Industrial comparability of student artifacts in traceability recovery research - An exploratory survey

Markus Borg, Krzysztof Wnuk, Dietmar Pfahl

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

7 Citations (SciVal)
112 Downloads (Pure)


Abstract in Undetermined
About a hundred studies on traceability recovery have been published in software engineering fora. In roughly half of them, software artifacts developed by students have been used as input. To what extent student artifacts differ from industrial counterparts has not been fully explored in the literature. We conducted a survey among authors of studies on traceability recovery, including both academics and practitioners, to explore their perspectives on the matter. Our results indicate that a majority of authors consider software artifacts originating from student projects to be only partly representative to industrial artifacts. Moreover, only few respondents validated student artifacts for industrial representativeness. Furthermore, our respondents made suggestions for improving the description of artifact sets used in studies by adding contextual, domain-specific and artifact-centric information. Example suggestions include adding descriptions of processes used for artifact development, meaning of traceability links, and the structure of artifacts. Our findings call for further research on characterization and validation of software artifacts to support aggregation of results from empirical studies.
Original languageEnglish
Title of host publication[Host publication title missing]
EditorsTom Mens, Anthony Cleve, Rudolf Ferenc
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages9
ISBN (Print)978-0-7695-4666-7
Publication statusPublished - 2012
Event16th European Conference on Software Maintenance and Reengineering - Szeged, Hungary
Duration: 2012 Mar 27 → …


Conference16th European Conference on Software Maintenance and Reengineering
Period2012/03/27 → …

Subject classification (UKÄ)

  • Computer Science


  • empirical study
  • software artifacts
  • traceability
  • survey


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