An Approach of Test Case Generation with Software Requirement Ontology

Software testing plays an essential role in software development process since it helps to ensure that the developed software product is free from errors and meets the defined specifications before the delivery. As the software specification is mostly written in the form of natural language, this may lead to the ambiguity and misunderstanding by software developers and results in the incorrect test cases to be generated from this unclear specification. Therefore, to solve this problem, this paper presents a novel hybrid approach, Software Requirement Ontologies based Test Case Generation (ReqOntoTestGen) to enhance the reliability of existing software testing techniques. This approach enables a framework that combines ontology engineering with the software test case generation approaches. Controlled Natural Language (CNL) provided by the ROO (Rabbit to OWL Ontologies Authoring) tools is used by the framework to build the software requirement ontology from unstructured functional requirements. This eliminates the inconsistency and ambiguity of requirements before test case generation. The OWL ontology resulted from ontology engineering is then transformed into the XML file of data dictionary. Combination of Equivalence and Classification Tree Method (CCTM) is used to generate test cases from this XML file with the decision tree. This allows us to reduce redundancy of test cases and increase testing coverage. The proposed approach is demonstrated with the developed prototype tool. The contribution of the tool is confirmed by the validation and evaluation result with two real case studies, Library Management System (LMS) and Kidney Failure Diagnosis (KFD) Subsystem, as we expected.

@article{Intana2023,
  title     = {An Approach of Test Case Generation with Software Requirement Ontology},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {14},
  number    = {8},
  year      = {2023},
  publisher = {The Science and Information Organization},
  author    = {Adisak Intana and Kuljaree Tantayakul and Kanjana Laosen and Suraiya Charoenreh},
  doi       = {10.14569/IJACSA.2023.01408109},
  url       = {https://doi.org/10.14569/IJACSA.2023.01408109}
}