined corrective measure for the critical path. | 02-12-2009 |
| 20090049338 | ROOT CAUSE DIAGNOSTICS USING TEMPORAL DATA MINING - A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence. | 02-19-2009 |
| 20090055684 | METHOD AND APPARATUS FOR EFFICIENT PROBLEM RESOLUTION VIA INCREMENTALLY CONSTRUCTED CAUSALITY MODEL BASED ON HISTORY DATA - A system for problem resolution in network and systems management includes a database of trouble ticket data including information fields for checked components and affected components, an automated model builder system that processes the trouble ticket data to construct a causality model to represent causality information between system components identified in the checked component and affected component fields of the trouble ticket data, and an automated problem analysis system that receives information indicative of a problem event and determines a cause of the problem event using the causality model. | 02-26-2009 |
| 20090070628 | HYBRID EVENT PREDICTION AND SYSTEM CONTROL - A system for predicting an occurrence of a critical even in a computer cluster includes: a control system that includes an event log, a system parameter log, a memory for storing information related to occurrences of critical events, and a processor. The processor implements a hybrid prediction system; loads the information from the event log and the system performance log into a Bayesian network model; uses the Bayesian network model to predict a future critical event; makes future scheduling and current data migration selections; and adapts the Bayesian network model by feeding the scheduling and data migration selections. | 03-12-2009 |
| 20090077421 | LOAD TEST METHOD AND LOAD TEST APPARATUS - A load test method for a computer and apparatus are provided. The method includes acquiring control information indicating a type of a hardware resources required for executing a load test program and quantitative conditions determined for each type of the hardware resources, acquiring an assignment rule table specifying a set of rules for each of the various hardware resources to assign the hardware resources of the computer to a load test program, selecting a rule for each of the hardware resources from the acquired assignment rule table in such a manner that a load is imposed on a predetermined part of the computer, developing the load test programs by assigning the hardware resources of the computer to the load test programs based on the acquired control information and the selected rule for each of the various hardware resources, and executing in parallel the developed load test programs. | 03-19-2009 |
| 20090083576 | FAULT TREE MAP GENERATION - A method for Fault Tree Map generation employs to transformation of Fault Trees of production installation, specific installation, technical system (Hardware and integrated Hardware/Software) to new Fault Tree diagram (Fault Tree Map), which permits drastically compact the Fault Tree depiction and facilitates performing of the Fault Tree qualitative analysis, including evaluation of combination of latent failures and evident failures, repeated events and critical events position influence, and failure propagation potentiality, besides facility of localization of each Fault Tree logical Gate and relevant failures in the fault tree printed report. Generation takes place using special symbols, which permit to reflect the Fault Tree logic, present all Fault Tree failures with graphically identification of the failure type, and show the failure repetition and also the failure critically (importance) to Fault Tree Top Event probability. The method presents exceptional advantages to analysis of large-scale, extended Fault Trees, allowing vastly decrease the time of analysis and elevate the analysis quality and Fault Tree perception, including for specialists, who are not the Fault Tree authors. | 03-26-2009 |
| 20090083577 | Scheduling and Decision System - The inventive subject matter herein is directed toward improved scheduling and planning system in which computer implemented software uses a hierarchical selection list to select at least one of a plurality of unconnected users and contact the selected user(s) as a function of an event. | 03-26-2009 |
| 20090094484 | SYSTEM AND METHOD FOR AUTONOMOUSLY PROCESSING FAULTS IN HOME NETWORK ENVIRONMENTS - There are provided a fault processing system and method for quickly and accurately diagnosing a fault and autonomously processing the fault, based on interdependencies between various devices, networks, systems, and services in home network environments, the method including: establishing fault detection rules for detecting faults belonging to respective fault types defined for each situation by classifying faults occurring in the home network environments, fault diagnosis rules for diagnosing a fault type of a fault, and fault processing rules defining a method of solving a fault for each fault type; collecting state information of devices, networks, services, and the system in the home network environments and detecting a fault based on the fault detection rules; diagnosing the fault type of the detected fault by applying the fault diagnosis rules; and processing the detected fault based on the fault processing rules according to the diagnosed fault type. | 04-09-2009 |
| 20090100293 | METHOD AND SYSTEM FOR PREDICTING TURBOMACHINERY FAILURE EVENTS EMPLOYING GENETIC ALGORITHM - A method for predicting or detecting an event in turbomachinery includes the steps of obtaining operational data from at least one machine and at least one peer machine. The operational data comprises a plurality of performance metrics. A genetic algorithm (GA) analyzes the operational data, and generates a plurality of clauses, which are used to characterize the operational data. The clauses are evaluated as being either “true” or “false”. A fitness function identifies a fitness value for each of the clauses. A perturbation is applied to selected clauses to create additional clauses, which are then added to the clauses group. The steps of applying a fitness function, selecting a plurality of clauses, and applying a perturbation can be repeated until a predetermined fitness value is reached. The selected clauses are then applied to the operational data from the machine to detect or predict a past, present or future event. | 04-16-2009 |
| 20090132855 | AUTOMATED KERNEL EXTRACTION - A method and system for automatically developing a fault classification system from time series data. The sensors need not have been intended for diagnostic purposes (e.g., control sensors). These methods and systems are functionally independent of knowledge related to a particular equipment system, thereby allowing seamless application to multiple systems, regardless of the suite of sensors in each system. Because this algorithm is totally automated, substantial savings in time and development cost can be achieved. The algorithm results in a classification system and a set of features that might be used to develop alternative classification systems without human intervention. | 05-21-2009 |
| 20090138759 | SELF-AWARE AND SELF-HEALING COMPUTING SYSTEM - A method and a computing system for performing the method. Microstates of components of a computing system are organized into macrostates of the computing system. Each microstate represents a state that a component of the computing system is able to individually enter. Each macrostate represents a state that the computing system is able to enter as a whole. The macrostates of the computing system are organized into meta-dynamic states of the computing system. The computing system is monitored such that perturbations of the computing system are detected, wherein a perturbation of the computing system will result in movement thereof to a new meta-dynamic state. It is determined that the new meta-dynamic state is undesirable. A path is determined. The path causes the computing system to move back to a desirable meta-dynamic state. The computing system is caused to move on the path to the desirable meta-dynamic state. | 05-28-2009 |
| 20090183029 | Root Cause Analysis In A System Having A Plurality Of Inter-Related Elements - A method of performing root cause analysis for use in a system comprising a plurality of inter-related elements, wherein at least some of the elements experience one or more abnormal conditions, comprising defining one or more conditions for more than one element symptomatic of abnormal operation of the element; defining one or more causal relationships between the conditions and results on one or more related elements; compiling the conditions and causal relationships of each element for which conditions and relationships have been defined, as at least one continuation in a continuation passing style (CPS); receiving one or more observed events symptomatic of abnormal operation of at least one element of the system; processing the received events using the conditions and the continuations; concluding at least one root cause of the received events consistent with the received events; and outputting the root cause. | 07-16-2009 |
| 20090193293 | Systems, Methods, and Media for Outputting Data Based Upon Anomaly Detection - Systems, methods, and media for outputting data based on anomaly detection are provided. In some embodiments, methods for outputting data based on anomaly detection include: receiving a known-good dataset; storing distinct n-grams from the known-good dataset to form a binary anomaly detection model; receiving known-good new n-grams; computing a rate of receipt of distinct n-grams in the new n-grams; determining whether further training of the anomaly detection model is necessary based on the rate of receipt on distinct n-grams; using the binary anomaly detection model to determine whether an input dataset contains an anomaly; and outputting the input dataset based on whether the input dataset contains an anomaly. | 07-30-2009 |
| 20090193294 | SYSTEM AND METHOD FOR VERIFYING OPERATION OF A TARGET SYSTEM - A system and method for verifying operation of a target system to be inspected. The system includes an abstract binary tree generation unit and a matching unit. The abstract binary tree generation unit obtains information about a functional specification of the target system and generates one or more binary trees that associate one or more states that can occur in the target system with respective nodes and that associate state transitions of objects constituting the target system and interactions between the objects with connection relationships between the nodes. The matching unit receives an event sequence in an application model of the target system obtained in response to the operation of the target system and matches the event sequence against the binary trees generated by the abstract binary tree generation unit. The method includes steps for accomplishing the functionality of the system. | 07-30-2009 |
| 20090210745 | Runtime Error Correlation Learning and Guided Automatic Recovery - A method and apparatus for automatic error analysis and recovery for applications on one or more computer systems, which maintain a dependency structure of the applications, maintain correlation information between errors and error symptoms, and analyze and recover a problem when the problem occurs. The method, program product or system further utilizes a centralized knowledge base for runtime error handling and problem resolution. | 08-20-2009 |
| 20090210746 | GENERATING TEST COVERAGE BIN BASED ON SIMULATION RESULT - A solution for generating functional coverage bins for testing a device is disclosed. A method includes: receiving information of a failing test generated from a random simulation performed on the device; tracing a first sequence of signal events that happened in the failing test; correlating the signal events to coverage bins to generate a sequence of coverage bins; creating cross coverage event sequence bins based on the sequence of coverage bins; and outputting the created coverage event sequence bins for testing the device. | 08-20-2009 |
