Abstract: Provided is a method for automated verification of a software program in a Behavior-Driven Development environment and a data processing system configured to execute such a method. Individual test steps of BDD test scenarios are first matched and then assigned to existing test step definitions from a BDD framework. If a one-to-one matching is not possible, natural language processing is used to decide if an assignment is possible with a certain matching probability. The assigned test step definitions are used to generate graphical test models for the test scenarios, e.g., UML diagrams. Finally, executable test scripts are generated to test the software program. The present invention relates particularly to Behavior-Driven Development and combines traditional BDD advantages with Model Based Testing for improved convenience and automatization in case of complex software packages.

Abstract: A design control architecture and software quality assurance system for analyzing stimulus-response patterns in user activity data. A design control architecture and software quality assurance system may process user activity data according to a classifier model to assess an impact of an incremental design change to one or more quality measures of a software product. In accordance with certain embodiments the one or more quality measures may include one or more efficacy, safety, and/or performance metrics associated with one or more features of the software product. In certain embodiments, the software product may comprise a digital health intervention or software as a medical device product.

Abstract: An automated system is presented for unit testing an application in a mainframe execution environment. A plurality of stub objects reside in the mainframe execution environment, such that each stub object in the plurality of stub objects represents a different stub type. A command translator table is configured with an entry for each command available for an online transaction processor. Each entry in the command translator table specifies a stub type for the command and includes a listing of possible arguments associated with the given command, such that each possible argument in the listing of possible arguments has a specified category type. A test configurator executes in the mainframe execution environment and is configured to receive and parse a test input file. A setup routine interacts with the test configurator to receive records from the test input file.

Abstract: Methods and apparatuses are described for automated testing of mobile devices. A server establishes a connection with a client device via a high-latency connection. The server receives input from the client device comprising (i) a selection of mobile devices for testing and (ii) a selection of a test interaction. The server generates predicted interactions for each of the selected mobile devices using historical device interaction data. The server converts the predicted interactions into test scripts, each test script formatted for use with one of the selected mobile devices. The server deploys each test script for execution on the corresponding mobile device, and transmits results from the test script executions to the client device.

Abstract: Mechanisms are provided to generate a test dataset for software application development. A baseline mixed reality (MR) environment simulation of an existing process is generated that models applications of an application landscape. A requirement for an application that is to be developed is received and a MR component model is generated to represent the application based on a machine learning computer model processing of the requirements data structure and a knowledge corpus. The MR component model modifies the baseline MR environment simulation, and executes the modified MR environment simulation to simulate the modified MR environment simulation. The simulation is monitored for user input specifying a contextual scenario and context data is collected from the MR component models of the modified MR environment simulation. A test dataset for testing a coded version of the SUD application is generated based on the contextual scenario and the collected data.

Abstract: System and method for creating unit tests include: constructing a CFG representation for a computer program; utilizing the CFG to identify different potential execution paths and to identify different formulas corresponding to the different potential execution paths; parsing the source code to generate an abstract syntax tree; analyzing the computer program to determine whether it provides capability to set each of the associated variables in each formula by utilizing the abstract syntax tree; translating variables, fields, and expressions of the source code represented in each formula into decision variables; computing a solution to the list of pre-conditions from each formula to one of the potential solutions that specifies values for decision variables; selecting a formula, from the plurality of formulas, with a fewest number of associated variables; and creating a unit test, based on the data and the list of pre-conditions collected and solved.

Abstract: Embodiments facilitate testing of software functions, by elaborating upon a small volume test sample originally provided by a developer. Where the original test sample is determined to be numerical, embodiments perform repetition techniques to generate corpuses of test data of varying scope representing operation over different timescales. For original test samples of greater complexity (e.g., including text and/or hierarchical output states of the software function), embodiments select a relevant Machine Learning (ML) model and apply that ML model to generate the corpuses of test data. These are then available for loading to measure one or more performance parameters (e.g., runtime, memory consumption; processing consumption; bandwidth) of the software function. Broadly reported non-linear behavior of performance parameter(s) may reveal lack of suitability of the generated data corpuses for testing. More specific non-linear behavior may indicate failure of the software function to pass certain tests.

Abstract: A method creates a table of keys and values. Each key is an element of an input array which is an input of a machine-learning pre-processing pipeline, and each value is an output of the pipeline. The method measures (1) a hit rate H to the memo table, (2) an average time Ttable to look up the table, (3) an average time Tpipeline to execute the pipeline, and (4) a threshold Telements on a number of elements of the input array. The method looks up the value in the table by using an element of the input array as a key when Tpipeline×H>Ttable and the number of elements in the input array is less than Telements. The method calls the pipeline in place of the lookup for all of the remaining elements in the input array when the value is not in the table.

Abstract: A method includes receiving a test input, obtaining a resource access feedback indicating an access for a resource based on the test input, selectively, based on the resource access feedback indicating whether a first-time accessed resource is accessed based on the test input, adding the test input to a test input queue, and performing a fuzz test based on the test input queue with the test input.

