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Developer Interaction Traces Backed by IDE Screen Recordings from Think Aloud Sessions

机译:通过大声思考会话的IDE屏幕录像支持的开发人员交互跟踪

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There are two well-known difficulties to test and interpret methodologies for mining developer interaction traces: first, the lack of enough large datasets needed by mining or machine learning approaches to provide reliable results; and second, the lack of 'ground truth' or empirical evidence that can be used to triangulate the results, or to verify their accuracy and correctness. Moreover, relying solely on interaction traces limits our ability to take into account contextual factors that can affect the applicability of mining techniques in other contexts, as well hinders our ability to fully understand the mechanics behind observed phenomena. The data presented in this paper attempts to alleviate these challenges by providing 600+ hours of developer interaction traces, from which 26+ hours are backed with video recordings of the IDE screen and developer's comments. This data set is relevant to researchers interested in investigating program comprehension, and those who are developing techniques for interaction traces analysis and mining.
机译:测试和解释挖掘开发人员交互踪迹的方法存在两个众所周知的困难:首先,缺乏挖掘或机器学习方法所需的足够大的数据集以提供可靠的结果;其次,缺乏可用于对结果进行三角化或验证其准确性和正确性的“地面真理”或经验证据。此外,仅依靠交互作用痕迹限制了我们考虑可能会影响采矿技术在其他情况下的适用性的上下文因素的能力,并且阻碍了我们充分理解所观察到的现象背后的机理的能力。本文中提供的数据试图通过提供600多个小时的开发人员交互跟踪来缓解这些挑战,其中26个小时以上的开发人员将获得IDE屏幕的视频记录和开发人员的评论。该数据集与有兴趣研究程序理解的研究人员以及正在开发交互轨迹分析和挖掘技术的研究人员有关。

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