| 20090222694 | Model-Based Hardware Exerciser, Device, System and Method Thereof - Device, system and method for verification of a hardware system-under-test including at least one processor. A method includes building an executable image of a hardware exerciser adapted for execution on a test platform selected from: a simulation accelerator, a hardware emulator, a prototype hardware system, and a hardware production wafer. The exerciser image includes embedded data corresponding to architectural knowledge, testing knowledge, and a test template. The test template is defined in a context-free formal language and includes biasing directives to influence at least one of a desired test structure, one or more resources to be included in the test, and one or more values of the included resources. The architectural knowledge is obtained from an architectural model including a formal description of the specification for the system-under-test, and the testing knowledge is obtained from a testing knowledgebase including heuristics for testing desired aspects of the system-under-test. | 09-03-2009 |
| 20090287958 | METHOD AND APPARATUS FOR TEST GENERATION FROM HYBRID DIAGRAMS WITH COMBINED DATA FLOW AND STATECHART NOTATION - A test generator and methods for generating tests from a hybrid diagram are provided. A hybrid diagram is a diagram that primarily uses one higher-level semantic notation with portions utilizing one or more secondary higher-level semantic notations. Example higher-level semantic notations are statechart notation and data-flow notation. A test generator processes the hybrid diagram without reducing the higher-level semantic constructs to lower-level semantic constructs. The test generator generates test-generation templates as needed based on the higher-level semantic model used in the diagram. The test generator uses the test-generation templates to generate tests for a system-performing device specified by the diagram. The generated tests may be executed automatically by a test driver or manually by a human tester. | 11-19-2009 |
| 20090292948 | Fault Location in Telecommunications Networks using Bayesian Networks - A method for locating a fault in a communication network, includes receiving status information relating to alarms, events, polled statuses or test results in the communication network; and locating the fault based on the received status information, wherein locating the fault includes identifying a limited region of the communication network in which the fault has occurred based on the received status information and on topological and functional information relating to network apparatuses that have generated the status information; constructing a probabilistic model relating faults and status information in the identified limited region of the communication network; and locating the fault based on the constructed probabilistic model and on status information received from the identified limited region of the communication network. | 11-26-2009 |
| 20090300417 | SYSTEM AND METHOD FOR ADVANCED CONDITION MONITORING OF AN ASSET SYSTEM - A method for advanced condition monitoring of an asset system includes using a plurality of auto-associative neural networks to determine estimates of actual values sensed by at least one sensor in at least one of the plurality of operating regimes; determining a residual between the estimated sensed values and the actual values sensed by the at least one sensor from each of the plurality of auto-associative neural networks; and combining the residuals by using a fuzzy supervisory model blender; performing a fault diagnostic on the combined residuals; and determining a change of the operation of the asset system by analysis of the combined residuals. An alert is provided if necessary. A smart sensor system includes an on-board processing unit for performing the method of the invention. | 12-03-2009 |
| 20090300418 | Method for Error Tree Analysis - A technical system is broken down into a plurality of subsystems, each of which is allocated a time-dependent distribution function which describes the probability of failure of the respective subsystem. The distribution functions are linked to one another to form a time-dependent system distribution function which describes the probability of failure of the technical system. | 12-03-2009 |
| 20090319827 | FAULT PREDICTION METHOD, FAULT PREDICTION SYSTEM, AND IMAGE FORMING APPARATUS - A fault prediction method predicts a plurality of faults in a target device, and includes the steps of collecting internal information of the target device output from the target device, generating one or more criteria for defining a deviation from a normal state based on the collected internal information of the target device, incorporating the one or more criteria into a device state discriminator, identifying a deviation from a normal state in the target device according to the one or more criteria using the device state discriminator, and outputting a fault prediction as a result of the identifying step to a user. One or more of the steps are performed by a processor. | 12-24-2009 |
| 20090327809 | DOMAIN-SPECIFIC GUIDANCE SERVICE FOR SOFTWARE DEVELOPMENT - During software development, both before and after release, information may be collected and stored that may provide insight to developers as a generalized service. For example, data from past debugging sessions, source code in various repositories, bug repositories, discussion groups, and various documents may provide relevant information for software developers to fix current problems when this information is coherently matched with the problem. Using various sources, a system may mine the stored data to give the current developer information related to past code development, and reveal why the code changed throughout previous development. Using sophisticated analyses to identify similar code patterns across multiple large software projects, discovering patterns in normal and abnormal uses of particular software interfaces, and employing other mining techniques, a developer may find domain-specific information to facilitate ongoing software development. | 12-31-2009 |
| 20090327810 | SYSTEM FOR EXAMINING EFFECTS AND PROPOSING CONSEQUENTIAL ACTIONS - Traditionally, in fault diagnosis systems, the user is instructed to investigate symptoms exhaustively until a single fault is identified. A more advanced known system recognises that it may be cost effective to address a fault that has been determined as being likely but not certain to exist; in preference to further examination of the symptoms. However this technique has been found not to work well when a symptom is known to be only sometimes associated with a fault. The invention addresses this problem by 1) deriving a first value, for each fault, of probable benefit of acting on that fault and for identifying the fault for which that value is greatest, 2) deriving a second value, for each symptom, of probable benefit of an investigation into that symptom and for identifying the symptom for which that second value is greatest, and 3) comparing the greatest first value with the greatest second value thereby determining when to switch from investigating symptoms to acting upon a fault. By employing the invention the aforementioned problem can be overcome because the system calculates the extent to which each symptom examination would improve the situation, assuming no further symptom investigations are used. | 12-31-2009 |
| 20090327811 | Expert System and Method - A system and method is provided for representation of a real world problem situation. The system includes a computer software process which can acquire or accept a set of input data. The input data generally includes seed facts and user entered facts. The set of input data represents real world objects which pertain to a real-world problem situation. The computer software process generates new data. The new data consists of additional not-previously-known facts about the real-world problem situation. The additional not-previously known facts include acquired facts and reasoned facts. The computer software process utilizes a fact structured representation method. The fact structured representation method represents a first group of facts about a problem situation. It also represents a rule structured representation method for representing a first group of rules about a class of problem situations. The computer software process also represents a plurality of causal features of the problem situation so that a reasoning process results. The reasoning process is characterized as performing some elements of deep reasoning. | 12-31-2009 |
| 20100037099 | DIAGNOSTIC METHOD FOR LOCATING A FAILURE IN A COMPLEX SYSTEM, AND A DEVICE FOR IMPLEMENTING SAID METHOD - A diagnostic method for locating a failure in a complex system that includes the steps of detecting operating information using a detector device; verifying a performance of the system based on the operating information; determining an operating status of the system to be one of “operational,” “non-operational” and “degraded” based on the operating information; comparing the operating information with predetermined data when the operation status is one of “operational,” “non-operational” and “degraded;” and generating at least one hypothesis as to a location of the failure of the system. | 02-11-2010 |
| 20100042872 | RECURSIVE STRUCTURE FOR DIAGNOSTIC MODEL - A recursive mapping structure for diagnostic models is provided. A parent diagnostic model includes a first input module, a first output module, a first monitor module coupled to the first input and first output modules, and a first propagation module coupled between the first input and first output modules. A child diagnostic model includes a second input module, a second output module, a second monitor module coupled to the second input and second output modules, and a second propagation module coupled between the second input and second output modules, wherein the second monitor module is coupled to the first monitor module. | 02-18-2010 |
| 20100042873 | METHOD AND DEVICE FOR FAULT AUTO-DETECTION IN AN ON-BOARD SYSTEM - The method includes:
| 02-18-2010 |
| 20100088546 | STATISTICAL DEBUGGING USING PATHS AND ADAPTIVE PROFILING - The method executes the application and if there are no errors from the execution of the application, the method ends. If errors exist, the errors are collected from the execution of the application in an error report. Labeled application paths are created by adding a unique label to individual application paths where the application paths are individual loops and individual functions in the application. An analysis is created of the labeled application paths by executing the application with the labeled paths, reviewing the error report for data related to the labels and if an error is sufficiently related to application paths with labels, storing the path that created the errors in a report. If an error is not sufficient related to the application path with labels, the method is repeated by the creating the analysis again by substituting additional application paths for the application paths. | 04-08-2010 |
| 20100095153 | Apparatus and Method for Diagnosing Abnormal Conditions - The present invention discloses an apparatus and a method for diagnosing abnormal conditions, that quantitatively considers acquisition difficulties between abnormal symptoms provided on a computer screen and quantifies acquisition difficulties of the abnormal symptoms through distinctiveness of measuring devices to exactly diagnose the abnormal conditions even under an improved control environment, making it possible for a user to rapidly and easily diagnose the abnormal conditions that may be generated from a complicated device. | 04-15-2010 |
| 20100107009 | DETERMINISTIC COMPONENT MODEL JUDGING APPARATUS, JUDGING METHOD, PROGRAM, RECORDING MEDIUM, TEST SYSTEM AND ELECTRONIC DEVICE - There is provided a deterministic component model identifying apparatus for determining a model of a deterministic component contained in a probability density function supplied thereto. The deterministic component model identifying apparatus includes a spectrum calculating section that calculates a spectrum of the probability density function on an axis of a predetermined variable, a null value detecting section that detects a null value on the axis of the predetermined variable in the calculated spectrum, a theoretical value calculating section that calculates a theoretical value of a spectrum of the deterministic component in association with each of a plurality of predetermined deterministic component models, based on the null value detected by the null value detecting section, and a model determining section that determines the model of the deterministic component contained in the probability density function based on a spectrum difference representing a difference between the spectrum calculated by the spectrum calculating section and the theoretical value of the spectrum of the deterministic component calculated in association with each of the plurality of predetermined deterministic component models. | 04-29-2010 |
