Function block diagram (FBD) is a standard programming language for programmable logic controllers (PLCs). As PLCs have been commonly used to develop safety-critical systems, it is crucial to test FBD programs for such systems effectively. Research on automated FBD test generation mainly focused on achieving certain structural coverage criteria. Although tests achieving a high coverage level can detect errors, they fail to provide the assurance of fault detection. Mutation testing is an error-based testing technique that can be used to generate mutation-adequate test suite. Mutation-adequate test suites are highly effective at revealing specific types of faults that are expressed by mutation operators. Since FBD programs are mainly implemented in safety-critical systems, it is required to provide some guarantees for fault detection. To provide a certain level of guarantee for detecting specific types of faults, this project MuFBDTester developed an automated testing tool that generates mutation-based test sequence for FBD programs.
This project is developed using Eclipse IDE.
- Lingjun Liu, Eunkyoung Jee, and Doo-Hwan Bae. MuFBDTester: A mutation-based test sequence generator for FBD programs implementing nuclear power plant software. Softw Test Verif Reliab. 2022. e1815. https://doi.org/10.1002/stvr.1815
- Lingjun Liu. "Automated Mutation-adequate Test Generation for Function Block Diagram Programs." Master thesis, KAIST, 2021.
- Lingjun Liu, Eunkyoung Jee, and Doo-Hwan Bae. "MuGenFBD: Automated Mutant Generator for Function Block Diagram Programs." KIPS Transactions on Software and Data Engineering 10.4 (2021): 115-124.
- Lingjun Liu, Eunkyoung Jee, and Doo-Hwan Bae. "Analysis of coupling effect hypothesis for function block diagram programs." Korea Software Congress, pp. 162-164, 2020.
- Lingjun Liu, Eunkyoung Jee, and Doo-Hwan Bae. "Automated mutant generation for function block diagram programs." Proceedings of the 22nd Korea Conference on Software Engineering (KCSE), pp. 154-155, 2020.
Lingjun Liu: riensha@se.kaist.ac.kr