Abstract: Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for testing. The method includes: obtaining code modification information, program error information, and test case information. The method further includes: selecting a first test case set associated with code modification records from the test case information according to the program error information. The method further includes: sorting multiple test cases in the first test case set to generate a test strategy for the code modification records. Embodiments of the present disclosure may select the best test case for current code fix to meet different test requirements and reduce the test time.

Abstract: In some implementations, there is provided a method that includes monitoring, by an application uptime system, whether execution of an application is successful without causing an incident; in response to the execution of the application being unsuccessful and causing the incident, the method further comprising: collecting one or more end user incident reports including an incident identifier, a start time of the incident, and a stop time of the incident, collecting one or more development system incident reports linked to the one or more end user incident reports, determining at least one end user metric for the application, generating one or more user interface views based on the at least one end user metric for the application, and causing to be presented the one or more user interface views. Related systems, methods, and articles of manufacture are also disclosed.

Abstract: The invention relates to a system and method for managing the data streams for unified governance of a plurality of intensive computing solutions (70) accessible to a user client (2) from an aggregated interface (10), said intensive computing solutions including at least two solutions selected among: a high performance computing server (71), a server dedicated to supervised or unsupervised learning (72) and a server dedicated to quantum computing (73); said method being implemented at least partly by said computer system including: at least one database (25a) configured to store execution data for intensive computing operations; said method including the steps of storing (300) execution data for the intensive computing solutions (70) and transmitting (400) execution data for the intensive computing solutions to the aggregated interface (10).

Abstract: A hybrid cloud package build architecture can be provided for a computer system. For instance, a trigger can be determined for fetching an external package component for integration with a local package component. Based on the trigger, a request can be transmitted to an external package repository to obtain the external package component. The external package component can be received responsive to the request. The external package component can be cached for integration with the local package component.

Abstract: Aspects of the present disclosure relate generally to software development environments and, more particularly, to systems, computer program products, and methods of automating software development, security, and operations (DevSecOps). For example, a computer-implemented method includes receiving, by a processor, a plurality of infrastructure as code files specifying a configuration of a runtime environment for a deployable image of source code in a continuous integration and continuous delivery pipeline for a cloud platform; generating, by the processor, compliance code for at least one file of the plurality of infrastructure as code files; building, by the processor, the deployable image of the source code in the continuous integration and continuous delivery pipeline according to the configuration specified by the plurality of infrastructure as code files and the compliance code; and deploying, by the processor, an instance of the image in the runtime environment.

Abstract: A system for communicating and managing messaging between a source system and a destination system including a publisher module, a topic module that receives the message from the publisher module and including one or more subscription modules, a queue module that receives the message from the topic module, a success queue module, an error queue module, and a subscriber module that receives the message from the queue module, then decompresses, decrypts, calculates the check sum, then prepares the message for transmission to the destination system and transmits the message to the destination system.

Abstract: The disclosure relates to a method, system and computer readable media for validating that a configuration of a cloud system meets requirements, using a reduced test suite selected from a test suite. The method includes classifying the requirements and service instances realizing the requirements composing the cloud system. The method includes applying test suite reduction rules to the test suite, using the classified requirements and service instances, to obtain the reduced test suite. The method includes applying the reduced test suite to the cloud system configured with the configuration, thereby validating that the configuration of the cloud system meets the requirements.

Abstract: The system receives, from a client, a first request for a document which is parsed based on a syntax. The system parses and returns an initial number of lines of the document, thereby allowing the client to display the parsed initial number of lines in a visible window. Subsequent to successfully parsing a remainder of the lines, the system stores a fully-parsed version. Responsive to a scrolling action in the visible window, the system provides a relevant portion of an unparsed document associated with the first request. Responsive to detecting a termination of the scrolling action, the system receives a second request for parsed lines corresponding to a first set of lines. The system returns the corresponding parsed lines, thereby allowing the client to display the corresponding parsed lines in the visible window.