| 20100125753 | PREDICTIVE DIAGNOSTICS AND FAULT MANAGEMENT - The present application discloses a preventative, diagnostic maintenance system designed for gaming systems. Sensor and software monitor, accumulate, store and share information for efficient maintenance of the gaming systems. Diagnostic and prognostic tests are run and results prioritized wherein minor and intermittent problems that indicate potential future problems are stored. When a technician visit is prescribed, the system will present via a GUI a visualization of the status of gamed devices, and, forearm the technician with the high and low priority information regarding the high priority problems along with the low priority problems for all the game devices at the same site. The technician will be able to bring the specific tools, programs and parts to service the high and the low priority problems of all the game devices. | 05-20-2010 |
| 20100131799 | Trouble emulator for a rules-based diagnostic system - Embodiments of the present invention are directed to validating a rules-based diagnostic system for a network. Emulated data for use by the rules-based diagnostic system can be generated that includes a trouble ticket to emulate a problem associated at least one of Layer 1 and Layer 2 network services and includes network information associated with the problem. Responses from the rules-based diagnostic system can be received in response to the emulated data being processed by the rules-based diagnostic system. A log generated by the rules-based diagnostic system can be analyzed to determine rules implemented by the rules-based diagnostic system in response to the emulated data, thereby validating operation of the rules-based diagnostic system. | 05-27-2010 |
| 20100138694 | Root-Cause Analysis System And Associated Methods - A method for determining a root cause of a problem in a multiple-element system includes correlating an incoming alarm signal with an element x in a multiple-element system and accessing an implication list comprising a list of all elements upstream of element x. At least one element on the implication list is weighted with data relating to the at least one element. Taking into account the weighting step, a probability is calculated that an element on the implication list comprises a most-probable root cause of the subsequent alarm signal. The identified most-probable root cause of the incoming alarm signal is output. | 06-03-2010 |
| 20100146336 | MULTI-MODAL GREEN COMPUTING FUSION USING PROBLEM ANALYTICS - A system, method and program product for processing a computational problem for a computing center having a plurality of computing resources. The system includes: a problem analytics system for generating a characterized problem description from an inputted computational problem using at least one of a keyword nonparametric inverse indexing or a nonparametric data structure analysis; a system for selecting a model that resembles the characterized problem description by comparing the characterized problem description with a set of models; and a system for generating a computing solution for running the inputted computational problem on the computing center based on a selected model and a set of environment factors associated with the computing center. | 06-10-2010 |
| 20100174945 | COMMUNICATION NETWORK FAILURE CAUSE ANALYSIS SYSTEM, FAILURE CAUSE ANALYSIS METHOD, AND FAILURE CAUSE ANALYSIS PROGRAM - A failure cause analysis system for estimating a cause of a failure in a communication network from recorded contents of internal processing of a communication apparatus includes: feature extraction means for extracting a statistical feature of the recorded contents at a time of occurrence of a failure; and failure cause estimation means for estimating a failure cause based on similarity between a statistical feature of the recorded contents that is acquired at a time of occurrence of a past failure with a known failure cause and the statistical feature of the recorded contents that is acquired at the time of occurrence of the failure. The failure cause analysis system of a communication network provided can acquire the correspondence between failure features and failure causes from past failure cases irrespective of the number of cases as to communication network failures that are detected from process logs retained in communication apparatuses, and quantitatively incorporate the range of dispersion of the features into a judgment to estimate the cause of occurrence of a failure. | 07-08-2010 |
| 20100192013 | System and Method for Automated Distributed Diagnostics for Networks - A method for distributed computations for fault-diagnosis in a system whose fault propagation model has deterministic couplings between faults and symptoms includes creating a ‘relation graph’ in which the nodes correspond to the potential faults, with two nodes connected by a ‘relational link’ if their corresponding faults have an observed symptom in common. The relation graph is then partitioned into several domains, while minimizing the number of cross-domain relational links, which correspond to cross-domain symptoms. In each domain, all the optimal local solutions to the domain's sub-problem are first determined, and then a combination is selected of the local solutions, one from each domain, that explains the maximum number of cross-domain symptoms, where the optimal solution is supplemented, if necessary, with additional faults to explain any remaining unexplained cross-domain symptoms, determining also a bound on the deviation from optimality of the global solution. | 07-29-2010 |
| 20100205483 | OPERATION MANAGEMENT APPARATUS AND METHOD THEREOF - An operation management apparatus monitors the performance information of a system executing services and extracts correlation variants of the performance information, thus allowing the management to detect and localize performance-degrading faults of the system. It is determined whether or not the range of correlation collapse ascribed to the performance information falls within the normal range of correlation collapse measured in the normal operation of the system. A history is retained with regard to the range of correlation collapse ascribed to the performance information which does not fall within the normal range of correlation collapse. It is determined whether or not the history accumulating the predetermined number of ranges of correlation collapse approximates to the fault range of correlation collapse measured in the faulty operation of the system, thus discriminating a fault model on the basis of the performance information. | 08-12-2010 |
| 20100223500 | METHOD AND DEVICE FOR DETERMINING A PROBABILITY OF OCCURRENCE - IN a method and a device for determining a probability of occurrence that an overall system fulfills a predefined system performance, the overall system is composed of instances of different classes of partial systems, and each class of partial systems has an associated class fault tree. The method has the following steps: (a) calculating (S | 09-02-2010 |
| 20100241901 | Method and apparatus for checking a control program in an industrial system - Industrial systems ( | 09-23-2010 |
| 20100306587 | COMPUTATIONALLY EFFICIENT TIERED INFERENCE FOR MULTIPLE FAULT DIAGNOSIS - A computer based method and system for tiered inference multiple fault diagnosis is provided. The method includes using a computer processor to dissect a hypothesis space representing a production system having a plurality of production modules into tiers. Production modules in the current tier are partitioned into a group or a set of sub-groups. A fault diagnosis algorithm is applied to the group of each sub-group to identify an acceptable fault diagnosis. When no acceptable fault diagnosis is found, the process moves to the next tier to perform further investigations. The process continues to move to higher tiers until an acceptable fault diagnosis is obtained or the system instructs the process to end. | 12-02-2010 |
| 20100306588 | Intelligent Integrated Diagnostics - A diagnostic tools and methods are disclosed. The diagnostic tool is configured or operable to nominate a commonly connected component in a target system as being faulty if more than a pre-determined number of active components connected to the commonly connected component appear faulty. | 12-02-2010 |
| 20100313070 | BROKEN-SPHERES METHODOLOGY FOR IMPROVED FAILURE PROBABILITY ANALYSIS IN MULTI-FAIL REGIONS - A failure probability for a system having multi-fail regions is computed by generating failure directions in a space whose dimensions are the system parameters under consideration. The failure directions are preferably uniform, forming radial slices. The failure directions may be weighted. The radial slices have fail boundaries defining fail regions comparable to broken shells. The distribution of the system parameters is integrated across the broken shell regions to derive a failure contribution for each failure direction. The failure probability is the sum of products of each failure contribution and its weight. Failure contributions are computed using equivalent expressions dependent on the number of dimensions, which can be used to build lookup tables for normalized fail boundary radii. The entire process can be iteratively repeated with successively increasing failure directions until the failure probability converges. The method is particularly useful in analyzing failure probability of electrical circuits such as memory cells. | 12-09-2010 |
| 20100318846 | SYSTEM AND METHOD FOR INCIDENT MANAGEMENT ENHANCED WITH PROBLEM CLASSIFICATION FOR TECHNICAL SUPPORT SERVICES - A system and method of problem determination and resolution utilizes enhanced problem classification, and effectively categorizes any problem a user experiences by leveraging all available data to recognize the specific problem. Historical problem data is labeled with the cause of that problem and is analyzed to learn problem patterns. The historical problem data is classified into a predefined hierarchical structure of taxonomies by using an incremental online learning algorithm. The hierarchical structure and learned patterns are utilized to recognize problems and generate the root cause of the problem when given a new set of monitoring data and log data. | 12-16-2010 |
| 20100318847 | TECHNIQUES FOR BUILDING AN AGGREGATE MODEL FOR PERFORMING DIAGNOSTICS - Techniques for building a model for performing diagnostics. In one embodiment, a set of models is determined based upon a topological relationship created upon receiving an alert or a request for which diagnostics are to be performed. An aggregate model is then generated based upon the set of models and the topological relationship. The aggregate model is then used for performing the diagnostics. | 12-16-2010 |
| 20100325487 | METHOD AND SYSTEM FOR AUTOMATICALLY DIAGNOSING FAULTS IN RENDERING DEVICES - A method and system for automatically determining an optimal re-training interval for a fault diagnoser based on online monitoring of the performance of a classifier. The classifier generates a soft measure of membership in association with a class based on a training data. The output of the classifier can be utilized to assign a label to new data and then the members associated with each class can be clustered into one or more core members and potential outliers. A statistical measure can be utilized to determine if the distribution of the outliers is sufficiently different than the core members after enough outliers have been accumulated. If the outliers are different with respect to the core members, then the diagnoser can be re-trained; otherwise, the output of the classifier can be fed to the fault diagnoser. | 12-23-2010 |
| 20100325488 | FUZZY LOGIC APPROACH IN TEMPORAL FAULT REASONING AND APPLICATION IN AIR HANDLING UNITS - A system that transforms information into fuzzy observable states. These states may be matched against a mapping table which indicates which observable state admits or excludes particular faults. This information may be processed over time when in each time instant the admitted or excluded faults are used for updating the rate for each fault. | 12-23-2010 |
