Abstract: A device may receive software data identifying current logs and events associated with software products utilized by an entity and may process the software data, with a machine learning model, to generate error severity scores for the software products. The machine learning model may be trained based on historical software data identifying events and logs associated with software products utilized by the entity and based on a combination of historical health scores, historical sentiment scores, and historical dissimilarity scores for the software products. The device may process the error severity scores, with a prioritization model, to generate prioritized error scores and may process the error severity scores and the prioritized error scores, with a root cause analysis model, to generate root cause data identifying root causes associated with the error severity scores. The device may perform one or more actions based on the root cause data.

Abstract: An example method includes receiving incident data for historical incidents of downtime or interrupted service. The incident data includes identification information about one or more first computing applications, devices, or services affected by the downtime or the interrupted service. The incident data further includes timing information relating to the historical incidents and version history information of the one or more first computing applications, devices, or services. The method further includes receiving root cause data indicating a cause of the historical incidents and receiving action data indicating a corrective or preventative action taken or to be taken in response to each of the historical incidents. The method further includes training a machine learning algorithm using the incident, root cause, and action data to create a trained model configured to determine a root cause and a new corrective or preventative action for a new incident.

Abstract: Methods and systems for parallelizing processes through the use of predicted data are described herein. A requesting system may send processing requests to a processing system. The processing system may need to have a third-party validation system validate the processing requests before proceeding. The processing system may detect errors and generate modified data that is predicted to resolve the errors in obtained processing requests. The modified data may be sent to the validation system in place of the original data that contained errors. While waiting for validation results from the validation system, the modified data may also be sent to the requesting system to confirm that it is correct. By sending the modified data to both the validation system and the requesting system for approval, increased efficiency and parallelization may be achieved.

Abstract: An event analysis system is provided. During operation, the system can determine an event description associated with the switch from an event log of the switch. The event description can correspond to an entry in a table in a switch configuration database of the switch. A respective database in the switch can be a relational database. The system can then obtain an event log segment, which is a portion of the event log, comprising the event description based on a range of entries. Subsequently, the system can apply a pattern recognition technique on the event log segment based on the entry in the switch configuration database to determine one or more patterns corresponding to an event associated with the event description. The switch can then apply a machine learning technique using the one or more patterns to determine a recovery action for mitigating the event.

Abstract: A failure recommendation system for a command line interface (CLI) uses machine learning to predict the most likely command to correct an unsuccessful or failed attempt to perform an intended operation using the CLI. The failure recommendation system is based on a conditional probability model trained on failure-success pairs of commands from CLI telemetry data to learn the most likely command to remediate a failure. The conditional probability model predicts the most likely command based on a failure type and the failed command. The failure type is identified through a failure type classifier and is used to select the most likely command to remediate a failure from the different events that may lead to a failure.

Abstract: According to an aspect, a (recommendation) system constructs a knowledge graph based on problem descriptors and remediation actions contained in multiple incident reports previously received from a performance management (PM) system. Each problem descriptor and remediation action in an incident report are represented as corresponding start node and end node in the knowledge graph, with a set of qualifier entities in the incident report represented as causal links between the start node and the end node. Upon receiving an incident report related to an incident identified by the PM system, the system extracts a problem descriptor and a set of qualifier entities. The system traverses the knowledge graph starting from a start node corresponding to the extracted problem descriptor using the set of qualifier entities to determine end nodes representing a set of remediation actions. The system provides the set of remediation actions as recommendations for resolving the incident.

Abstract: A system, computer program product, and method are presented for providing replacement data for data in a time series data stream that has issues indicative of errors, where the data issues and the replacement data are related to one or more KPIs. The method includes determining one or more predicted replacement values for potentially erroneous data instances in the time series data stream. The method further includes resolving the potentially erroneous data instances with one predicted replacement value of the one or more predicted replacement values in the time series data stream.

Abstract: Systems and methods for are provided for predicting impending failure of a database and preemptively initiating mitigating failover actions, for example by shedding connections or redirecting connection requests to an alternate database that can fulfill resources being requested. In an example embodiment, to detect a slow or unstable database, connection wait times are monitored over a rolling window of time intervals, a quantity of intervals in which at least one excessive wait time event occurred are counted during the time window, and if the quantity exceeds a threshold, the database is deemed unavailable, thereby triggering connection adjustments.

