Search-based Test Case Selection for PLC Systems Using Functional Block Diagram Programs

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Abstract

Programmable Logic Controllers (PLCs) are the core unit of the production system, which frequently need to implement new processes to address customer needs. These changes must be fully tested to ensure the reliability of the PLC code, which is commonly programmed through Functional Block Diagrams (FBDs). This is a tedious task that requires considerable time and effort given the manual nature of the process involved in PLC testing. Hence, we present a cost-effective test selection approach to test FBD programs in dynamic environments. The proposed method uses a search-based multi-objective test case selection algorithm as a regression technique to test recently modified FBD programs. Specifically, we derived a total of 7 fitness function combinations, by combining different cost and quality-based fitness functions. We carried out an empirical evaluation, by employing fitness metrics in the wellknown NSGA-II algorithm to determine the best configuration setup for testing FBD programs. Furthermore, we benchmarked the performance of the NSGA-II with the baseline Random Search (RS). The study was carried out with three case studies of a reactor protection system, and evaluated with two sets of mutants. The results demonstrated that the proposed approach significantly reduces time, while keeping high the overall fault detection capability.

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Key words

programmable logic controller,functional block diagram,test case selection,regression testing,search-based testing

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