| 20100325489 | FAULT ANALYSIS APPARATUS, FAULT ANALYSIS METHOD, AND RECORDING MEDIUM - The present invention determines the type of each piece of system information including a plurality of index values indicative of abnormality levels of a monitoring target device, as follows. The system information and identification information for the system information are sequentially received from the monitoring target device configured to sequentially output the system information together with the identification information for the system information. The piece of the received system information is compared with a predetermined determination criterion and thus determined to be of a particular type based on a result of the comparison. The determined type is output in association with the identification information. Input information indicative of a true type is accepted and stored in association with the identification information. The determination criterion is updated based on the piece of the system information and the information indicative of the true type. In the type determination procedure, an index value irrelevant to the abnormality level of the monitoring target device is included in the piece of the system information for comparison with the determination criterion. | 12-23-2010 |
| 20110022891 | Method for the Generation of a Set of Conflicts for Model-Based System Diagnostics, and Corresponding Diagnostic Method - A method for the generation of a set of conflicts for model-based system diagnostics is described, with which system a plurality of sensors is associated for the observation of variables indicative of operation conditions. | 01-27-2011 |
| 20110055631 | PLUGGABLE ERROR DETECTION BOARD AND MOTHERBOARD ERROR DETECTION SYSTEM CONTAINING THE SAME - A motherboard error detection system includes a pluggable error detection board and a motherboard having a boot management chip. When the motherboard enters a device-driven status from a standby status, the boot management chip is used to manage power-on timings of different voltage sources; to collect a plurality of sets of status information; and to check whether the sets of status information and the power-on timings have errors. The pluggable error detection board includes an interpreting unit, a message-reading interface and a connector which is pluggably disposed on the motherboard. When the boot management chip notifies the pluggable error detection board to read an error message, the interpreting unit converts the error message to human-readable information, and the human-readable information is outputted through the message-reading interface. | 03-03-2011 |
| 20110060946 | METHOD AND SYSTEM FOR PROBLEM DETERMINATION USING PROBE COLLECTIONS AND PROBLEM CLASSIFICATION FOR THE TECHNICAL SUPPORT SERVICES - A system and method for problem determination using probe collections and problem classification for the technical support services monitor and collect data associated with a computer system, raise an alarm based on the monitored and collected data, probe the computer system for additional information, filter the monitored and collected data based on the additional information established from probing, and use the filtered data to label a problem associated with the raised alarm. | 03-10-2011 |
| 20110087922 | TEST METHOD AND TOOL FOR MASTER-SLAVE SYSTEMS ON MULTICORE PROCESSORS - A test method for a master-slave concurrent system running on a multicore processor includes the steps of establishing a PFA, otherwise called probabilistic finite automata, or probabilistic finite state machine, for a given regular expression; generating test patterns by running the PFA; splitting and merging the test patterns to generate an interleaved test pattern; and performing test on the master-slave system according to the interleaved test pattern. In an embodiment, the method further includes a step of debugging failures of the multicore processor during testing. | 04-14-2011 |
| 20110087923 | ONLINE FORMAL VERIFICATION OF EXECUTABLE MODELS - A system and method for automatic formal verification of an executable model includes an assertion monitor configured to verify a system against an assertion in a specification. The assertion monitor includes a parser configured to generate a propositional formula representing the assertion in the specification using Boolean propositions, a filter configured to generate a run of the system using truth assignments for the propositional symbols, and a trace verifier configured to verify the assertion using the run of the system using truth assignments for the propositional symbols and the propositional formula. | 04-14-2011 |
| 20110087924 | Diagnosing Abnormalities Without Application-Specific Knowledge - Methods, articles, and systems for determining a probable cause of a component's abnormal behavior are described. To determine the probable cause, a computing device computes, for one or more pairs of components having dependency relationships, a likelihood that behavior of one component of a pair is impacting behavior of the other component of the pair. This computing is based on joint historical behavior of the pair of components. The computing device then determines that one of a plurality of components is a probable cause of the abnormal behavior based on the computed likelihoods. | 04-14-2011 |
| 20110145640 | System for Automated Computer Support - Systems and methods for providing automated computer support are described herein. One described method comprises receiving a plurality of snapshots from a plurality of computers, storing the plurality of snapshots in a data store, and creating an adaptive reference model based at least in part on the plurality of snapshots. The described method further comprises comparing at least one of the plurality of snapshots to the adaptive reference model, and identifying at least one anomaly based on the comparison. | 06-16-2011 |
| 20110154109 | CONTINUOUS, AUTOMATED DISCOVERY OF BUGS IN RELEASED SOFTWARE - According to aspects illustrated herein, there is provided a method, system, and computing device for identifying bugs in a software application. The method provides for hosting the software application on a cloud server and providing the software application to a group of users and monitors usage of the software application. Next, new usage patterns are identified by identifying current usage patterns based on the monitoring are identified and comparing the current usage patterns to stored usage patterns. After that, bugs are identified by: 1) automatically generating a set of new test matrices based on the new usage patterns; 2) automatically running the set of new test matrices on the software application, while the software application is being used; 3) recording error messages generated; and 4) correlating the error messages with the new usage patterns to identify the bugs. Then, a reporting message is generated to report the identified bugs. | 06-23-2011 |
| 20110173496 | INTELLIGENT CONDITION MONITORING AND FAULT DIAGNOSTIC SYSTEM FOR PREVENTATIVE MAINTENANCE - A system for condition monitoring and fault diagnosis includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses. | 07-14-2011 |
| 20110185230 | LEARNING PROGRAM BEHAVIOR FOR ANOMALY DETECTION - A computer-enabled method of learning the behavior of a program. A processor can execute a target program during a learning interval while varying a plurality of stimuli provided to the target program so as to produce a multiplicity of different sequences of events which differ in combinations of types of events in respective sequences, orders in which the types of events occur in respective sequences, or in the combinations and in the orders in which the types of events occur. The multiplicity of event sequences can be recorded, and a second program can be executed by a processor to: determine a plurality of clusters based on similarities between the event sequences in their entirety; and determine a plurality of signatures corresponding to the plurality of clusters. Each signature can be the longest common subsequence of all sequences in the respective cluster and thus representative of the cluster. In such method, each of the plurality of signatures can be a benchmark representative of acceptable behavior of the target program. | 07-28-2011 |
| 20110209001 | TIME MODULATED GENERATIVE PROBABILISTIC MODELS FOR AUTOMATED CAUSAL DISCOVERY - Dependencies between different channels or different services in a client or server may be determined from the observation of the times of the incoming and outgoing of the packets constituting those channels or services. A probabilistic model may be used to formally characterize these dependencies. The probabilistic model may be used to list the dependencies between input packets and output packets of various channels or services, and may be used to establish the expected strength of the causal relationship between the different events surrounding those channels or services. Parameters of the probabilistic model may be either based on prior knowledge, or may be fit using statistical techniques based on observations about the times of the events of interest. Expected times of occurrence between events may be observed, and dependencies may be determined in accordance with the probabilistic model. | 08-25-2011 |
| 20110231703 | BAYESIAN APPROACH TO IDENTIFYING SUB-MODULE FAILURE - A diagnostic device identifies failed sub-modules within a larger system based on error codes received from the system. The device stores a likelihood matrix that correlates each sub-module with each possible error code and maintains a likelihood value corresponding to the probability of a failed sub-module generating a corresponding error code and stores a prior probability of failure associated with each sub-module based on prior observational data. In response to received error codes, the device calculates a posterior probability of failure for each of the plurality of sub-modules based on a product of the likelihood values corresponding to the received error codes and the prior probability of failure associated with each sub-module. Based on the calculated posterior probability, the device identifies the sub-module with the highest posterior probability of failure as the failed sub-module. | 09-22-2011 |
| 20110231704 | METHODS, APPARATUS AND ARTICLES OF MANUFACTURE TO PERFORM ROOT CAUSE ANALYSIS FOR NETWORK EVENTS - Example methods, apparatus and articles of manufacture to perform root cause analysis for network events are disclosed. An example method includes retrieving a symptom event instance from a normalized set of data sources based on a symptom event definition; generating a set of diagnostic events from the normalized set of data sources which potentially cause the symptom event instance, the diagnostic events being determined based on dependency rules; and analyzing the set of diagnostic events to select a root cause event based on root cause rules. | 09-22-2011 |
| 20110239045 | EVALUATING APPARATUS AND EVALUATING PROGRAM PRODUCT - According to one embodiment, an evaluating apparatus includes an operation data storage unit, a labeling unit, a learning unit, and an evaluating unit. The labeling unit applies a failure label, indicating that a product is broken down, to operation data of the product that is broken down within a designated period of time from the observation date of the operation data, while applies a non-failure label, indicating that the product is not broken down, to the operation data of the product that is not broken down within a designated period of time from the observation date of the operation data. The labeling unit applies neither the failure label nor the non-failure label to the operation data of the product, which is not certain that it is broken down or not within a designated period of time from the observation date of the operation data. | 09-29-2011 |
| 20110276828 | APPARATUS ANOMALY MONITORING METHOD AND SYSTEM - There is provided a technique related to an apparatus anomaly monitoring method and capable of achieving a model which can detect an anomaly with high accuracy, monitoring with using the model, and others. In an apparatus anomaly monitoring system, a model creation module ( | 11-10-2011 |
