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Predicting Testability of Concurrent Programs

机译:预测并发程序的可测试性

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Concurrent programs are difficult to test due to their inherent non-determinism. To address the nondeterminism problem, testing often requires the exploration of thread schedules of a program, this can be time-consuming for testing real-world programs. We believe that testing resources can be distributed more effectively if testability of concurrent programs can be estimated, so that developers can focus on exploring the low testable code. Voas introduces a notion of testability as the probability that a test case will fail if the program has a fault, in which testability can be measured based on fault-based testing and mutation analysis. Much research has been proposed to analyze testability and predict defects for sequential programs, but to date, no work has considered testability prediction for concurrent programs, with program characteristics distinguished from sequential programs. In this paper, we present an approach to predict testability of concurrent programs at the function level. We propose a set of novel static code metrics based on the unique properties of concurrent programs. To evaluate the performance of our approach, we build a family of testability prediction models combining both static metrics and a test suite metric and apply it to real projects. Our empirical study reveals that our approach is more accurate than existing sequential program metrics.
机译:由于其固有的非确定性,并发计划难以测试。为了解决非必需问题,测试通常需要探索程序的线程时间表,这可能对测试真实世界的程序来耗时。我们认为,如果可以估计并发程序的可测试性,则可以更有效地分发测试资源,以便开发人员可以专注于探索低可测试代码。 Voas介绍了可测试性的概念,因为程序具有故障,可以基于基于故障的测试和突变分析来测量可测试性的概率。已经提出了许多研究来分析可测试性并预测顺序程序的缺陷,但到目前为止,没有任何工作已考虑对并发程序的可测试性预测,与顺序程序区分开率。在本文中,我们提出了一种方法来预测在功能级别的并发程序的可测试性。我们基于并发程序的唯一属性提出了一组新颖的静态代码指标。为了评估我们的方法的性能,我们构建了一系列可测试性预测模型,将静态度量和测试套件指标组合并将其应用于实际项目。我们的实证研究表明,我们的方法比现有的连续计划度量更准确。

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