Change-driven Software Test Case Generation Method Based on Knowledge
Graph
- Chao Peng,
- Dunwei Gong,
- Xiangjuan Yao,
- Baicai Sun
Abstract
Testing is an important means to ensure the quality of software. With
the increase of software change frequency, the efficiency of testing is
required to be continuously improved. Among the many factors that affect
the efficiency of software testing, the generation of test cases is very
critical, and there is still a lack of effective methods. In this paper,
a method of software test case generation driven by knowledge graph
changes is proposed. Its purpose is to improve the efficiency of test
case generation by using the change of knowledge graph to determine the
test cases available for the changed software. Firstly, before and after
the change of the software knowledge graph is constructed. Then, the
changed entities and paths in the knowledge graph are identified, and
the test cases available for the software after the change are filtrated
by the similar entities. Meanwhile, the cases for testing the changed
entities are generated by multi-objective optimization method. Finally,
the above test cases are integrated to form a valid case set for testing
the changed software. The proposed method is applied to six benchmark
programs and compared with other algorithms. The experimental results
demonstrate that the proposed method can significantly improve the
efficiency and accuracy of test case generation.Submitted to Journal of Software: Evolution and Process Submission Checks Completed
Assigned to Editor
Reviewer(s) Assigned