| 20110296242 | ENERGY-EFFICIENT FAILURE DETECTION AND MASKING - A method, system, and computer usable program product for energy-efficient soft error failure detection and masking are provided in the illustrative embodiments. A soft error is injected to occur during execution of a set of instructions. If an output of the execution of the set of instructions is incorrect, a record is made of the instruction that was affected by the injected soft error and led to the incorrect result. This identified instruction is designated as vulnerable to the soft error. Several soft errors are injected with different input data sets over several executions of the same set of instructions, and a probability of each instruction in the instruction set is computed, the probability of an instruction accounting for the vulnerability of the execution of the instruction sets to errors that affect the instruction. A report including several probabilities of instruction vulnerabilities is produced. | 12-01-2011 |
| 20110296243 | Recommendation of Relevant Information to Support Problem Diagnosis - The disclosure generally relates to knowledge retrieval using a knowledgebase storing general and/or expert knowledge. In particular, the disclosure relates to using complex retrieval techniques to implement an enhanced troubleshooting system that provides relevant information. Aspects of the disclosure retrieve relevant documents to assist in troubleshooting by reasoning with stored representations about the faulty system and its operating environment. After receiving a description of the symptoms and/or other information related to the problem, the system may recommend textual and/or non-textual documents with relevant information for identifying the cause of the problem and restoring operation. | 12-01-2011 |
| 20110314330 | MANAGEMENT APPARATUS AND MANAGEMENT METHOD - A management apparatus and a management method that enable parsing processing to be executed efficiently by means of a working memory of a fixed size are proposed. One or more predefined rules are divided into one or more rule segments that comprise a condition and a conclusion that each form part of the rule, and the rule segments obtained through the division are stored in the secondary storage, and when an event notification from the information processing device is received, one or more related rule segments are selected and, by linking the selected one or more rule segments in the memory as required, a rule parsing network is constructed that indicates relationships between rules in the memory, an inference is derived on the basis of the constructed rule parsing network, and rule segments that are not readily used in inference derivation are deleted from the memory. | 12-22-2011 |
| 20110314331 | AUTOMATED TEST AND REPAIR METHOD AND APPARATUS APPLICABLE TO COMPLEX, DISTRIBUTED SYSTEMS - An intelligent system for automatically monitoring, diagnosing, and repairing complex hardware and software systems is presented. A number of functional modules enable the system to collect relevant data from both hardware and software components, analyze the incoming data to detect faults, further monitor sensor data and historical knowledge to predict potential faults, determine an appropriate response to fix the faults, and finally automatically repair the faults when appropriate. The system leverages both software and hardware modules to interact with the complex system being monitored. Additionally, the lessons learned on one system can be applied to better understand events occurring on the same or similar systems. | 12-22-2011 |
| 20110314332 | Failure cause estimation device and failure cause estimation method - A failure cause estimation device includes: a database that manages the causes of failure cases, questions, and replies thereto for each of the failure cases; a condition presentation unit that presents combinations of the questions and replies managed in the database on a display screen as branch conditions used to classify the cause of a failure case; a condition selection unit that selects at least one branch condition from the presented branch conditions according selection operation; a cause estimation unit that estimates a cause satisfying the at least one branch condition from the contents of the database; and a cause presentation unit that presents the estimated cause on the display screen as a cause candidate. | 12-22-2011 |
| 20120005532 | METHOD AND APPARATUS FOR DETERMINING RANKED CAUSAL PATHS FOR FAULTS IN A COMPLEX MULTI-HOST SYSTEM WITH PROBABILISTIC INFERENCE IN A TIME SERIES - A method and apparatus are provided for determining that problems have occurred within a complex multi-host system and for identifying for each problem, sequences of causes and effects called a fault cause path, starting with a root cause. A probabilistic model representing the cause/effect relationships among potential system problems identifies the probability that a problem occurred in the system. Such failure probabilities may be determined based on aggregating, over a recent time interval, probability of failure values determined by the probabilistic model. Each fault cause path may have an associated probability of accuracy value reflecting the expected accuracy of the fault cause path relative to other fault cause paths. When more than one fault cause path is identified, the number and order of the fault cause paths may be ranked and displayed based on their probability of accuracy value. | 01-05-2012 |
| 20120005533 | Methods And Apparatus For Cross-Host Diagnosis Of Complex Multi-Host Systems In A Time Series With Probablistic Inference - A method and apparatus are provided for performing cross-host root cause diagnosis within a complex multi-host environment. In a multi-host environment, sometimes system failures on one host may cause problems at another host within the same environment. A probabilistic model is used to represent failures that can occur within each host in the environment. The cause and effect relationships among these failures together with measurement values are used to generate a probability that each potential failure occurred in each host. When a problem is observed on one host without detecting a corresponding root cause within the same host, a cross-host failure diagnosis is performed. The probabilistic models for other hosts in the environment are used to determine the most likely cause of the failure. | 01-05-2012 |
| 20120005534 | METHOD AND APPARATUS FOR DEALING WITH ACCUMULATIVE BEHAVIOR OF SOME SYSTEM OBSERVATIONS IN A TIME SERIES FOR BAYESIAN INFERENCE WITH A STATIC BAYESIAN NETWORK MODEL - A method and apparatus are provided for determining the probability that one or more problems have occurred within a complex multi-host system. A probabilistic model representing the cause/effect relationships among potential system problems identifies the probability that a problem occurred in the system based at least on system measure states that are input into the probabilistic model. System measure states may be determined based on an aggregation of system measurement values taken periodically. Aggregating system measurement values may be performed over system measurement values that were taken during a recent time interval. A rolling count aggregation function may be used for this purpose. A rolling count function counts the number of system measurement values taken within the recent time interval that lie within a particular range of values. A system measure state may be determined based on whether the rolling count exceeds a threshold associated with the system measure. | 01-05-2012 |
| 20120005535 | FAILURE DIAGNOSTIC SYSTEM, ELECTRONIC CONTROL UNIT FOR VEHICLE, FAILURE DIAGNOSTIC METHOD - A failure diagnostic system ( | 01-05-2012 |
| 20120017117 | Solving Hybrid Constraints to Validate Specification Requirements of a Software Module - In one embodiment, a method includes analyzing one or more first numeric constraints and one or more first string constraints associated with a software module including one or more numeric variables and string variables; inferring one or more second numeric constraints applying to specific ones of the string variables; inferring one or more second string constraints applying to specific ones of the numeric variables; representing each one of the first and second numeric constraints with an equation; representing each one of the first and second string constraints with a finite state machine; and validating the software module with respect to one or more requirements associated with the software module by attempting to solve for a solution including one or more values for specific ones of the numeric and string variables that satisfies all the first and second numeric constraints, all the first and second string constraints, and all the requirements. | 01-19-2012 |
| 20120066547 | Problem Record Signature Generation, Classification and Search in Problem Determination - A method for problem determination and resolution in an information technology (IT) system includes receiving a problem ticket, searching a database for a plurality of problem features based on data included in the problem ticket, extracting the plurality of problem features from the database, and generating a problem signature corresponding to the problem ticket, wherein the problem signature comprises at least one non-textual feature extracted from the plurality of problem features. | 03-15-2012 |
| 20120079324 | FIRMWARE TRACING IN A STORAGE DATA COMMUNICATION SYSTEM - A method includes generating trace data at a device associated with data communication to and from a computer storage device through an appropriate communication link therefor and transmitting the trace data through the appropriate communication link. The trace data is configured to enable debugging of a set of instructions associated with the device. The method also includes capturing the trace data transmitted through the appropriate communication link through a protocol analyzer, a host system or the protocol analyzer coupled to the host system and analyzing the trace data therein to obtain information associated with the set of instructions associated with the device. The protocol analyzer, the host system or the protocol analyzer coupled to the host system is configured to be external to the device associated with the data communication to and from the computer storage device. | 03-29-2012 |
| 20120089868 | FUZZ TESTING OF ASYNCHRONOUS PROGRAM CODE - A fuzz testing system is described herein that represents event sources, channels, processors, and consumers as first-class entities in an application. Abstracting event-related entities allows fuzzing through injecting, dropping, reordering, and delaying events from within the application. This translates into the ability to localize the areas under test and perform fuzzing in a systematic manner. In some embodiments, the fuzz testing system tests concurrent asynchronous and event-based code, and can generate event streams based on a given statistical distribution. Representing events, event sources, processors, and sinks as first-class objects provides easy access to the event handlers and facilitates implementing fuzzing by introducing event processors between the source and the sink. Thus, the fuzz testing system improves the testability of applications and APIs with asynchronous behavior and provides a uniform framework for introducing fuzz testing into such applications. | 04-12-2012 |
| 20120089869 | Pessimistic Model-Based Testing - Model-based testing is performed by repeatedly constructing a test strategy in which each test stimulus will lead to increased test coverage regardless of the nondeterministic choices made by the system under test, and following said strategy until coverage is increased. As soon as no such strategy exists, testing stops. | 04-12-2012 |
| 20120102359 | System for Automated Computer Support - Systems and methods for providing automated computer support are described herein. One described method comprises receiving a plurality of snapshots from a plurality of computers, storing the plurality of snapshots in a data store, and creating an adaptive reference model based at least in part on the plurality of snapshots. The described method further comprises comparing at least one of the plurality of snapshots to the adaptive reference model, and identifying at least one anomaly based on the comparison. | 04-26-2012 |
| 20120117424 | SYSTEM-LEVEL TESTCASE GENERATION - A system-level testcase may be generated by performing system-level generation tasks by a system-level generator to produce an abstract testcase. Based upon the abstract testcase, one or more unit-level generators may generate the testcase. The testcase may be utilized in simulation of operation of a system-under-test (SUT). The testcase may be utilized for verification of the SUT. The SUT may comprise a plurality of units. The unit-level generator may be associated with units of the SUT and perform generation tasks associated with pertinent units. | 05-10-2012 |
