An Empirical Study of Metric-based Comparisons of Software Libraries
An Empirical Study of Metric-based Comparisons of Software Libraries
复制标题
基于度量的软件库比较的实证研究
DOI：
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发表时间：
2018
期刊：
影响因子：
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通讯作者：
Sarah Nadi
中科院分区：
文献类型：
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作者：
Fernando López de la Mora;Sarah Nadi
背景：软件库提供了一组可重用的功能，帮助开发人员以系统和及时的方式编写代码。然而，选择适当的库来使用通常不是一件容易的事情。目的：在本文中，我们调查了软件度量在帮助开发人员选择库方面的有用性。不同的开发人员关心库的不同方面，在给定域中寻找库的两个开发人员可能不一定选择相同的库。因此，我们不是直接推荐要使用的库，而是为开发人员提供同一领域中的库的基于度量的比较，以使他们能够获得做出明智决策所需的信息。方法：我们使用来自多个信息源的软件数据分析来创建软件库的可量化的基于度量的比较。为了进行评估，我们从10个热门领域中选择了34个开源Java库，并提取了与这些库相关的9个指标。然后，我们对61名开发人员进行调查，以评估我们提出的基于指标的比较是否有用，并了解开发人员关心哪些指标。结果：我们的结果表明，开发人员发现所提出的技术在选择库时提供了有用的信息。我们观察到，开发人员最关心与库的受欢迎程度、安全性和性能相关的指标。我们还发现，一些指标的有用性可能会因域而异。结论：我们的调查结果表明，我们提出的技术是有用的。我们目前正在建立一个公共网站，用于基于公制的图书馆比较，同时纳入我们从调查参与者那里获得的反馈。
BACKGROUND: Software libraries provide a set of reusable functionality, which helps developers write code in a systematic and timely manner. However, selecting the appropriate library to use is often not a trivial task. AIMS: In this paper, we investigate the usefulness of software metrics in helping developers choose libraries. Different developers care about different aspects of a library and two developers looking for a library in a given domain may not necessarily choose the same library. Thus, instead of directly recommending a library to use, we provide developers with a metric-based comparison of libraries in the same domain to empower them with the information they need to make an informed decision. METHOD: We use software data analytics from several sources of information to create quantifiable metric-based comparisons of software libraries. For evaluation, we select 34 open-source Java libraries from 10 popular domains and extract nine metrics related to these libraries. We then conduct a survey of 61 developers to evaluate whether our proposed metric-based comparison is useful, and to understand which metrics developers care about. RESULTS: Our results show that developers find that the proposed technique provides useful information when selecting libraries. We observe that developers care the most about metrics related to the popularity, security, and performance of libraries. We also find that the usefulness of some metrics may vary according to the domain. CONCLUSIONS: Our survey results showed that our proposed technique is useful. We are currently building a public website for metric-based library comparisons, while incorporating the feedback we obtained from our survey participants.