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首页> 外文会议>IEEE International Symposium on Software Reliability Engineering >SCOUT: A Multi-objective Method to Select Components in Designing Unit Testing
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SCOUT: A Multi-objective Method to Select Components in Designing Unit Testing

机译：SCOUT：在设计单元测试中选择组件的多目标方法

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The creation of a suite of unit testing is preceded by the selection of which components (code units) should be tested. This selection is a significant challenge, usually made based on the team member's experience or guided by defect prediction or fault localization models. We modeled the selection of components for unit testing with limited resources as a multi-objective problem, addressing two different objectives: maximizing benefits and minimizing testing cost. To measure the benefit of a component, we made use of metrics from static analysis (cost of future maintenance), dynamic analysis (risk of fault, and frequency of calls), and business value. We tackled gaps and challenges in the literature to formulate an effective method, the Selector of Software Components for Unit Testing (SCOUT). SCOUT provides an automated extraction of all necessary data followed by a multi-objective optimization process. SCOUT is a method able to assist testers in different domains, and the Android platform was chosen to perform our experiments, taking nine leading open-source applications as our subjects. SCOUT was compared with two of the most frequently used strategies in terms of efficacy. We also compared the effectiveness and efficiency of seven algorithms in solving a multi-objective component selection problem. Our experiments were performed under different scenarios, and reveal the potential of SCOUT in reducing the market vulnerability, compared to others approaches. To the best of our knowledge, SCOUT is the first method to assist in an automated way software testing managers in selecting components for the development of unit testing, combining static and dynamic metrics and business value.
机译：在创建一组单元测试之前，先选择应该测试哪些组件（代码单元）。这种选择是一个巨大的挑战，通常是基于团队成员的经验或在缺陷预测或故障定位模型的指导下进行的。我们将有限资源的单元测试组件选择建模为一个多目标问题，解决了两个不同的目标：最大化收益和最小化测试成本。为了衡量组件的优势，我们使用了来自静态分析（未来维护成本），动态分析（故障风险和呼叫频率）以及业务价值的指标。我们解决了文献中的空白和挑战，以制定一种有效的方法，即用于单元测试的软件组件选择器（SCOUT）。 SCOUT提供对所有必要数据的自动提取，然后进行多目标优化过程。 SCOUT是一种能够协助不同领域的测试人员的方法，并且选择了Android平台来进行我们的实验，以9个领先的开源应用程序为主题。就有效性而言，将SCOUT与两种最常用的策略进行了比较。我们还比较了七种算法在解决多目标组件选择问题上的有效性和效率。我们的实验是在不同的场景下进行的，与其他方法相比，它揭示了SCOUT在降低市场脆弱性方面的潜力。据我们所知，SCOUT是第一种以自动化方式协助软件测试经理选择用于开发单元测试的组件的方法，该组件结合了静态和动态指标以及业务价值。

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