Combining Dynamic Symbolic Execution, Machine Learning and Search-Based Testing to Automatically Generate Test Cases for Classes
This addresses the challenge of creating adequate test suites for classes, which is an incremental improvement over existing techniques.
The authors tackled the problem of automatically generating thorough test cases for object-oriented programs by combining dynamic symbolic execution, search-based testing, and machine learning, with preliminary experiments indicating positive results.
This article discusses a new technique to automatically generate test cases for object oriented programs. At the state of the art, the problem of generating adequate sets of complete test cases has not been satisfactorily solved yet. There are various techniques to automatically generate test cases (random testing, search-based testing, etc.) but each one has its own weaknesses. This article proposes an approach that distinctively combines dynamic symbolic execution, search-based testing and machine learning, to efficiently generate thorough class-level test suites. The preliminary data obtained carrying out some experiments confirm that we are going in the right direction.