Abstract: Techniques for predictive system remediation are disclosed. Based on attributes associated with applications of one or more system-selected remedial actions to one or more problematic system behaviors in a system (e.g., a database system), the system determines a predicted effectiveness of one or more future applications of a remedial action to a particular problematic system behavior, as of one or more future times. The system determines that the predicted effectiveness of the one or more future applications of the remedial action is positive but does not satisfy a performance criterion. Responsive to determining that the predicted effectiveness is positive but does not satisfy the performance criterion, the system generates a notification corresponding to the predicted effectiveness not satisfying the performance criterion.

Abstract: Example embodiments relate to low-overhead, bidirectional error checking for a serial peripheral interface. An example device includes an integrated circuit. The device also includes a serial peripheral interface (SPI) with a Master In Slave Out (MISO) channel and a Master Out Slave In (MOSI) channel. The MOSI channel is configured to receive a write address, payload data, and a forward error-checking code usable to identify data corruption within the write address or the payload data. The integrated circuit is configured to calculate and provide a reverse error-checking code usable to identify data corruption within the write address or the payload data. Additionally, the integrated circuit is configured to compare the forward error-checking code to the reverse error-checking code. Further, the integrated circuit is configured to write, to the write address if the forward error-checking code matches the reverse error-checking code, the payload data.

Abstract: Methods, systems, and devices for channel modulation for a memory device are described. A system may include a memory device and a host device coupled with the memory device. The system may be configured to communicate a first signal modulated using a first modulation scheme and communicate a second signal that is based on the first signal and that is modulated using a second modulation scheme. The first modulation scheme may include a first quantity of voltage levels that span a first range of voltages, and the second modulation scheme may include a second quantity of voltage levels that span a second range of voltages different than (e.g., smaller than) the first range of voltages. The first signal may include write data carried over a data channel, and the second signal may include error detection information based on the write data that is carried over an error detection channel.

Abstract: A request is received to program host data to a memory device of a memory sub-system. The host data is associated with a logical address. A redundancy factor that corresponds to the logical address associated with the host data is obtained. A first physical address associated with a first set of cells of the memory device and a second physical address associated with a second set of cells of the memory device are determined based on the redundancy factor. The first set of memory cells is to store the host data and the second set of memory cells is to store redundancy metadata associated with the host data. The host data is programmed to the first set of memory cells. The redundancy metadata associated with the host data is programmed to the second set of memory cells.

Abstract: Low-density parity-check (LDPC) coding based on memory cell voltage distribution (CVD) in data storage devices. In one embodiment, a memory controller includes a memory interface configured to interface with a non-volatile memory; and a controller. The controller is configured to receive a plurality of data pages to be stored in the non-volatile memory, and transform the plurality of data pages into a plurality of transformed data pages. The controller is further configured to determine a plurality of parity bits based on the plurality of transformed data pages, and store the plurality of data pages and the plurality of parity bits in the non-volatile memory.

Abstract: A semiconductor memory device includes a memory cell array, an on-die error correction code (ECC) engine, and a control logic circuit. The on-die ECC engine, based on an ECC, in a write operation, performs an ECC encoding on main data to generate first parity data, selectively replaces a portion of the first parity data with a poison flag to generate second parity data based on a poison mode signal, provides the main data to a normal cell region in a target page of the memory cell array, and provides the first parity data to a parity cell region in the target page or provides the poison flag and the second parity data to the parity cell region. The control logic circuit controls the on-die ECC engine and generates the poison mode signal, based on a command and an address from a memory controller.

Abstract: A processing system of a storage network operates by: receiving a write request to store a data object; selecting a selected memory type of a plurality of memory types to store the data object, based on object parameters associated with the data object; selecting a selected memory to store the data object, the selected memory having the selected memory type of the plurality of memory types; and facilitating storage of the data object in the selected memory having the selected memory type of the plurality of memory types, wherein the data object is dispersed error encoded and stored as a plurality of encoded data slices.

Abstract: A method for resumeable snapshot deletion is provided. A method for deletion of nodes maintained in an ordered data structure for a first snapshot includes processing the nodes maintained in the ordered data structure according to a defined order, setting a node path cursor with a pointer to a node and an indication of the deletion of the node; storing the node path cursor in a persistent storage; and during processing of the nodes: detecting a failure; after the failure, checking the pointer of the node path cursor; and resuming processing of the nodes starting from the first node indicated by the pointer.

