Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.

Abstract: A method or system for testing and benchmarking commits made on source code. The system extracts commits from a history of a first code history that records a sequence of commits made thereon. The extracted commits are then combined into a sequence of patches, each of which includes changes made during consecutive commits. The system also establishes a connection with a system under test (SUT) having a second code repository corresponding to a historical version of the first code repository before the extracted commits were made, and sequentially applies the sequence of the patches to the second code repository. Performance of the SUT is monitored during the application of the sequence of the patches to determine whether the SUT performs as expected after the application of each patch.

Abstract: A system and method to adaptively generate a program model. Source code of a program to be tested for code issues, and a set of predefined patterns to be tested in the source code are received. Feature configuration data is generated by determining a set of features corresponding to the received set of predefined patterns. A set of program models is identified by selecting, for each feature in the set of features, a program model from among a plurality of program models that is optimized for the feature. A dynamic program model is built based on the identified set of program models, the dynamic program model being adapted to resolve each of the patterns included in the received set of predefined patterns. And the source code is tested for code issues by extracting from the dynamic program model instances of each of the set of predefined patterns.