Developer Interaction Traces backed by IDE Screen Recordings from Think-aloud Sessions. Yamashita, A., Petrillo, F., Khomh, F., & Gu�h�neuc, Y. May, 2018. Data showcase at the 15th International Conference on Mining Software Repositories. 4 pages.
Developer Interaction Traces backed by IDE Screen Recordings from Think-aloud Sessions [pdf]Paper  abstract   bibtex   
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.
@MISC{Yamashita18-Demo-MSR,
   AUTHOR       = {Aiko Yamashita and F�bio Petrillo and Foutse Khomh and 
      Yann-Ga�l Gu�h�neuc},
   OPTHOWPUBLISHED = {},
   MONTH        = {May},
   NOTE         = {Data showcase at the 15<sup>th</sup> International Conference on Mining Software Repositories. 4 pages.},
   TITLE        = {Developer Interaction Traces backed by IDE Screen 
      Recordings from Think-aloud Sessions},
   YEAR         = {2018},
   KEYWORDS     = {Understanding program comprehension, MSR},
   URL          = {http://www.ptidej.net/publications/documents/MSR18DataShowcase.doc.pdf},
   PDF          = {http://www.ptidej.net/publications/documents/MSR18DataShowcase.ppt.pdf},
   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.}
}
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