| 20120117425 | METHOD AND APPARATUS FOR OBTAINING FEEDBACK FROM A DEVICE FOR RECOMMENDATIONS - A system and method for utilizing user feedback of a user device. The method includes accessing a troubleshooting request for a user device and obtaining use pattern data of a user's use pattern of the user device. Operational setting information of the user device is obtained. Next, analysis of the use pattern data and the operational setting information of the user device is performed. A customized troubleshooting step list is generated, which is based on the analysis. A plurality of troubleshooting steps is performed in a sequence based on the customized troubleshooting step list. | 05-10-2012 |
| 20120124421 | Error management within a data processing system - A data processing system | 05-17-2012 |
| 20120124422 | DESCRIPTION LANGUAGE FOR IDENTIFYING PERFORMANCE ISSUES IN EVENT TRACES - A description language and a tool for identifying, analyzing and addressing performance issues in event traces. With this language, a behavior descriptor may be defined to describe a simple behavior within a performance trace, by specifying values for a relatively small number of attributes. Even a relatively unsophisticated user can define behavior descriptors, but complex behaviors may be defined based on interactions between multiple behavior descriptors. A trace analysis tool may use a library of behavior descriptors to identify performance issues in performance traces by matching behavior descriptors to the performance trace. This analysis may be used in any number of ways, including reporting to a user detected performance issues reflected in a set of performance traces, filtering a set of performance traces to remove those performance traces corresponding to known performance issues or prioritizing efforts to resolve performance issues. | 05-17-2012 |
| 20120144237 | METHOD OF EFFICACY ANTICIPATION AND FAILURE EXAMINATION FOR AN APPARATUS - A method of efficacy anticipation and failure examination for an apparatus is disclosed. The method first establishes an anticipation model, and then trains the anticipation model by calibrating the same using errors obtained between a realistic data and an anticipated data, so as to use the calibrated anticipation model to estimate the performance efficacy of an apparatus or any component in the apparatus, and also to acknowledge if there is any abnormality occurred during the operation of the apparatus or the component. | 06-07-2012 |
| 20120159250 | COMPATIBILITY TESTING USING TRACES, LINEAR TEMPORAL RULES, AND BEHAVIORAL MODELS - A “Compatibility Tester” extracts observable behaviors from different system implementations (e.g., software, operating systems, device drivers, hardware interfaces, etc.), then performs compatibility testing via comparisons of the extracted behaviors. Traces (e.g., bus level signals between controllers and hardware devices or commands between software components) representing observable behaviors of different implementations of a system are captured. Temporal and structural rules are then mined from these traces. The mined rules (or a model constructed from those rules) are used by a “Rule Checking” process that determines whether reference rules (mined from a known compatible system) are compatible with rules mined from test traces of a second system. Invalid rules are flagged as behavioral compatibility bugs. Alternately, the mined rules are used by a “Rule Diffing” process that performs set differencing of the behavioral and structural rules mined from the different system implementations, with differences between the systems flagged as behavioral compatibility bugs. | 06-21-2012 |
| 20120166874 | Wireless Device Expert System - A wireless expert system connects to a plurality of diagnostic modules and is configured to receive a complaint from a user of a wireless device, the complaint comprising data and attributes. The expert system executes a two-phase process. In the first phase, the complaint is analyzed to determine which of the diagnostic modules should be run. In the second phase, the selected diagnostic modules are run, and the user is provided with a recommended corrective action. If the action is successful, the expert system is updated with the successful resolution, providing additional assurance for future analyses. | 06-28-2012 |
| 20120173927 | SYSTEM AND METHOD FOR ROOT CAUSE ANALYSIS - Systems and methods for determining the root cause of an event in a data center are presented. The system includes a data center management device coupled to a network and configured to receive an indication of the event from a physical infrastructure device via the network, determine a first generic cause model for the event by accessing an event cause model data store, determine a first event profile by adapting the first generic cause model to the data center using data center profile information stored in a data center profile data store and display a first probability that a potential cause defined by the first event profile is the root cause. | 07-05-2012 |
| 20120185728 | SYSTEM AND METHOD FOR DETECTING AND/OR DIAGNOSING FAULTS IN MULTI-VARIABLE SYSTEMS - A method for detecting faulty operation of a multi-variable system is described. The method includes receiving operational data from a plurality of components of the multi-variable system and processing the operational data in accordance with a plurality of dynamic machine learning fault detection models to generate a plurality of fault detection results. Each fault detection model uses a plurality of variables to model one or more components of the multi-variable system and is adapted to detect normal or faulty operation of an associated component or set of components of the multi-variable system. The plurality of fault detection results are output. | 07-19-2012 |
| 20120198277 | Method for Detecting Anomalies in a Control Network - A method for monitoring and controlling, industrial or building automation to detect anomalies in a control network, wherein a technology of an intrusion detection system (IDS) is configured to analyze a time sequence and time intervals of correct messages in the network traffic and to use the messages to train an anomaly detection system. Detecting a time sequence and a rhythm of correct messages allows for the detection of malfunctions or manipulations of devices and attacks that are performed using regular monitoring or control stations that have been taken over by attackers or that are defect, and that cannot be detected using content-based methods or by a considerable increase of data traffic. An additional security barrier is thus provided that can continue monitoring and protecting a technical unit from possible acts of sabotage, even if the control network of the technical unit has already been corrupted. | 08-02-2012 |
| 20120226940 | Self-Expanding Test Automation Method - A method for automatically testing an apparatus controlled by software based on pilot test case file comprising user input sequence data recorded manually and the time stamp of the input. In the process of automated testing, these pre-recorded user inputs are replay with same input sequence but with either the same time interval between two subsequent inputs recorded prior; or with a random time interval autonomously generated in a range set by the test configuration. During the process of replaying user input, a separate plural numbers of background tasks are executed in parallel with random execution delays to generate varying system load and execution timing to simulate the apparatus' unpredictable real operation scenarios. The user input and new random time interval between each user input are recorded at replay as a new expanded test record file for later test result trace and failure analysis. | 09-06-2012 |
| 20120233501 | Configuration Based Service Availability Analysis of AMF Managed Systems - An Availability Management Framework (AMF) configuration describes how configuration entities of a highly available system are grouped and includes information on service provision and service protection policies against resource failure. The AMF configuration defines a set of failure types for each component and each node, and specifies a failure rate and a recommended recovery for each failure type. A method for evaluating service availability receives the AMF configuration as input, and analyzes it to obtain an actual recovery that the highly available system is to perform when the given component fails. The method maps the AMF configuration to a stochastic model that captures the dependencies among the components and among the configuration entities at multiple levels of the hierarchy. The method utilizes the model to calculate the service availability of the AMF configuration based on the failure rate, the actual recovery and the dependencies. | 09-13-2012 |
| 20120266020 | SYSTEM, METHOD, AND APPARATUS FOR RESOLVING ERRORS IN A SYSTEM - A system includes at least one monitored device collect data detect and detect an error in the data, a central server, and at least one local server communicatively coupled to the monitored device and the central server. The local server is configured to receive the data and an indication of the error detected from the monitored device, determine a solution for use in resolving the error, transmit instructions to perform the solution to the monitored device, and transmit the error and the solution to the central server for storage. | 10-18-2012 |
| 20120272099 | COMPUTER HARDWARE AND SOFTWARE DIAGNOSTIC AND REPORT SYSTEM - The present invention tests computer systems for defects that are able to cause performance and functional problems. An agent application is first installed on a user's system. The agent application then retrieves problem data from the expert system library pertinent to the user's operating environment. The agent application tests the user's system for each problem description within a downloaded data structure from the expert system library. If a problem is discovered, a script attempts to remediate the problem and/or notifies the user, describing the issue. If an unknown problem arises, a feedback mechanism expands the expert system library by sending a notification that a problem was discovered. The feedback is then utilized to increase the total knowledge in the expert system library. Then when another user with a similar or the same setup is tested, the agent application will recognize the issue and will take the appropriate remedial actions. | 10-25-2012 |
| 20120290879 | METHOD AND DEVICE FOR MONITORING THE STATE OF A FACILITY - This invention provides method for detecting advance signs of anomalies, event signals outputted from the facility are used to create a separate mode for each operating state, a normal model is created for each mode, the sufficiency of learning data for each mode is checked, a threshold is set according to the results of said check, and anomaly identification is performed using said threshold. Also, for diagnosis, a frequency matrix is created in advance, with result events on the horizontal axis and cause events on the vertical axis, and the frequency matrix is used to predict malfunctions. Malfunction events are inputted as result events, and quantized sensor signals having anomaly measures over the threshold are inputted as cause events. | 11-15-2012 |
| 20120304007 | METHODS AND SYSTEMS FOR USE IN IDENTIFYING ABNORMAL BEHAVIOR IN A CONTROL SYSTEM - Methods and apparatus for use in identifying abnormal behavior in a control system. Operating events associated with a control system are received, and an actual behavior of the control system is determined based on the received operating events. The actual behavior is compared to expected behavior to determine whether the actual behavior differs from the expected behavior. The expected behavior includes a correlation between a plurality of operating events associated with the control system. The expected behavior is updated based on an indication of whether the actual behavior is abnormal from a user. | 11-29-2012 |
