The aDoctor Project

Code smells are symptoms of poor design solutions applied by programmers during the development of software systems. While the research community devoted a lot of effort in studying and devising approaches for detecting the traditional code smells defined by Fowler, a little knowledge and support is available for an emerging category of Mobile app code smells. Specifically, Reimann et al. recently proposed a new catalogue of Android-specific code smells that may threat the maintainability and the efficiency of Android applications. Existing tools working in the context of Mobile apps provide limited support and, more importantly, are not available for developers interested in monitoring the quality of their apps. To overcome these limitations, we propose a fully automated tool, coined as aDoctor , able to identify 15 Android-specific code smells from the catalogue by Reimann et al. An empirical study conducted on the source code of 18 Android applications reveal that the proposed tool is highly performant and reaches, on average, 98% of precision and 98% of recall. We made aDoctor publicly available.代码坏味（code smells）是程序员在软件开发过程中采用劣质设计方案的征兆。尽管学界已投入大量精力研究并设计用于检测Fowler所定义的传统代码坏味的方法，但针对新兴的移动应用代码坏味类别，相关研究成果与工具支持却寥寥无几。具体而言，Reimann等人近期提出了一套全新的Android专属代码坏味目录，这类坏味可能会损害Android应用的可维护性与运行效率。当前面向移动应用的现有工具仅能提供有限的支持，更关键的是，对于希望监控自身应用质量的开发者而言，这类工具大多无法直接获取使用。为克服上述局限，本文提出一款全自动化工具，命名为aDoctor，该工具可识别Reimann等人所提目录中的15种Android专属代码坏味。针对18款Android应用的源代码开展的实证研究表明，所提工具性能优异，平均精确率与召回率均达到98%。我们已将aDoctor工具对外公开。