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

A. Yamashita, Fábio Petrillo, Foutse Khomh, Yann-Gaël Guéhéneuc
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引用次数: 7

Abstract

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.
开发者互动的痕迹由IDE屏幕录音从思考出声会议
测试和解释挖掘开发人员交互痕迹的方法有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来提供可靠的结果;其次,缺乏“基本事实”或经验证据,可用于三角测量结果,或验证其准确性和正确性。此外,仅仅依靠相互作用的痕迹限制了我们考虑环境因素的能力,这些因素会影响挖掘技术在其他环境中的适用性,也阻碍了我们充分理解观察到的现象背后的机制的能力。本文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多个小时的视频记录了IDE屏幕和开发人员的评论。该数据集与研究程序理解感兴趣的研究人员以及正在开发交互跟踪分析和挖掘技术的研究人员相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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