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Fostering Real-Time Software Analysis by Leveraging Heterogeneous and Autonomous Software Repositories

机译:通过利用异构和自治软件存储库促进实时软件分析

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Mining software repositories allow software practitioners to improve the quality of software systems and to support maintenance based on historical data. Such data is scattered across autonomous and heterogeneous information sources, such as version control, bug tracking and build automation systems. Despite having many tools to track and measure the data originated from such repositories, software practitioners often suffer from a scarcity of the techniques necessary to dynamically leverage software repositories to fulfill their complex information needs. For example, answering a question such as “What is the number of commits between two successful builds?” requires tiresome manual inspection of multiple repositories. As a solution, this paper presents a conceptual framework and a proof of concept visual query interface to satisfy distinct software quality related information needs of software practitioners. The data originated from repositories is integrated and analyzed to perform systematic investigations, which helps to uncover hidden relationships between software quality and trends of software evolution. This approach has several significant benefits such as the ability to perform real-time analyses, the ability to combine data from various software repositories and generate queries dynamically. The framework evaluated with 31 subjects by using a series of questions categorized into three software evolution scenarios. The evaluation results evidently show that our framework surpasses the state of the art tools in terms of correctness, time and usability.
机译:挖掘软件存储库使软件从业人员可以提高软件系统的质量,并根据历史数据支持维护。这样的数据散布在自治和异构信息源之间,例如版本控制,错误跟踪和构建自动化系统。尽管有许多工具可以跟踪和测量源自此类存储库的数据,但是软件从业人员经常会遭受缺乏动态利用软件存储库来满足其复杂信息需求所必需的技术的困扰。例如,回答诸如“两次成功构建之间的提交次数是多少?”之类的问题。需要对多个存储库进行繁琐的手动检查。作为解决方案,本文提出了一种概念框架和概念证明视觉查询界面,以满足软件从业人员与软件质量相关的独特信息需求。对来自存储库的数据进行集成和分析,以进行系统的调查,这有助于发现软件质量与软件发展趋势之间的隐藏关系。这种方法具有许多显着的好处,例如执行实时分析的能力,组合来自各种软件存储库的数据并动态生成查询的能力。该框架通过使用一系列分为三个软件演进方案的问题,对31个主题进行了评估。评估结果显然表明,我们的框架在准确性,时间和可用性方面都超过了最先进的工具。

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