开放数据驱动的静态代码分析可用性改进及其挑战

Emma Söderberg, Luke Church, Martin Höst
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引用次数: 0

摘要

背景:软件开发正朝着这样一个方向发展:为了改进实践,以系统的方式收集有关开发的数据,例如,在调整静态代码分析时。然而,到目前为止,这种类型的数据收集主要发生在组织内部,这是不幸的,因为它倾向于拥有更多资源来维护开发人员工具的大型组织。目标:多年来,我们看到了开源带来的很多好处,最近在开放数据方面也有了很大的发展。我们认为这是一个跨组织社区建设的机会,并想知道使用和共享开源软件开发人员工具的观点在多大程度上可以跨越到开放数据驱动的软件开发工具调优。方法:将11名参与者分为3个焦点组进行探索性研究,讨论静态代码分析器的使用和共享以及这些分析器的数据。结果:虽然使用和共享开源代码(在本例中是分析程序)作为现代软件开发实践的一部分被认为是积极的,但共享数据却受到怀疑和不确定性的影响。开发者关心的是对公司品牌的威胁、知识产权的暴露、法律责任,以及数据在多大程度上是特定组织的特定环境。结论:软件开发中的数据共享不同于软件开发中的数据共享。我们需要更好地理解我们如何能够以一种降低风险和开放的方式为软件开发数据的共享提供解决方案。
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Open Data-driven Usability Improvements of Static Code Analysis and its Challenges
Context: Software development is moving towards a place where data about development is gathered in a systematic fashion in order to improve the practice, for example, in tuning of static code analysis. However, this kind of data gathering has so far primarily happened within organizations, which is unfortunate as it tends to favor larger organizations with more resources for maintenance of developer tools. Objective: Over the years, we have seen a lot of benefits from open source and recently there has been a lot of development in open data. We see this as an opportunity for cross-organisation community building and wonder to what extent the views on using and sharing open source software developer tools carry across to open data-driven tuning of software development tools. Method: An exploratory study with 11 participants divided into 3 focus groups discussing using and sharing of static code analyzers and data about these analyzers. Results: While using and sharing open-source code (analyzers in this case) is perceived in a positive light as part of the practice of modern software development, sharing data is met with skepticism and uncertainty. Developers are concerned about threats to the company brand, exposure of intellectual property, legal liabilities, and to what extent data is context-specific to a certain organisation. Conclusions: Sharing data in software development is different from sharing data about software development. We need to better understand how we can provide solutions for sharing of software development data in a fashion that reduces risk and enables openness.
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