2021/12/02 by Ling Xiao, Tim Menzies, Ling, Xiao +1 · 1 citation
Computer Science · Decision Sciences · Engineering · Mathematics · #Computer science #Domain (mathematical analysis) #Engineering #FOS: Computer and information sciences #Grid #Machine learning #Mathematical optimization #Mathematics #Model-Driven Software Engineering Techniques #Mutation #Real-time simulation and control systems #Selection (genetic algorithm) #Set (abstract data type) #Simulation Techniques and Applications #Software Engineering (cs.SE) #Task (project management) #Test (biology) #Test set #Variance (accounting)
paper · pdf · doi:10.48550/arxiv.2112.01598
published in arXiv (Cornell University) (Cornell University)
openalex publication_date 2021/12/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
For simulation-based systems, finding a set of test cases with the least cost by exploring multiple goals is a complex task. Domain-specific optimization goals (e.g. maximize output variance) are useful for guiding the rapid selection of test cases via mutation. But evaluating the selected test cases via mutation (that can distinguish the current program from the mutated systems) is a different goal to domain-specific optimizations. While the optimization goals can be used to guide the mutation analysis, that guidance should be viewed as a weak indicator since it can hurt the mutation effectiveness goals by focusing too much on the optimization goals. Based on the above, this paper proposes DoLesS (Domination with Least Squares Approximation) that selects the minimal and effective test cases by averaging over a coarse-grained grid of the information gained from multiple optimizations goals. DoLesS applies an inverted least squares approximation approach to find a minimal set of tests that can distinguish better from worse parts of the optimization goals. When tested on multiple simulation-based systems, DoLesS performs as well or even better as the prior state-of-the-art, while running 80-360 times faster on average (seconds instead of hours).