Abstract: An interface software layer is interposed between at least one application and a plurality of coprocessors. A data and command stream issued by the application(s) to an API of an intended one of the coprocessors is intercepted by the layer, which also acquires and stores the execution state information for the intended coprocessor at a coprocessor synchronization boundary. At least a portion of the intercepted data and command stream data is stored in a replay log associated with the intended coprocessor. The replay log associated with the intended coprocessor is then read out, along with the stored execution state information, and is submitted to and serviced by at least one different one of the coprocessors other than the intended coprocessor.

Abstract: Embodiments provide systems, methods, and computer program products for enabling user authorization to perform a file level recovery from an image level backup of a virtual machine without the need for access control by an administrator. Specifically, embodiments enable an access control mechanism for controlling access to stored image level backups of a virtual machine. In an embodiment, the virtual machine includes a backup application user interface that can be used to send a restoration request to a backup server. The restoration request can include a machine identifier and a user identifier of the user logged onto the virtual machine. The backup server includes a backup application that determines whether or not the machine identifier contained in the restoration request can be matched to a machine identifier of a virtual machine present in one of the virtual machine backups stored on the backup server.

Abstract: Methods, non-transitory computer readable media, and devices that more effectively manage snapshots by creating a namespace including files described by stored file recipe objects and each comprising fragments, directories described by metadata in the file recipe objects and each comprising one or more of the files, and snapshots described by stored snapshot request objects. Content of one of the directories are identified based on an identification of corresponding ones of the file recipe objects that existed within the namespace at a specified time. At least one of the files, included in the identified content and existing within the namespace at the specified time, is accessed in response to one or more received requests. A garbage collection operation is periodically performed to delete the recipe objects that are marked for deletion by tombstone objects and are unreferenced by any of the snapshots as determined based on the snapshot request objects.

Abstract: A system and method converts a list that may be used for tracking, into an input that can be used by backup and recovery software to avoid backing up certain virtual machines in a multiple cluster backup configuration, network coupled, environment.

Abstract: Changes made to a database table are accumulated, in durable storage, and snapshots of partitions of the table are obtained. For successive snapshots of a partition, the system accesses a previous snapshot, applies changes from the accumulated changes, and stores the updated snapshot to a durable data store. The accumulated changes and the successive partition snapshots are made available to restore the database to any point in time across a continuum between successive snapshots. Although each partition of the table may have a backup snapshot that was generated at a time different from when other partition snapshots were generated, changes from respective change logs may be selectively log-applied to distinct partitions of a table to generate an on-demand backup of the entire table at common point-in-time across partitions. Point-in-time restores of a table may rely upon a similar process to coalesce partition snapshots that are not aligned in time.

Abstract: A cross-platform data migration method and a cross-platform data migration system include generating backup data of a virtual machine in a host system, identifying a first file format associated with backup data, converting the first file format associated with backup data into a platform-neutral file format associated with backup data, and storing the backup data in the platform-neutral file format in a first storage platform.

Abstract: A distributed system responds to a request to enable restoration capability for a database instance by beginning a process for monitoring configuration changes made to a first operating environment of a first database instance. The system identifies a configuration change on which the database instance is dependent, and stores a record of the configuration change. The record is provided to a second operating environment. The second operating environment is configured, based on the record of the configuration change, to have configuration settings corresponding to the first operating environment as of the restoration point in time. The database instance is restored to the second operating environment.

Abstract: A processing system may apply a binary classifier to detect whether a first data pattern of a first data source associated with a communication network performance indicator is consistent with prior data patterns of the first data source that are labeled as correct data patterns, determine, via the binary classifier, that the first data pattern is not consistent, apply a clustering model to a first input data set comprising the first data pattern and invalid data patterns of the first data source to obtain a first plurality of clusters, verify that the first data pattern is an invalid data pattern when the first plurality of clusters is the same as a second plurality of clusters generated by applying the clustering model to a second input data set comprising the invalid data patterns, and replace the first data source with a replacement data source as an active data source in response.

Abstract: A method comprises executing a testing operation on a plurality of redundant components of an edge device. In one example, based, at least in part, on the testing operation, at least one redundant component of the plurality of redundant components is identified as having an operational issue, and the at least one redundant component is deactivated in response to the identifying. One or more remaining redundant components of the plurality of redundant components are utilized in one or more operations following the testing operation.