Abstract: Examples for device-driven auto-recovery using multiple recovery sources are disclosed herein. At least one storage device or storage disk includes instructions that, when executed, cause at least one processor to at least detect a flaw in a first configuration of a program to be installed on a programmable device, the first configuration recorded on a first chain of a distributed ledger of a blockchain; correct the flaw in the first configuration to generate a corrected configuration; commit the corrected configuration to the distributed ledger, the corrected configuration to create a second chain of the distributed ledger; detect an update of the first configuration to a first updated configuration and an update to the corrected configuration to an updated corrected configuration; and prevent the first updated configuration from being installed on the programmable device by replacing the first updated configuration with the updated corrected configuration on the second chain.

Abstract: An operation method of a server for updating firmware includes: generating a first delta file including a plurality of blocks based on a plurality of update areas included in a first version firmware; generating a second delta file by repositioning the plurality of blocks included in the first delta file such that a plurality of unit blocks are generated by grouping control blocks, difference blocks, and extra blocks, each of which corresponds to the plurality of update areas, respectively; generating a plurality of swap blocks based on extra blocks among the plurality of blocks; and generating a third delta file by adding the generated plurality of swap blocks to the second delta file.

Abstract: A method of testing a physical system that includes software and hardware includes developing a software application arranged to operate at least a portion of the physical system and constructing a simulation of the physical system within a test ecosystem, the simulation including inputs that simulate control inputs of the physical system and outputs that simulate control and informational outputs. The method also includes connecting the software application to the simulation of the physical system to test the operation of the software application, and simulating operation of the physical system and the software application within test ecosystem operation of the software application as each of a cloud application, a network operation of the software application as each of a cloud application, a network application, and a local application.

Abstract: The present disclosure is directed to systems, media, and methods of accessing data from a test settlement file. An application programming interface (API) configured to permit alteration of one or more fields of test data in a test data file is exposed by a settlement generator. One or more fields of test data exposed by the API are altered. A test data file in a configurable format is generated based on the one or more fields of test data and alteration. The test data file is transmitted from the settlement generator to an orchestrator. A binary file, converted from the test data file, is transmitted from the settlement generator to a third-party processor. One or more pieces of data from a test settlement file are retrieved by the settlement generator, where the test settlement file includes processing results of the binary file received from the third-party processor.

Abstract: Systems and methods provide techniques for more effective and efficient proactive monitoring of a target software application framework. In response, embodiments of the present invention provide methods, apparatuses, systems, computing devices, and/or the like that are configured to enable effective and efficient proactive monitoring of a target software application framework using a load testing experiment definition data object, wherein the load testing experiment definition data object describes a load increase action definition, a steady state definition, and a fault inducement action definition.

Abstract: A system and method are provided for testing application. The method is executed by a device having a communications module and includes initiating via the communications module, an application testing tool, to test an application build according to at least one metric and obtain a test result. The method also includes accessing via the communications module, session details generated by the application testing tool while testing the application build, to determine an overhead component introduced by the application testing tool in generating the test result. The method also includes adjusting the test result based on the overhead component to increase an accuracy of the test result.

Abstract: A code hot-update method and terminal are provided. The method includes: code to be hot-updated is translated into first-type intermediate code, wherein the first-type intermediate code is compiled by using a compiler of a target-type operating system; the first-type intermediate code is translated into bytecode to be run, wherein the bytecode to be run is interpreted by an interpreter of the target-type operating system; and the bytecode to be run is interpreted by using the interpreter to hot-update the code to be hot-updated.

Abstract: Implementations generally relate to a method of automatically generating applications for multiple platforms based on one source of application code. Implementations include receiving a signal from a client device to initiate an application generation process, for example, through a graphical user interface (GUI). In an implementation, the application generation process analyzes the application code to differentiate between core application code, which is shared between many platforms, and device-specific code, and then separates the core application code from the device-specific code. The core application code may then be deployed for use in a plurality of applications such as a web application, progressive web application, or, as taken together with device-specific code, as a native mobile application. Applications may be deployed with features that are automatically determined based on their deployment method and the feature set of each platform.

Abstract: A robot design interface comprises tools for testing a robotic process automation (RPA) workflow. Some embodiments automatically generate a mock workflow comprising a duplicate of the original workflow wherein a set of RPA activities are replaced with substitute activities for testing purposes. Some embodiments expose an intuitive interface co-displaying the substitute activities in parallel to their respective original activities and enabling a user to configure various mock parameters. Testing is then carried out on the mock workflow.

Abstract: According to some embodiments, methods and systems may be associated with trustworthy application integration. A formalization platform may facilitate definition of pattern requirements by an integration developer. The formalization platform may also formalize singe pattern compositions and compose single patterns to template-based formalized compositions. A correctness platform may then check for structural correctness of the formalized compositions and execute a semantic transformation or binding to pattern characteristics and associated interactions. The correctness platform may also check composition semantics and generate a formal model. An implementation platform may translate the formal model generated by the correctness platform and configure implementation parameters of the translated formal model. The implementation platform may then execute the translated formal model in accordance with the configured implementation parameters.

Abstract: System and method are provided for facilitating performance testing.