鸣叫大步走
发表于 2025-3-21 17:12:20
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prolate
发表于 2025-3-21 22:21:52
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WAIL
发表于 2025-3-22 03:15:24
https://doi.org/10.1007/978-1-4757-2502-5This chapter describes how to use metaheuristic search and evolutionary algorithms to generate covering arrays for combinatorial testing. They include, among others, genetic algorithms, simulated annealing, tabu search, and particle swarm optimization.
善于骗人
发表于 2025-3-22 08:04:44
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暂时别动
发表于 2025-3-22 09:21:57
https://doi.org/10.1007/978-1-4757-5331-8This chapter lists some test generation tools (mostly, tools for finding covering arrays). The chapter also gives some pointers to benchmarks, so that the reader can evaluate and select tools.
profligate
发表于 2025-3-22 16:51:07
Nonconvex Optimization and Its ApplicationsThis chapter briefly discusses some other topics that are related to test data generation. They include, among others, how to construct a combinatorial testing model for the software under test, how to select a subset of test cases from an existing test suite, and how to generate special-purpose test cases in the process of debugging.
火海
发表于 2025-3-22 20:56:42
Introduction to Combinatorial Testing,This chapter gives an introduction to combinatorial testing, in particular, an overview of its applications. Some basic concepts, including Latin squares, orthogonal arrays, and covering arrays, are described in detail, with examples. Variants of covering arrays, such as covering arrays with constraints, are also described.
Entrancing
发表于 2025-3-23 01:09:15
Mathematical Construction Methods,This chapter presents some representative mathematical methods that are commonly used in the construction of orthogonal arrays and covering arrays, as well as some bounds on the size of such arrays.
murmur
发表于 2025-3-23 02:40:11
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candle
发表于 2025-3-23 05:36:37
Backtracking Search,This chapter describes how to use backtracking search to find covering arrays and orthogonal arrays. The basic algorithms are presented, as well as various heuristics which improve the efficiency of the search. Different from the approaches described in the previous chapters, backtracking search is able to find the smallest test suite.