Abstract: A storage system has a plurality of storage nodes having equal non-volatile storage capacity that is subdivided into equal size cells. Host application data that is stored in the cells is protected using RAID or EC protection groups each having members stored in ones of the cells and distributed across the storage nodes such that no more than one member of any single protection group is stored by any one of the storage nodes. Spare cells are maintained for rebuilding protection group members of a failed one of the storage nodes on remaining non-failed storage nodes so full data access is possible before replacement or repair of the failed storage node.

Abstract: A method and apparatus for performing a power stress test on an FPGA acceleration card and a computer-readable storage medium. The method includes: dividing, according to a partial reconfiguration method, a hardware resource of an FPGA acceleration card into a static region serving as a hardware logic implementation region for performing a normal function test, and a dynamic PR region including a blank mode occupying no hardware resource and a power test mode for performing a power stress test, and burning FPGA firmware having a partial reconfiguration function to a flash memory; upon receiving a request for power stress test, configuring an operation mode of the dynamic PR region to be the power test mode, loading, to the dynamic PR region, a dynamic PR configuration file burned in the flash memory; and calling a power stress test module to execute the power stress test in the dynamic PR region.

Abstract: A memory test method, a memory test apparatus, a device and a storage medium are provided. The memory test method includes: obtaining a central processing unit (CPU) accessible space of a memory to-be-tested; obtaining a graphics processing unit (GPU) accessible space of the memory to-be-tested; and driving a CPU to run a test program based on the accessible space of the CPU, to access the memory to-be-tested through a bus of memory to-be-tested, when the CPU runs the test program, the CPU controls a GPU to access the memory to-be-tested based on the accessible space of the GPU through the bus of memory to-be-tested.

Abstract: A method and apparatus for sending a debugging instruction, an electronic device and a computer readable storage medium are provided. The method may include: after acquiring a debugging instruction sent by an operating terminal, determining a debugged terminal and a first edge communication node corresponding to the debugged terminal according to the debugging instruction, and determining a debugging communication link between the first edge communication node and the debugged terminal, the first edge communication node being determined based on first edge communication node information sent by the debugged terminal, and the first edge communication node information being determined and obtained based on an edge node computing application locally installed on the debugged terminal, and sending an debugging operation included in the debugging instruction to the debugged terminal through the debugging communication link.

Abstract: A computer-implemented method for cloud-based testing of a payment network may include receiving a test configuration for testing a payment processing network, configuring a simulated worker generator for generating a plurality of simulated workers according to the received test configuration, reading commands to be executed by each simulated worker among the plurality of simulated workers from a command bank according to the received test configuration, configuring the plurality of simulated workers according to the commands and the received test configuration, starting a swarm test of the payment processing network by the plurality of simulated workers, reading results of the swarm test from the plurality of simulated workers, and saving the results to storage.

Abstract: Test packets may be received at a design under test (DUT) from an automated test equipment (ATE) over a serializer/deserializer (SERDES) connection between the ATE and the DUT. The test packets may include test pattern data to test the DUT. The test pattern data may be applied to the DUT using a set of scan chains and test response data corresponding to the test pattern data may be obtained. The test response data may be received by a circuit in the DUT at irregular time intervals. Response packets may be sent to the ATE by the circuit in the DUT at regular time intervals, where the response packets may include a portion of the test response data (which may be encoded using an encoding technique), and where the response packets may be sent to ATE over the SERDES connection.

Abstract: A system and method for agentless discovery and inspection of applications and services in a compute environment includes establishing a connection with a first workload in a first compute environment. The first compute environment includes a plurality of workloads. The system causes installation of a collector on the first workload, wherein the collector, when executed, is configured to collect data from the first workload. Collected data is received from the collector, and the collector is configured to remove the executable code of the collector upon completing data collection. Access is provided to the collected data for an asset monitoring system, wherein the asset monitoring system is configured to discover from the collected data at least an application executed on the first workload.

Abstract: Various embodiments of the present disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for multi-node system monitoring using one or more distributed ledgers, wherein a ledger entry request received from a miner node computing entity is validated based at least in part on executing a hierarchical validation workflow that comprises an ordered sequence of L validation iterations, wherein each of one or more ith non-initial validation iterations is performed based at least in part on an association of an (i?1)th validation iteration with a non-affirmative validation determination.

Abstract: Examples described herein relate to a system including a first management system having a primary memory including a free memory, a used memory, and a loosely reserved memory, where the loosely reserved memory comprises cache memory having a reclaimable memory; and a processing resource coupled to the primary memory. The processing resource may monitor an amount of the used memory and an amount of an available memory during runtime of the first management system. Further, the processing resource may enable a synchronized reboot of the first management system if the amount of the used memory is greater than a memory exhaustion first threshold or the amount of the available memory is less than a memory exhaustion second threshold, wherein the memory exhaustion first threshold and the memory exhaustion second threshold are determined based on usage of the reclaimable memory and a number of major page faults.

