MORTO分析:多目标回归检验优化

Neha Gupta, Arun Sharma, M. K. Pachariya
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引用次数: 0

摘要

无论何时在软件中进行更改,都要进行回归测试以检查代码中最近的更改是否在系统中创建了任何不想要的缺陷。由于回归测试套件的规模非常大,优化算法可以帮助选择、最小化测试套件并确定测试套件的优先级。主要目的是在较少的测试用例的情况下最大限度地提高故障检测能力。各种优化技术都是可用的,但多目标算法是使用的最佳选择,因为测试依赖于许多充分性标准或替代品。本文对回归检验中使用多目标算法的研究论文进行了研究。然后对多目标算法进行性能比较,确定最适合进行回归测试的多目标算法。
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Analysis of MORTO:Multi-objective Regression test optimization
Whenever a change is done in software, regression testing is done to check that a recent change in code has not created any unwanted defects in the system. As size of regression test suite is very large, optimization algorithms help in selecting, minimizing and prioritizing test suites. Main aim is maximize fault detection ability with less number of test cases. Optimization techniques of various types are available but Multiobjective algorithms are the best choice to use as testing is dependent on many adequacy criteria or surrogates. In this paper, authors have carried out study on research papers where multi-objective algorithms are used in regression testing. Then comparison of performance of multi-objective algorithms is done to identify the best suitable multi-objective algorithm for regression testing.
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