Systems, methods, and computer-readable media are disclosed for unified regression testing. A first set of inputs configured to test a first scenario and a second set of inputs configured to test a second scenario may be received from a user. The first set of inputs may be used to generate a first set of outputs, and the second set of inputs may be used to generate a second set of outputs. A software update may be received. The first set of outputs may be regenerated using the first set of inputs, and the second set of outputs may be regenerated using the second set of inputs. The regenerated first set of outputs may be compared against the first set of outputs, and the regenerated second set of outputs may be compared against the second set of outputs. The comparison results may then be displayed to the user.

The system can identify data stored in repositories that indicate changes in the version of the application relative to a prior version of the application tested or deployed before receipt of the request to test the performance of the version of the application. The system can determine, based on the data and using machine learning with historical data associated with applications tested or deployed to test performance of the version, and without execution of the tests, a score for each of a plurality of tests configured to test performance of the version of the application. The system can select, based on the scores, a subset of the tests to execute, and provide an indication of the selected subset of the tests to cause execution of the subset of the tests to evaluate performance of the version of the application prior to deployment of the version of the application.

The disclosure relate to detecting performance regressions in software used to control autonomous vehicles. For instance, a simulation may be run using a first version of the software. While the simulation is running, CPU and memory usage by one or more functions of the first version of the software may be sampled. The sampled CPU and memory usage may be compared to CPU or memory usage by each of the one or more functions in a plurality of simulations each running a corresponding second version of the software. Based on the comparisons, an anomaly corresponding to a performance regression in the first version of the software relating to one of the one or more functions may be identified. In response to detecting the anomaly, the first version of the software and the one of the one or more functions may be flagged for review.

Systems and methods are disclosed for automatically assessing and conforming software development modules to accessibility guidelines in real-time. The systems may facilitate an incremental development of applications. One or more modules or base codes of the application, as they are developed, may be tested for compliance to various accessibility standards (e.g., Web Content Accessibility Guidelines 2.0). If a module or base does not meet a specific threshold of compliance, systems and methods allow for an automatic modification of the module or base code to make it more compliant to the accessibility standards.

Techniques are provided for tracking application programming interface (API) requests in a cloud computing environment. For example, a method for tracking API requests is implemented by an API gateway. The API gateway receives an API request which comprises a given API endpoint to access a target service of a computing system. The API gateway determines if the received API request is valid. In response to determining that the received API request is valid, the API gateway accesses at least one API counter associated with the given API endpoint of the received API request, wherein the at least one API counter is configured to count a number of times that the given API endpoint is accessed. The API gateway increments a count of the at least one API counter by one, and the API gateway routes the API request to the target service for execution.

An example method of operation may include automatically receiving information from a storage area in response to a signal, which information may include test results for a computer product evaluated by a plurality of test stages. The method may also include retrieving deployment parameters for the computer product, determining whether the test results satisfy the deployment parameters for the computer product, and automatically authorizing deployment of the computer product based on whether the test results satisfy the deployment parameters.

Methods, systems, and apparatus, including computer programs encoded on computer storage media, for performing self qualification of cloud based applications. One of the methods includes analyzing, by a self-qualified process (SQP), a set of risks for a cloud based software platform, wherein each risk comprises a set of features that are being evaluated according to a risk definition; performing, by the SQP, one or more tests related to one or more risks of the set of risks; and based on an outcome of each of the tests, generating a measure of a qualification state for the cloud based software platform, wherein the measure of the qualification state is used to determine self-qualification of the software platform.

A method of continuous development of an internal threat scan engine based on an iterative quality assessment includes iteratively performing a dynamic assessment of a quality of a threat detection with a frequency defined for each of objects in an object collection, wherein a result of the dynamic assessment includes internal and external scan results of the objects and a consistency verdict of the internal and external scan results of the objects, changing a frequency of scanning iteration of the objects based on the consistency verdict of the external and internal scan results of the objects, classifying the objects based on the result of the dynamic assessment, and creating a development task including the internal and external scan results of the objects, meta-data of the objects, and automated test results to provide details for developing a software to fix inconsistency of the internal and external scan results.

A non-transitory computer-readable recording medium storing an acceleration test program for causing a computer to execute a process, the process includes selecting a cooperation application that operates in cooperation with a test target application that is a target application of an acceleration test by accelerating an operation of an application, determining an acceleration degree of an operation in an acceleration mode in which an operation of an application is accelerated in comparison to a normal mode, and disabling an acceleration of an operation of a non-cooperation application that does not cooperate with the test target application during an acceleration of operations of the test target application and the cooperation application based on the acceleration degree.

An efficient and cost-effective method for usage of emulation machine is disclosed, in which a new concept and use model called debug station is described. The debug station methodology lets people run emulation using a machine from one vendor, and debug designs using a machine from another vendor, so long as these machines meet certain criteria. The methodology and its associated hardware hence are called a ‘platform neutral debug station.’ The debug station methodology breaks loose usage of emulation machines, where people can choose the best machine for running a design, and the best machine for debugging, and they do not need to be the same. Unlike the past, where people needed to run emulation and debug a design using same emulator from beginning to the end, the mix-and-match method described herein allows users to use emulators in the most efficient way, and often most cost effective too.