Abstract: An approach is provided for implementing memory profiling aggregation. A hardware aggregator provides memory profiling aggregation by controlling the execution of a plurality of hardware profilers that monitor memory performance in a system. For each hardware profiler of the plurality of hardware profilers, a hardware counter value is compared to a threshold value. When a threshold value is satisfied, execution of a respective hardware profiler of the plurality of hardware profilers is initiated to monitor memory performance. Multiple hardware profilers of the plurality of hardware profilers may execute concurrently and each generate a result counter value. The result counter values generated by each hardware profiler of the plurality of hardware profilers are aggregated to generate an aggregate result counter value. The aggregate result counter value is stored in memory that is accessible by a software processes for use in optimizing memory-management policy decisions.

Abstract: Methods, computer program products, and systems are presented. The methods include, for instance: creating a log data specific lexicon based on log data samples, each word in the log data specific lexicon corresponding to a weighted sentiment score with a binary polarity. A log message is obtained, and a sentiment value of the log message is assigned based on respective weighted sentiment scores of words appearing in the log message. The log message is classified for a class indicating an issue the log message addresses. An alert type for the log message is determined based on the sentiment value, the class, and a priority of the log message, and a system alert including a set of key performance indicators according to the alert type is produced to a user.

Abstract: A method for generating an output for performance impact assessment of a change includes determining changes associated with a first managed computer system where corresponding change records includes a respective change time-stamp, determining performance values for a performance metric for predetermined times and associating respective performance time-stamps, selecting one of the changes wherein the selected change has a change time-stamp, identifying first performance values with performance time-stamps that are prior in time to change time-stamp and associating them with a before-change category, identifying second performance values with performance time-stamps that are later in time relative to the change time-stamp and associating them with an after-change category, and generating an output with the first and second performance values (in a tabular or common timeline format) with the first performance values being distinguishable from the second performance values to thereby allow the user to determin

Abstract: A system is described that obtains first performance data collected during execution of a first application at a first group of computing devices, determines, based on the first performance data, at least one metric for quantifying performance of the first application, and compares the at least one metric to a corresponding benchmark derived from second performance data collected during execution of one or more second applications at a second group of computing devices. Each of the one or more second applications being different than the first application. The system determines whether the at least one metric is within a threshold amount of the corresponding benchmark, and further determines, determines, based at least in part on the at least one metric is not within the threshold amount of the corresponding benchmark, a fix to the first application and outputs, for presentation at a developer device, an indication of the fix.

Abstract: Systems, methods and media are directed to automatically generating a recommendation. Data describing a configuration of a production infrastructure is received, the production infrastructure running the system operating in the production environment. One or more metrics data values indicative of a performance of the system operating in the production environment is retrieved. Expected performance values of the system are received. An augmented decisioning engine compares the metrics data values with the expected performance values. The augmented decisioning engine is trained to provide a recommended configuration of the production infrastructure. Based on the comparing, the augmented decisioning engine is trained to improve subsequent recommendations of configuration of the production infrastructure through a feedback process.

Abstract: A method of aggregating metrics associated with a user interaction during a real user session comprises identifying a span comprising a tag associated with a workflow from ingested spans associated with the real user session, where the workflow comprises spans generated in response to the user interaction. The method also comprises identifying other spans associated with the workflow from the ingested spans. The method further comprises grouping the other spans associated with the workflow with the tagged span and aggregating metrics for the workflow over a duration of time.

Abstract: In one embodiment, a device obtains page load information corresponding to a loaded web application. The device detects, based on the page load information, an anomalous feature of the loaded web application. The device identifies a type of the anomalous feature based on a number of resource anomalies within the loaded web application, wherein the type of the anomalous feature is selected from a group consisting of: a page anomaly; a resource anomaly; and a domain anomaly. The device performs one or more mitigation actions according to the type of the anomalous feature.

Abstract: A semiconductor device (100) includes: first storage means (110) storing, in advance, a plurality of pieces of execution order inspection information (111˜11n) used for inspection of an execution order of a plurality of code blocks in a predetermined program, second storage means (120), which is a cache for the first storage means, and prediction means (130) for predicting a storage area of the execution order inspection information based on prediction auxiliary information in a first code block of the plurality of code blocks and a control flow graph of the program, the storage area being a prefetch target to be prefetched from the first storage means to the second storage means.