Abstract: A sample set of cloud computing resources is dynamically selected for testing a software deployment. Telemetry data associated with the resources and customer support data associated with customers that utilize the resources are obtained. A subset of the customers is selected based on the customer support data, and a candidate subset of the resources is selected based on the selected subset of customers and the telemetry data. Criteria for the selection is based on usage patterns and is configurable. Resources of customers with special support agreements, and customers previously selected, may be excluded from the candidate subset. The sample set of cloud computing resources may be randomly selected from the candidate subset. Software is deployed to the sample set as a B resource group and tested for issues with an A resource group to determine whether to proceed to full deployment, roll back the deployment, and/or retest the software.

Abstract: An automated program repair tool utilizes a neural transformer model with attention to predict the contents of a bug repair in the context of source code having a bug of an identified bug type. The neural transformer model is trained on a large unsupervised corpus of source code using a span-masking denoising optimization objective, and fine-tuned on a large supervised dataset of triplets containing a bug-type annotation, software bug, and repair. The bug-type annotation is derived from an interprocedural static code analyzer. A bug type edit centroid is computed for each bug type and used in the inference decoding phase to generate the bug repair.

Abstract: A source code correction assistance apparatus is configured to include a storage device that stores an updated source code, and an arithmetic operational device that generates, as an evaluation code template of the updated source code, a template including a conditional branch sentence related to each case of success or failure of an input condition, notifies an evaluator terminal of a request to create an evaluation code based on the template, controls an access to the updated source code by the evaluator, receives editing by the evaluator on the conditional branch sentence in the template, generates a list of input values for executing all control paths of the evaluation code after the editing, and generates an evaluation code driver that automatically executes the evaluation code by inputting the input value.

Abstract: A test program generation method, a test program generation device, a computer readable storage medium, and an electronic equipment are disclosed. The test program generation method includes: acquiring a configuration information of the memory and a test logic for the memory; determining at least one type of test program components from a preset test program component library according to the test logic; and acquiring a test program according to the configuration information by combining a plurality of test program components. Types of the plurality of test program components are included in the determined at least one type of test program components. The test program generation method not only meets different test requirements and matches different test conditions, but also avoids coding errors and improve the efficiency and accuracy in generating a memory test program.

Abstract: A method and system include code analysis and visualization technology. The method and system include (i) a repository that stores developer code in a codebase to which many developers and developer teams contribute code over time, (ii) one or more static analysis tools that identify misbehaviors in the codebase from a list of predetermined misbehaviors, (iii) a database that includes each commit that each developer performed on the codebase for a predetermined period of time, (iv) a code attribution tool that employs abstract syntax trees to determine if each commit that a particular developer performs resulted in breaking the code or impairing the code, or results in a failure to correct the code, or if clean code results, and (v) a dashboard tool that enables visualization at different levels of commits with misbehaviors over a predetermined period of time.

Abstract: A computer-readable medium stores instructions that, when executed by one or more processors of a computing device, cause the computing device to dynamically generate and display, on an interactive display, one or more person icons and one or more property icons representing persons and properties associated with a loss event. Each person and property icon is generated and displayed as a user adds a corresponding person or property via the interactive display. Each of the person icons is a graphical representation of a person and each of the property icons is a graphical representation of a type of the corresponding property. The instructions also cause the computing device to dynamically link specific ones of the person icons to specific ones of the property icons as the user specifies relationships between the specific ones of the person icons and the specific ones of the property icons via the interactive display.

Abstract: The execution-time reporting of telemetry of execution of a software program. Subscribers submit subscriptions to telemetry of the software program. As each subscription is received, the telemetry scope of the subscription is evaluated to determine what portion of an object model is to be augmented. The augmented portion will include portion(s) related to the scope of telemetry subscribed to in the subscription. Thereafter, that portion of the object model is indeed augmented as execution of the computer program proceeds further. Subsequently, telemetry reports are generated for a subscription based on the interpretation of a defined subscription-specific portion of the object model.

