|Authors||D. Pradhan, S. Wang, T. Yue, S. Ali and M. Liaaen|
|Title||Search-Based Test Case Implantation for Testing Untested Configurations|
|Project(s)||The Certus Centre (SFI), Department of Engineering Complex Software Systems|
|Publication Type||Journal Article|
|Year of Publication||2019|
|Journal||Information and Software Technology|
|Keywords||genetic algorithms, Multi-objective optimization, Search, test case implantation|
Context: Modern large-scale software systems are highly configurable, and thus require a large number of test cases to be implemented and revised for testing a variety of system configurations. This makes testing highly configurable systems very expensive and time-consuming.
Objective: Driven by our industrial collaboration with a video conferencing company, we aim to automatically analyze and implant existing test cases (i.e., an original test suite) to test the untested configurations.
Method: We propose a search-based test case implantation approach (named as SBI) consisting of two key components: 1) Test case analyzer that statically analyzes each test case in the original test suite to obtain the program dependence graph for test case statements and 2) Test case implanter that uses multi-objective search to select suitable test cases for implantation using three operators, i.e., selection, crossover, and mutation (at the test suite level) and implants the selected test cases using a mutation operator at the test case level including three operations (i.e., addition, modification, and deletion).
Conclusion: SBI can be applied to automatically implant a test suite with the aim of testing untested configurations and thus achieving higher configuration coverage.