Visible to the public A Systematic Requirements and Risks-Based Test Case Prioritization Using a Fuzzy Expert System

TitleA Systematic Requirements and Risks-Based Test Case Prioritization Using a Fuzzy Expert System
Publication TypeConference Paper
Year of Publication2019
AuthorsHettiarachchi, Charitha, Do, Hyunsook
Conference Name2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)
KeywordsComplexity theory, Estimation, expert systems, fuzzy expert system, fuzzy expert systems, fuzzy set theory, human factors, Iron, Metrics, program testing, pubcrawl, regression analysis, regression testing, requirements risks-based testing, Resiliency, risk estimation process, risk information, risk-based approaches, Scalability, security, Security Risk Estimation, Software, software components, software engineering, software engineers, software requirements, systematic requirements, test case prioritization, Testing
AbstractThe use of risk information can help software engineers identify software components that are likely vulnerable or require extra attention when testing. Some studies have shown that the requirements risk-based approaches can be effective in improving the effectiveness of regression testing techniques. However, the risk estimation processes used in such approaches can be subjective, time-consuming, and costly. In this research, we introduce a fuzzy expert system that emulates human thinking to address the subjectivity related issues in the risk estimation process in a systematic and an efficient way and thus further improve the effectiveness of test case prioritization. Further, the required data for our approach was gathered by employing a semi-automated process that made the risk estimation process less subjective. The empirical results indicate that the new prioritization approach can improve the rate of fault detection over several existing test case prioritization techniques, while reducing threats to subjective risk estimation.
Citation Keyhettiarachchi_systematic_2019