Abstract: An instantiated application includes both a runtime instantiation of an application image, and an administrative service operable to install in the instantiated application at least one security module during runtime of the instantiated application in a container. Prior to runtime, a design time agent can access the application image in a repository, examine the application image, and based on the examining, adding at least one security module to the application image prior to instantiation. During runtime, a runtime agent can query parameters of the container, such as static and dynamic variables available on the machine on which the container is running. The runtime agent processes these parameters in conjunction with predefined rules to determine an action such as starting, stopping, adding, and/or changing the security module, such as the method of packet inspection.

Abstract: Metrics corresponding to services provided by a cloud service provider can be received via a first API responsive to queries specifying identifiers of the services. A configuration file can be maintained that includes mappings between the identifiers of the services and the metrics corresponding to the services. An identifier of a new service provided by the cloud service provider can be received via a second API. A mapping between the identifier of the new service and a metric corresponding to the new service can be received by the configuration file. The metric corresponding to the new service can be received via the first API responsive to a query specifying the identifier of the new service.

Abstract: The execution-time reporting of telemetry of execution of a software program. Subscribers submit subscriptions to telemetry of the software program. As each subscription is received, the telemetry scope of the subscription is evaluated to determine what portion of an object model is to be augmented. The augmented portion will include portion(s) related to the scope of telemetry subscribed to in the subscription. Thereafter, that portion of the object model is indeed augmented as execution of the computer program proceeds further. Subsequently, telemetry reports are generated for a subscription based on the interpretation of a defined subscription-specific portion of the object model.

Abstract: Examples of analyzing a log file are described. In an example, a log file comprising a plurality of event records is obtained from a computing device. The event records in the plurality of log files may be processed. Thereafter, an occurrence of anomaly in the log file may be ascertained.

Abstract: Methods and systems are disclosed herein for using one or more machine learning models to determine whether a user is expected to complete a task or action by a deadline. The one or more machine learning models may be trained and/or used to recommend a communication protocol for sending a reminder to the user such that the user is predicted to be more likely to complete an action by the action's deadline. A computing system may use the one or more machine learning models to generate a recommendation for type of reminder to send, for example, if it is predicted that the user is not expected to complete the task by the deadline. A computing system may determine the message to send, the communication protocol to use, and/or the time to send the message.

Abstract: Aspects of the invention include receiving system data associated with a first system, the first system comprising a plurality of system components, wherein the system data comprises component data for each system component in the plurality of system components, obtaining historical performance data for each system component in the plurality of system components, determining at least one testing constraint associated with the first system, determining a test environment for the first system, the test environment comprising a plurality of test cases for the first system based on the system data, the historical performance data, and the at least one testing constraint, and executing the test environment on the first system.

Abstract: A code change request prioritization tool that uses weighting values specific to pre-determined factors to concurrently calculate a total weighted prioritization score, is disclosed. The total weighted prioritization score may be calculated using a percentile score for factors as inputs in the calculation. Once a solution is found for a highest priority code change request, similar code defects may be identified so as to provide solutions to all similar defects, simultaneously.

Abstract: Technologies are provided for assigning developers to source code issues using machine learning. A machine learning model can be generated based on multiple versions of source code objects (such as source code files, classes, modules, packages, etc.), such as those that are managed by a version control system. The versions of the source code objects can reflect changes that are made to the source code objects over time. Associations between developers and source code object versions can be analyzed and used to train the machine learning model. Patterns of similar changes to various source code objects can be detected and can also be used to train the machine learning model. When an issue is detected in a version of a source code object, the model can be used to identify a developer to assign to the issue. Feedback data regarding the developer assignment can be used to re-train the model.

Abstract: A system for communicating and managing messaging between a source system and a destination system including a publisher module, a topic module that receives the message from the publisher module and including one or more subscription modules, a queue module that receives the message from the topic module, a success queue module, an error queue module, and a subscriber module that receives the message from the queue module, then decompresses, decrypts, calculates the check sum, then prepares the message for transmission to the destination system and transmits the message to the destination system.

