Abstract: Systems and methods for weakly supervised unit test quality scoring are disclosed. According to one embodiment, a method may include: parsing, by a generative model computer program, a plurality of code snippets in a repository using an abstract syntax tree; receiving, by the generative model computer program, a plurality of binary labelling functions from a labelling function repository; creating, by the generative model computer program, a labelling matrix by applying the binary labelling functions to the parsed code snippets; training, by the generative model computer program, a probabilistic generative model using the labelling matrix resulting in a vector of pseudo-labels; building, by a unit test scoring computer program, a discriminative model, wherein the discriminative model receives an array of real value inputs; and training, by the unit test scoring computer program, the discriminative model using the parsed code snippets, the vector of pseudo labels, and the abstract syntax tree.

Abstract: Various methods, apparatuses/systems, and media for automatic risk-based testing of an application are disclosed. A processor accesses a database to obtain data corresponding to a plurality of test results of test runs conducted over a certain period of time for a set of plurality of tests and data corresponding to a change set; generates historical data based on the data corresponding to the plurality of test results and the change set; assigns a test failing probability value for each test among the set of plurality of tests based on analyzing the historical data; identities a first test whose assigned test failing probability value is below a predetermined threshold value; and filters out the identified first test from the set of plurality of tests whose assigned test failing probability value is below the predetermined threshold value so that the identified first test is not utilized for future test runs.

Abstract: Various methods, apparatuses/systems, and media for automatic risk-based testing of an application are disclosed. A processor accesses a database to obtain data corresponding to a plurality of test results of test runs conducted over a certain period of time for a set of plurality of tests and data corresponding to a change set; generates historical data based on the data corresponding to the plurality of test results and the change set; assigns a test failing probability value for each test among the set of plurality of tests based on analyzing the historical data; identities a first test whose assigned test failing probability value is below a predetermined threshold value; and filters out the identified first test from the set of plurality of tests whose assigned test failing probability value is below the predetermined threshold value so that the identified first test is not utilized for future test runs.

Abstract: Various methods, apparatuses/systems, and media for implementing a test optimization module are provided. A processor utilizes a static analysis technique which analyzes an application's byte code to determine what files and line-numbers have been changed in a source code based on comparing successive versions of the application. The processor creates a change dependency graph (CDG) based on a change scope and analyzed bytecode, traverses the CDG to generate a list of test cases among a plurality of test cases, accessed from a test repository, that are directly and/or indirectly related to the modification to the source code, and automatically executes only the test cases selected from the generated list to test the latest version of the application.

Abstract: Various methods, apparatuses/systems, and media for implementing a test optimization module are provided. A processor utilizes a static analysis technique which analyzes an application's byte code to determine what files and line-numbers have been changed in a source code based on comparing successive versions of the application. The processor creates a change dependency graph (CDG) based on a change scope and analyzed bytecode, traverses the CDG to generate a list of test cases among a plurality of test cases, accessed from a test repository, that are directly and/or indirectly related to the modification to the source code, and automatically executes only the test cases selected from the generated list to test the latest version of the application.