Abstract: Techniques to facilitate provision of different user experiences to different groups of users of a mobile application are disclosed herein. In at least one implementation, a manifest provided by an application development and optimization platform is received that defines a plurality of user segments and a plurality of feature variants individually associated with the plurality of user segments. The manifest is processed to determine a segment of the plurality of user segments associated with a user of the mobile application along with a feature variant of the plurality of feature variants associated with the segment of the user. Execution of the mobile application is monitored for an occurrence of an event that triggers a default feature of the mobile application, and responsive to the event, the default feature is replaced with the feature variant associated with the segment of the user.

Abstract: A method, an apparatus, and a system are for evaluating code design quality. The method for evaluating code design quality includes: determining, based upon a result from static scanning of code, a probability of the presence of an error-prone pattern in the code; inputting the probability into an artificial neural network, and determining, based upon the artificial neural network, a prediction result for whether the code violates a preset design rule and for a quantized degree to which the design rule is violated; and based upon the prediction result, evaluating the design quality of the code. The present method is able to improve the accuracy of code design quality evaluation. By detecting a presence of an error-prone pattern in the code, whether or not a key design rule has been violated in a design process and a quantized degree to which the key design rule is violated are predicted.

Abstract: Disclosed is a window kernel fuzzing technique utilizing type information obtained through binary static analysis. The method of fuzzing a kernel of a computer operating system performed by a fuzzing system may include the steps of: automatically inferring type information of a system call using a library file provided by the computer operating system; and performing system call fuzzing on the basis of the type information of the system call obtained through the inference.

Abstract: Methods and systems provide for a notebook interactive programming environment, having out-of-order code-cell execution, which communicates potential cell execution outcomes. If an event handler receives an event (e.g., open notebook, code change, code execution, etc.) for a cell, without a request for a specific type of analysis (e.g., data-leakage, stale-state), intra-cell analysis is executed based-on the cell's abstract semantics, and an abstract state and pre-summaries are output that indicate the cell's propagation dependency (unbounded variables). If an analysis is associated with the event, starting with the stored abstract state, inter-cell analysis is recursively executed on successor cells having propagation dependencies, until a terminating criteria is reached. Outcomes (e.g., affected cell, line number, bug type, metrics, etc.) are sent via the notebook user-interface to warn users, ahead of concrete code execution, of hypothetical unsafe or safe actions in executing the notebook's code cells.

Abstract: Disclosed here is a system to enable interaction between a user with a disability and a computer program. The system can obtain a representation of a user interface to present to a user. The system can determine an element associated with the user interface, where the element is configured to provide information to the user, however, the user interface presentation of the element at least partially fails to provide the information to the user. Based on the element, the system can determine an appropriate test to perform. The appropriate test indicates at least two of: a test to perform with a keyboard, a gesture test to perform with a mobile screen reader, and an audio test to perform with a screen reader. The system can generate an indication of the appropriate test. The system can provide the indication of the appropriate test prior to releasing the user interface to the user.

Abstract: A system and method are disclosed for quality assurance and performance testing of supply chain applications and systems. Embodiments include providing a user interface for receiving a test case file that describes one or more actions to be tested and a properties file that maps one or more elements to one or more values, translating a received test case file and a corresponding properties file into a test case, and executing the test case by identifying the one or more actions identified in the test case and automatically invoking one or more testing components configured to execute a test using the one or more actions, wherein at least one of the one or more testing components is configured execute performance testing, and at least one of the one or more testing components is configured to execute regression testing.

Abstract: A test execution and maintenance system may include an application learner configured to develop knowledge of operations of an application based on one or more learning test. The test execution and maintenance system then may include a test execution and repair manager configured to execute a functional test of the application, detect a failure of the functional test, and repair the functional test based on the knowledge of operations of the application. Responsive to detecting the failure of the functional test, the application learner may optionally perform a re-learning process and update the previously acquired knowledge of operations of the application.

Abstract: A method and system for detecting performance regression in a software application is disclosed. The software application comprises a feature flag having at least two states, wherein in a first state a first version of a feature is provided and in a second state a second version of the feature is provided when the software application is executed. The feature flag is further wrapped in a timer for recording the time taken for the corresponding first and second versions of the feature to be provided.