Abstract: A test environment apparatus having processing circuitry is provided for testing an embedded system-under-test. The processing circuitry may be configured to implement the system-under-test for interaction with external test participants via messaging and control operation of an inner agent and an outer agent. The inner agent may be implemented within a virtual machine that is also implementing the system-under-test and the outer agent may be implemented external to the virtual machine implementing the system-under-test. The inner agent and the outer agent may be controlled to operate collaboratively to trigger captures of snapshots that store current states of the system-under-test at respective times and trigger a rollback of the system-under-test based on a timestamp of a delayed message using a snapshot for a selected time that provides a state of the system-under-test prior to the timestamp to permit subsequent delivery of the delayed message with the system-under-test in a rollback state.

Abstract: One or more processors examine source code of one or more software packages that produce output messages and identify, in the source code, one or more call expressions that each represent a logging call. The one or more processors generate a number of search patterns for parsing output messages produced by the one or more software packages, wherein each of the search patterns is based on one or more arguments of a corresponding call expression of the one or more call expressions. The one or more processors further reduce the number of search patterns to be applied to the output messages produced by the one or more software packages to identify log entries among the output messages.

Abstract: A method may include applying to at least a portion of historical runtimes associated with each of a plurality of tests included in a test suite, a machine learning model trained to identify one or more outlying runtime values. The portion of historical runtimes may include an n quantity of the most recent historical runtimes. An expected runtime for each test may be determined based on the portion of historical runtimes excluding the outlying runtime values. A schedule for executing each test in the test suite may be determined based on the expected runtime of each test. The test suite may be executed in accordance with the schedule. Moreover, the executing of the test suite may be monitored based on the expected runtime of each test. Related systems and computer program products are also provided.

Abstract: Systems and methods can implement a review process to evaluate changes to target code as part of development cycles for a continuous integration, continuous deployment pipeline for software-based products. The system can aggregate data and determine if the target code has been modified preliminarily and then intelligently determine where further review is needed before the changes are permanently implemented. To do this, a changeset including the preliminarily changed target code can be obtained from the aggregated data. The changeset can be tested with a prediction model based on feature data that characterizes aspects of a coding process carried out to generate the preliminary modification. The prediction model can provide an activation recommendation for the preliminary modification based on a plurality of risk factors determined from the testing. The prediction model can be trained, continuously, with training data that includes a plurality of data artifacts resulting from a code build processes.

Abstract: A computer generates a profile, where the profile comprises one or more programs to monitor. The computer determines a baseline for each of the one or more programs by collecting one or more values associated with a normal operation for each of the one or more programs. The computer detects an anomaly based on deviation of the one or more values from the normal operation. Based on identifying a playbook for the anomaly, the computer applies the playbook on the program from the one or more programs. The computer organizes chat services based on identifying one or more members associated with the anomaly.

Abstract: Disclosed herein are methods, systems, and processes for automated log entry identification and alert management. A log statement that includes a log format string and is part of program code associated with a computer program is accessed at a log management server. The execution of the log statement generates a log string that is associated with a trigger pattern of an alert configuration. A fixed part of the log format string that remains unchanged during execution of the log statement when the program code associated with the computer program is executed is extracted and a template is generated for the log statement to track changes to the fixed part of the log format string that causes a mismatch between the trigger pattern of the alert configuration and the log string. The template is then stored.

Abstract: Various methods are provided for quantum computing (QC) based code-optimization. One example method may comprise receiving an indication of one or more runtime hotspots in executed code based on one or more QC algorithms, testing a portion of the executed code associated with at least one of the one or more identified runtime hotspots; generating a plurality of performance information indicators comprising information resulting from the testing of the portion of the code; selecting, based on the plurality of performance information indicators, one QC algorithm for the at least one of the one or more identified runtime hotspots; and utilizing the selected QC algorithm for the at least one of the one or more identified runtime hotspots to optimize the at least one of the one or more identified runtime hotspots.

Abstract: A sample set of cloud computing resources is dynamically selected for testing a software deployment. Telemetry data associated with the resources and customer support data associated with customers that utilize the resources are obtained. A subset of the customers is selected based on the customer support data, and a candidate subset of the resources is selected based on the selected subset of customers and the telemetry data. Criteria for the selection is based on usage patterns and is configurable. Resources of customers with special support agreements, and customers previously selected, may be excluded from the candidate subset. The sample set of cloud computing resources may be randomly selected from the candidate subset. Software is deployed to the sample set as a B resource group and tested for issues with an A resource group to determine whether to proceed to full deployment, roll back the deployment, and/or retest the software.

