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Ideas on Signal Generation for Evolutionary Testing of Continuous Systems

2009/01/01 by Andreas Windisch, Windisch, Andreas
Biochemistry, Genetics and Molecular Biology · Computer Science · #Evolutionary Algorithms and Applications #Metaheuristic #Optimization #Search-Based Testing #Software Testing and Debugging Techniques #Viral Infectious Diseases and Gene Expression in Insects

paper · doi:10.4230/dagsemproc.08351.5

openalex publication_date 2009/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Test case generation constitutes a critical activity in software testing that is cost-intensive, time-consuming and error-prone when done manually. Hence, an automation of this process is required. One automation approach is search-based testing for which the task of generating test data is transformed into an optimization problem which is solved using metaheuristic search techniques. However, only little work has so far been done to apply search-based testing techniques to systems that depend on continuous input signals rather than single discrete input values. This paper proposes three novel approaches to generating input signals from within search-based testing techniques for continuous systems.

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