Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator

摘要: Software systems nowadays have large configuration spaces. Pairwise test design technique is found useful by testers to sample only required options of these for exploring errors owing their interactions. Being a NP-complete problem, pairwise suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in literature. ATLBO recent enhanced variant (TLBO) that adaptively applies its search operations Mamdani-type fuzzy inference system. Presently, enters into stagnation or sometimes converges abnormally after some iterations. To address this issue, paper proposes with remedial operator so as further improve searching capabilities. evaluate performance operator, it used strategy called pATLBO_RO problem. Experimental results reveal strong against other and hyper-heuristic based strategies.