Abstract: A software code testing system includes sub-engines and a test case database storing test cases. A test case sub-engine runs each of the test cases on a plurality of software code modules, and a software code coverage determination sub-engine identifies a respective software code coverage for each software code method included in each of the software code modules. A test case/software code coverage mapping sub-engine then maps the respective software code coverage for each of the software code methods included in each of the software code modules with the respective test case that was run on that software code module to provide a test case/software code coverage mapping, which is used by a test suite optimization sub-engine to generate a test suite that includes a subset of the test cases that provide a desired level of software code coverage using a minimum number of test cases.

Abstract: An automated program repair tool utilizes a neural transformer model with attention to predict the contents of a bug repair in the context of source code having a bug of an identified bug type. The neural transformer model is trained on a large unsupervised corpus of source code using a span-masking denoising optimization objective, and fine-tuned on a large supervised dataset of triplets containing a bug-type annotation, software bug, and repair. The bug-type annotation is derived from an interprocedural static code analyzer. A bug type edit centroid is computed for each bug type and used in the inference decoding phase to generate the bug repair.

Abstract: Certain embodiments of the present invention are configured to facilitate analyzing computer code more efficiently. For example, by conducting a first level abstraction (e.g., symbolic interpretation and algebraic simplification) and a second level abstraction (e.g., generalization) of the computer code, the analysis may more accurately account for variations in the code that may occur as a result of register renaming, instruction reordering, choice of instructions, etc. while minimizing the cost of computations required to perform the analysis.

Abstract: Livelock recovery circuits configured to detect livelock in a processor, and cause the processor to transition to a known safe state when livelock is detected. The livelock recovery circuits include detection logic configured to detect that the processor is in livelock when the processor has illegally repeated an instruction; and transition logic configured to cause the processor to transition to a safe state when livelock has been detected by the detection logic.

Abstract: A system for tracking an asset including one or more processing devices that identify a spatial region in a complex number space, the spatial region being associated with the asset, receive a user defined password, identify a plurality of key locations within the spatial region at least in part using the user defined password, calculate key numerical values at each of the plurality of key locations using a defined complex number formula and use the key numerical values to generate an encryption key. The asset can be associated with a user by storing an asset record in a database which is indicative of an asset identifier, the spatial region and an encrypted payload derived using the encryption key.

Abstract: Computer-implemented method for improving the test results of a static code analyzer includes: receiving a plurality of test violations from the static code analyzer; constructing a first vector for each code snippet containing error candidates; constructing a second vector for each test violation from meta-data associated with said each test violation; merging the first vector with the second vector to produce a feature vector for each test violation; and applying statistical learning techniques to each feature vector to estimate a probability that an error candidate in the plurality of test violations is a true error or a false positive.

Abstract: An information processing apparatus, a method, and a non-transitory recording medium. The information processing apparatus includes circuitry to acquire an operation log of a target device, generate a first vector of a distributed representation indicating the operation log, and calculate the first vector and a vector of a distributed representation based on another operation log to identify the first vector.

Abstract: The present application discloses an association method, instruction method, and device for a synchronization block and a paging-scheduling signaling message. In the present application, a terminal performs beam sweeping on received synchronization blocks to obtain a target synchronization block; and the terminal, according to a correspondence between a synchronization block and a paging-scheduling signaling message, determines a paging-scheduling signaling message corresponding to the target synchronization block.

Abstract: One or more processors examine source code of one or more software packages that produce output messages and identify, in the source code, one or more call expressions that each represent a logging call. The one or more processors generate a number of search patterns for parsing output messages produced by the one or more software packages, wherein each of the search patterns is based on one or more arguments of a corresponding call expression of the one or more call expressions. The one or more processors further reduce the number of search patterns to be applied to the output messages produced by the one or more software packages to identify log entries among the output messages.

Abstract: A processing device performs a preliminary grouping of data items in a dataset to define one or more clusters and for each cluster, identifies a set of search terms for a search query that would retrieve data items in the cluster upon execution of the search query against the dataset.