| 20120304008 | SUPERVISED FAULT LEARNING USING RULE-GENERATED SAMPLES FOR MACHINE CONDITION MONITORING - A machine fault diagnosis system is provided. The system combines a rule-based predictive maintenance strategy with a machine learning system. A simple set of rules defined manually by human experts is used to generate artificial training feature vectors to portray machine fault conditions for which only a few real data points are available. Those artificial training feature vectors are combined with real training feature vectors and the combined set is used to train a supervised pattern recognition algorithm such as support vector machines. The resulting decision boundary closely approximates the underlying real separation boundary between the fault and normal conditions. | 11-29-2012 |
| 20120324286 | UTILIZING AUXILIARY VARIABLES IN MODELING TEST SPACE FOR SYSTEM BEHAVIOR - Systems and methods for modeling test space for verifying system behavior, using one or more auxiliary variables, are provided. The method comprises implementing a functional coverage model including: one or more attributes, wherein respective values for the attributes are assigned according to a test plan, and one or more constraints defining restrictions on value combinations assigned to the attributes, wherein the restrictions are Boolean expressions defining whether said value combinations are valid; determining a set of valid value combinations for the attributes that satisfy the restrictions to define the test space for verifying the system behavior; and determining relevant auxiliary variables and a corresponding function for said auxiliary variables to reduce the complexity associated with modeling the test space. | 12-20-2012 |
| 20130019125 | DETECTION AND CLASSIFICATION OF PROCESS FLAWS USING FUZZY LOGIC - A fuzzy logic controller for a distributed control system that monitors a large electrical machine in order to detect and identify faults. Variables to be monitored by the fuzzy logic controller include oil pressure, oil temperature, and other critical variables that are used under classical logic to trip the electrical machine offline. After the input and output membership functions are identified, and a rule set is defined, the fuzzy logic controller fuzzifies the monitored variables to the input membership functions, determines an antecedent truth value, and implicates the antecedent truth value onto the output membership function, establishing a fuzzy output set. Where multiple output fuzzy sets are to be combined, they are amalgamated. The output fuzzy set or amalgamated combined output fuzzy set is then converted to a crisp value. | 01-17-2013 |
| 20130055020 | Method for Automated Distributed Diagnostics for Networks - A method for distributed computations for fault-diagnosis in a system whose fault propagation model has deterministic couplings between faults and symptoms includes creating a ‘relation graph’ in which the nodes correspond to the potential faults, with two nodes connected by a ‘relational link’ if their corresponding faults have an observed symptom in common. Each relational link is assigned a weight equal to the sum, taken over the symptoms represented by the relational link, of the reciprocal of the number of distinct fault-pairs that produce each such symptom. The relation graph is then partitioned into several domains, while minimizing the number of cross-domain relational links, which correspond to cross-domain symptoms. In each domain, all the optimal local solutions to the domain's sub-problem are first determined, and then a combination is selected of the local solutions, one from each domain, that explains the maximum number of cross-domain symptoms, where the optimal solution is supplemented, if necessary, with additional faults to explain any remaining unexplained cross-domain symptoms, determining also a bound on the deviation from optimality of the global solution. | 02-28-2013 |
| 20130055021 | METHOD AND APPARATUS FOR MINIMIZING ERROR IN DYNAMIC AND STEADY-STATE PROCESSES FOR PREDICTION, CONTROL, AND OPTIMIZATION - A method for providing independent static and dynamic models in a prediction, control and optimization environment utilizes an independent static model ( | 02-28-2013 |
| 20130061092 | FAST DETECTION AND DIAGNOSIS OF SYSTEM OUTAGES - Methods and arrangements for detecting and diagnosing system outages. A system outage is ascertained and aberrant user activities are categorized, as possible contributors to the system outage, based on system impact. User activities and system impact are learned, and user activities and system impact are compared against predetermined rules. A system outage alert is generated, and a user activity responsible for the system outage is displayed. | 03-07-2013 |
| 20130103983 | BDD-BASED FUNCTIONAL COVERAGE ANALYSIS - Obtaining a functional coverage model of a System Under Test (SUT) defining all functional coverage tasks of the SUT, wherein the functional coverage model defining a test-space with respect to functional attributes; obtaining a set of covered functional coverage tasks; encoding a covered Binary Decision Diagram (BDD) to represent the set of covered functional coverage tasks within the test-space; and manipulating the covered BDD to identify one or more coverage holes, wherein a coverage hole defines a set of coverage tasks in the test-space, all having a same combination of values to a subset of the functional attributes, that are not covered by the set of covered functional coverage task. | 04-25-2013 |
| 20130117607 | MULTI-PARAMETER SELF LEARNING MACHINE APPLICATION MODEL - A method for identifying root cause failure in a multi-parameter self learning machine application model is presented. At least one multi-function sensor having the capability to measure at least one of a voltage and current of the machine application model is provided. The method includes measuring voltages and currents of a multi-phase load with the multi-function sensors in a passive manor and calculating at least one of a time-varying variable KW, PF, kVAr, or Z out of the measured voltages and currents. The method further provides calculating a first, second or third order derivative of the time-varying variable and classifying segments of at least one of the time-varying variables depending on a state. Then, a step of choosing at least one of the variables and learning their normal behavior is undertaken. Finally, normal behavior is compared to a pattern difference and a root-cause meaning to the pattern difference is identified. | 05-09-2013 |
| 20130185591 | METHODS, APPARATUS AND ARTICLES OF MANUFACTURE TO PERFORM ROOT CAUSE ANALYSIS FOR NETWORK EVENTS - Example methods, apparatus and articles of manufacture to perform root cause analysis for network events are disclosed. An example method includes retrieving a symptom event instance from a normalized set of data sources based on a symptom event definition; generating a set of diagnostic events from the normalized set of data sources which potentially cause the symptom event instance, the diagnostic events being determined based on dependency rules; and analyzing the set of diagnostic events to select a root cause event based on root cause rules. | 07-18-2013 |
| 20130198565 | DETECTION, DIAGNOSIS, AND MITIGATION OF SOFTWARE FAULTS - A computational geometry technique is utilized to detect, diagnose, and/or mitigate fault detection during the execution of a software application. Runtime measurements are collected and processed to generate a geometric enclosure that represents the normal, non-failing, operating space of the application being monitored. When collected runtime measurements are classified as being inside or on the perimeter of the geometric enclosure, the application is considered to be in a normal, non-failing, state. When collected runtime measurements are classified as being outside of the geometric enclosure, the application is considered to be in an anomalous, failing, state. In an example embodiment, the geometric enclosure is a convex hull generated in N-dimensional Euclidean space. Appropriate action (e.g., restart the software, turn off access to a network port) can be taken depending on where the measurement values lie in the space. | 08-01-2013 |
| 20130219215 | SOLVING CONSTRAINT SATISFACTION PROBLEMS HAVING LOOSELY INTERCONNECTED SUB-PROBLEMS - A method, apparatus and product. The method comprising automatically determining an abstract CSP based on a formally defined problem having interconnected sub-problems, wherein the abstract CSP corresponds to the problem, wherein the abstract CSP has a reduced complexity in comparison to a CSP representing the problem, wherein the abstract CSP captures the interconnection between the sub-problems and reduces the details of each sub-problem, wherein the abstract CSP comprises constraints over variables, wherein each variable having an associated domain; and repeatedly: (1) propagating constraints of the abstract CSP to reduce domains of the abstract CSP; (2) selecting a sub-problem to solve; (3) solving the sub-problem; and (4) updating the abstract CSP with values in accordance with the solution of the sub-problem. Whereby, a solution to the formally defined problem is determined based on the solutions to the sub-problems. | 08-22-2013 |
| 20130219216 | Hybrid Memory Failure Bitmap Classification - Aspects of the invention relate to techniques for classifying memory failure bitmaps using both rule-based classification and artificial neural network-based classification methods. The rule-based classification method employs classification rules comprising those for global failure patterns. The artificial neural network-based classification method classifies local failure patterns. One of the artificial neural network models is the Kohonen self-organizing map model. The input vector for a failure pattern may contain four elements: pattern aspect ratio, failing bit ratio, dominant failing column number and dominant failing row number. | 08-22-2013 |
| 20130290784 | MANAGEMENT APPARATUS AND MANAGEMENT METHOD - A management apparatus and a management method that enable parsing processing to be executed efficiently by means of a working memory of a fixed size are proposed. One or more predefined rules are divided into one or more rule segments that comprise a condition and a conclusion that each form part of the rule, and the rule segments obtained through the division are stored in the secondary storage, and when an event notification from the information processing device is received, one or more related rule segments are selected and, by linking the selected one or more rule segments in the memory as required, a rule parsing network is constructed that indicates relationships between rules in the memory, an inference is derived on the basis of the constructed rule parsing network, and rule segments that are not readily used in inference derivation are deleted from the memory. | 10-31-2013 |
| 20130332773 | GENERALIZED PATTERN RECOGNITION FOR FAULT DIAGNOSIS IN MACHINE CONDITION MONITORING - A generalized pattern recognition is used to identify faults in machine condition monitoring. Pattern clusters are identified in operating data. A classifier is trained using the pattern clusters in addition to annotated training data. The operating data is also used to cluster the signals in the operating data into signal clusters. Monitored data samples are then classified by evaluating confidence vectors that include substitutions of signals contained in the training data by signals in the same signal clusters as the signals contained in the training data. | 12-12-2013 |
| 20140006861 | PROBLEM INFERENCE FROM SUPPORT TICKETS | 01-02-2014 |
| 20140006862 | MIDDLEBOX RELIABILITY | 01-02-2014 |
| 20140068330 | PREDICTING SYMPTOMS OF RUN-TIME PROBLEMS BASED ON ANALYSIS OF EXPERT DECISION MAKING - Systems, methods, and non-transitory computer-readable storage media for receiving historical data describing behavior of human subject-matter experts, wherein the historical data links customer problems with solutions, receiving a plurality of human-generated algorithms describing patterns for linking customer problems with solutions based on problem-specific diagnostic data, comparing each algorithm of the plurality of algorithms with the historical data to determine respective predictive scores for linking a customer problem type with a particular solution, and ranking at least part of the plurality of algorithms based on the respective similarity scores. | 03-06-2014 |
