论文标题
得出独立于用法的软件质量指标
Deriving a Usage-Independent Software Quality Metric
论文作者
论文摘要
上下文：释放后使用软件的程度会影响故障的数量，从而偏向质量指标并对相关的决策产生不利影响。使用数据的专有性质限制了过去对该主题的更深入探索。目的：确定软件故障和软件的使用是如何相关的，以及如何设计准确的质量度量。方法：针对Android和iOS的复杂专有移动应用程序测量的新用户，使用强度，使用频率，异常以及发布日期和持续时间。利用贝叶斯网络和随机森林模型来解释相互关系，并得出独立的释放质量度量。调查了各种代码复杂性度量，用法（下载）以及520 NPM软件包的问题数量，并从这些分析中得出了与用法无关的质量度量，并将其应用于4430个流行的NPM软件包中，以构建时间表构建时间表，以比较这些质量（问题），并在这些质量上进行了质量，以确定这些质量的质量。发现软件使用的强度和频率与软件故障之间没有直接联系。以用户为单位表示的释放质量独立于其他与使用相关的预测变量，因此可以用作用法独立于软件质量的衡量标准。用法还影响了NPM的质量，即使考虑了其他代码复杂性措施，下载也与许多问题密切相关。结论：我们希望我们的结果和提议的质量措施将有助于更准确地释放软件的质量，并激发该领域的进一步研究。
Context:The extent of post-release use of software affects the number of faults, thus biasing quality metrics and adversely affecting associated decisions. The proprietary nature of usage data limited deeper exploration of this subject in the past. Objective: To determine how software faults and software use are related and how an accurate quality measure can be designed. Method: New users, usage intensity, usage frequency, exceptions, and release date and duration measured for complex proprietary mobile applications for Android and iOS. Utilized Bayesian Network and Random Forest models to explain the interrelationships and to derive the usage independent release quality measure. Investigated the interrelationship among various code complexity measures, usage (downloads), and number of issues for 520 NPM packages and derived a usage-independent quality measure from these analyses, applied it on 4430 popular NPM packages to construct timelines for comparing the perceived quality (issues) and our derived measure of quality for these packages.Results: We found the number of new users to be the primary factor determining the number of exceptions, and found no direct link between the intensity and frequency of software usage and software faults. Release quality expressed as crashes per user was independent of other usage-related predictors, thus serving as a usage independent measure of software quality. Usage also affected quality in NPM, where downloads were strongly associated with numbers of issues, even after taking the other code complexity measures into consideration. Conclusions: We expect our result and our proposed quality measure will help gauge release quality of a software more accurately and inspire further research in this area.