Abstract: A method for use in a computing device having a processor, the method comprising: executing a computer program on the processor; while the computer program is running, detecting whether any of a plurality of transition instructions of the computer program is executed, the detecting being performed by using resources that are external to the computer program; in response to detecting that a given one of the transition instructions is executed, detecting whether a current execution flow of the computer program matches a control flow graph for the computer program; and performing a countermeasure action based on one of a mismatch of the current execution flow of the computer program and the control flow graph or a current value of a memory location associated with the computer program; wherein the control flow graph for the computer program is generated by simulating an execution of the computer program.

Abstract: Embodiments disclose a system/method for constraint-guided hybrid fuzzing. According to one embodiment, a system performs a grey box fuzzing for a program code, where the performing mutates an initial seed input to generate a first set of seed inputs. The system performs a concolic execution for the program code using the first set of seed inputs to generate a second set of seed inputs. The system determines constraint information associated with the second set of seed inputs by analyzing the concolic execution. The system performs one or more modified grey box fuzzing based on the second set of seed inputs bounded to the constraint information. That way the bounded portion of the second set of seed inputs are not mutated by the grey box fuzzing.

Abstract: Systems and methods for developing software applications including user interfaces. A user interface that is developed in a distributed manner may include components or plugins from multiple developers. The plugins can be evaluated prior to approval to determine whether any changes to the plugins are isolated and do not adversely impact other plugins or portions of the user interface. Plugins that are not sufficiently isolated are rejected.

Abstract: Systems, devices, media, and methods are presented for testing the capability of a mobile device to run a particular feature of an application. Each feature may include a package of code, a call, a state, and a condition; each condition correlated with a specific state. The call is a query that includes instructions to evaluate whether the application will run successfully if a particular feature is running. If the call fails, the feature condition remains Off, resulting in a rollback of the feature. If the call succeeds, the feature condition is changed to On. The system may include an experimentation framework on each mobile device for registering features, executing calls, logging results, and maintaining states and conditions.

Abstract: Storing and executing an application in a personal storage with a user-granted permission in a decentralized network that implements a distributed edger. First, receiving a request from an entity for storing an application in a data storage that is associated with a DID owner. The application is configured to use data stored in the data storage as one or more inputs to generate one or more results. Next, one or more characteristics of the application associated with the entity is identified. Based on identified one or more characteristics, a write permission is to be granted to the entity, and the application is stored in the data storage. Thereafter, the application stored in the data storage is executed using data stored in the data storage.

Abstract: According to one embodiment, a system receives an intermediate result generated by a compiler based on source code, where the intermediate result includes one or more vulnerability indicators indicating one or more lines of the source code being potentially vulnerable. The system performs a grey box fuzzing on a first executable code generated from the intermediate result to generate a first set of seed inputs. The system calculates a vulnerability score for each of the seed inputs of the first set based on the vulnerability indicators for the lines of the source code reachable but has not been explored by the grey box fuzzing. The system selects one of the seed inputs in the first set having a highest vulnerability score. The system performs a concolic execution using the selected seed input as priority, the concolic execution being performed on a second executable code generated from the intermediate result.

Abstract: Aspects of the invention include methods, systems and computer program products for identifying interaction software defects. Aspects include singly executing a first testcase at a normal processing speed and singly executing a second testcase at the normal processing speed. Aspects also include simultaneously executing the first testcase at a first processing speed and a second testcase at a second processing speed. Based on determining the single and simultaneous testcase results do not match, aspects further include creating an error notification.

Abstract: Storing and executing an application in a personal storage with a user-granted permission in a decentralized network that implements a distributed edger. First, receiving a request from an entity for storing an application in a data storage that is associated with a DID owner. The application is configured to use data stored in the data storage as one or more inputs to generate one or more results. Next, one or more characteristics of the application associated with the entity is identified. Based on identified one or more characteristics, a write permission is to be granted to the entity, and the application is stored in the data storage. Thereafter, the application stored in the data storage is executed using data stored in the data storage.