| 20140082417 | SYSTEMS AND METHODS FOR USING A CORRECTIVE ACTION AS DIAGNOSTIC EVIDENCE - Methods, systems and computing devices are provided for using a completed corrective action as evidence of a fault. The methods, systems and computing devices receive equipment status evidence and determine an equipment fault based on the equipment status evidence. The methods, systems and computing devices also create and rank a list of potential failure modes based at least in part on the determined equipment fault, recommend a corrective action to correct the equipment fault based at least in part on the ranking of the potential failure modes and receiving additional equipment status evidence indicating that the recommended corrective action failed to correct the equipment fault. The methods, systems and computing devices then associate a detection probability and a false negative rate with the failed corrective action to create additional status evidence, and re-rank the list of potential failure modes for subsequent performance based on the additional status evidence. | 03-20-2014 |
| 20140136896 | DIAGNOSING DISTRIBUTED APPLICATIONS USING APPLICATION LOGS AND REQUEST PROCESSING PATHS - A method for monitoring a distributed application for errors includes constructing a transaction path for each request received by the distributed application, detecting a writing action to a log of the distributed application, and annotating the transaction path in accordance with the writing action to produce an annotated transaction path. In another embodiment, a method for building a knowledge base for use in diagnosing an error occurring in a distributed application includes executing the distributed application on a replica of a production server that supports the distributed application, constructing a transaction path for a request received by the distributed application, wherein the transaction path traverses the replica, injecting a fault into the transaction path, detecting a writing action to a log of the distributed application, wherein the writing action is a response to the fault, and storing an association between the fault and the writing action. | 05-15-2014 |
| 20140181585 | REAL USAGE MODEL FOR SOLID-STATE DRIVE - An embodiment is a technique to generate failure mode information for solid-state drive (SSD) in real environment. An environmental acquisition module acquires environmental information from an environmental sensor. A learning and update module generates an environmental profile based on the acquired environmental information. A failure acquisition module associates failure information from an SSD controller that controls an SSD with the environmental profile. An operation analyzer analyzes the associated failure information using pre-determined information provided by a database to generate failure mode information. A decision module decides if the failure mode information is valid. | 06-26-2014 |
| 20140201571 | INTELLIGENT CONDITION MONITORING AND FAULT DIAGNOSTIC SYSTEM FOR PREVENTATIVE MAINTENANCE - A system for condition monitoring and fault diagnosis includes a data collection function that acquires time histories of selected variables for one or more of the components, a pre-processing function that calculates specified characteristics of the time histories, an analysis function for evaluating the characteristics to produce one or more hypotheses of a condition of the one or more components, and a reasoning function for determining the condition of the one or more components from the one or more hypotheses. | 07-17-2014 |
| 20140223234 | SYSTEM AND METHOD FOR ANALYZING A QC STRATEGY FOR RELEASING RESULTS - A method analyzes a quality control strategy. A quality control rule can define quality control events and specifying a control limit for determining whether a quality control event passes or fails. The quality control rule and a number of patient samples tested between quality control events can be received. A first expected number of correctible errors when a quality control event fails can be computed based on the quality control rule and the number of patient samples tested between quality control events. A second expected number of final errors that are not correctible when a quality control event fails can be computed based on the quality control rule and the number of patient samples tested between quality control events. An assessment of the quality control rule can include the first expected number of correctible errors and the second expected number of final errors as separate values. | 08-07-2014 |
| 20140281713 | MULTI-STAGE FAILURE ANALYSIS AND PREDICTION - A hierarchical multi-stage model of asset failure risk for complex heterogeneously distributed physical assets is built. The hierarchical multi-stage model considers heterogeneity of failure patterns for the assets. At least one data stream is analyzed to determine whether the hierarchical multi-stage model needs to be updated due to a change in the failure patterns. If the analysis indicates that the hierarchical multi-stage model needs to be updated, the hierarchical multi-stage model is dynamically updated to obtain an updated hierarchical multi-stage model. | 09-18-2014 |
| 20140325276 | APPARATUS, METHOD AND STORAGE MEDIUM FOR FAULT CAUSE EXTRACTION UTILIZING PERFORMANCE VALUES - A fault cause extraction apparatus including a storage unit which stores a model including one or more correlation functions between pieces of performance information acquired from a plurality of elements and a correlation-destruction-propagation detecting unit which calculates a degree of influence for each of the elements based on correlation destruction information. The correlation destruction information is calculated based on whether pieces of performance information newly acquired from the elements satisfy a relationship represented by the correlation functions. | 10-30-2014 |
| 20140351642 | SYSTEM AND METHODS FOR AUTOMATED PLANT ASSET FAILURE DETECTION - A system for performing failure signature recognition training for at least one unit of equipment. The system includes a memory and a processor coupled to the memory. The processor is configured by computer code to receive sensor data relating to the unit of equipment and to receive failure information relating to equipment failures. The processor is further configured to analyze the sensor data in view of the failure information in order to develop at least one learning agent for performing failure signature recognition with respect to the at least one unit of equipment. | 11-27-2014 |
| 20150019912 | ERROR PREDICTION WITH PARTIAL FEEDBACK - A method for performing data processing through a pipeline of components includes receiving a set of training observations, each including partial user feedback relating to error in data output by the pipeline for respective input data. Some pipeline components commit errors for at least some of the input data, contributing to an error in the respective output data. A prediction model models a probability of a pipeline component committing an error, given input data. Model parameters are learned using the training observations. For a new observation which includes input data and, optionally, partial user feedback indicating that an error has occurred in processing the new input data, without specifying which pipeline component(s) contributed to the observed error in the output data, a prediction is made as to which of the pipeline components contributed to the error in the output (if any). | 01-15-2015 |
| 20150135012 | NETWORK NODE FAILURE PREDICTIVE SYSTEM - In an example, network node failures may be predicted by extracting performance metrics for the network nodes from a plurality of data sources. A fail condition may be defined for the network nodes and input variables related to the fail condition for the network nodes may then be derived from the extracted performance metrics. A plurality of models may then be trained to predict the fail condition for the network nodes using a training set from the extracted performance metrics with at least one of the identified input variables. Each of the plurality of trained models may be validated using a validation set from the extracted performance metrics and may be rated according to predefined criteria. As a result, a highest rated model of the validated models may be selected to predict the fail condition for the network nodes. | 05-14-2015 |
| 20160055044 | FAULT ANALYSIS METHOD, FAULT ANALYSIS SYSTEM, AND STORAGE MEDIUM | 02-25-2016 |
| 20160062815 | DETECTION OF ANOMALIES IN ERROR SIGNALS OF CLOUD BASED SERVICE - Anomalies detection in error signals of a cloud based service is provided. An application such as an analysis application identifies a machine learning algorithm that matches error signals of components of a cloud based service. A periodic pattern from the error signals is removed with the machine learning algorithm to filter the periodic pattern from an error count in the error signals. The error signals are processed with the machine learning algorithm to detect one or more anomalies with the components. The machine learning algorithm is updated while processing new data to detect new patterns. | 03-03-2016 |
| 20160124823 | LOG ANALYTICS FOR PROBLEM DIAGNOSIS - In a set of problem log entries from a computing system, a subset of the set of problem log entries are identified, which pertain to a failed request. The subset is compared to a reference model which defines log entries per request type under a healthy state of the computing system, to identify a portion of the subset of problem log entries which deviate from corresponding log entries in the reference model. In the portion of the subset, at least one high-value log entry is identified. The at least one high-value log entry is output. | 05-05-2016 |
| 20160139977 | System and method for abnormality detection - A system and method for use in data analysis are provided. The system comprises a data processing utility configured to receive and process input data, comprising: plurality of neural network modules capable for operating in a training mode and in a data processing mode in accordance with the training; a network training utility configured for operating the neural network modules in the training mode utilizing selected set of training data pieces for sequentially training of the neural network modules in a cascade order to reduce an error value with respect to the selected set of the training data pieces for each successive neural network module in the cascade; and an abnormality detection utility configured for sequentially operating said neural network modules for processing input data, and classifying said input data as abnormal upon identifying that all the neural network modules provide error values being above corresponding abnormality detection thresholds. | 05-19-2016 |
| 20160188433 | TESTING AND MITIGATION FRAMEWORK FOR NETWORKED DEVICES - The present disclosure generally relates to the automated testing of a system that includes software or hardware components. In some embodiments, a testing framework generates a set of test cases for a system under test using a grammar. Each test case may perform an action, such as provide an input to the system under test, and result in an output from the system under test. The inputs and outputs are then compared to the expected results to determine whether the system under test is performing correctly. The data can then be interpreted in the grammar system or used as input to a fault isolation engine to determine anomalies in the system under test. Based on identified faults, one or more mitigation techniques may be implemented in an automated fashion. | 06-30-2016 |
| 20170235626 | Anomaly Fusion on Temporal Casualty Graphs | 08-17-2017 |
| 20220140940 | AI-Based Error Detection and Correction in 5G/6G Messaging - Artificial intelligence procedures are disclosed for localizing faults in corrupted messages in 5G and 6G, and for correcting those faults based on measured parameters such as backgrounds and message signals. Message faults can be caused by noise or interference from a variety of sources with a wide range of properties. An AI model with multiple adjustable variables may be “trained” using a large number of message events, including faulted messages, to determine which message elements are likely faulted, based on input parameters such as modulation quality, SNR, and other signal properties. The receiving entity can then attempt a grid search to correct the faulted message elements, or request a retransmission. For field use by base stations and user devices, an algorithm may be developed based on the AI model, and configured to predict which message elements are likely faulted. By detecting and correcting message faults, networks may increase reliability and reduce latency while avoiding most retransmission costs and delays, according to some embodiments. | 05-05-2022 |
