Supporting and accelerating reproducible empirical research in software evolution and maintenance using TraceLab Component Library

Bogdan Dit, Evan Moritz, Mario Linares-Vásquez, Denys Poshyvanyk, Jane Cleland-Huang

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Research studies in software maintenance are notoriously hard to reproduce due to lack of datasets, tools, implementation details (e.g., parameter values, environmental settings) and other factors. The progress in the field is hindered by the challenge of comparing new techniques against existing ones, as researchers have to devote a large portion of their resources to the tedious and error-prone process of reproducing previously introduced approaches. In this paper, we address the problem of experiment reproducibility in software maintenance and provide a long-term solution towards ensuring that future experiments will be reproducible and extensible. We conducted a preliminary mapping study of a number of representative maintenance techniques and approaches and implemented them as a set of experiments and a library of components that we make publicly available with TraceLab, called the Component Library. The goal of these experiments and components is to create a body of actionable knowledge that would (i) facilitate future research and (ii) allow the research community to contribute to it as well. In addition, to illustrate the process of using and adapting these techniques, we present an example of creating new techniques based on existing ones, in order to produce improved results.

Original languageEnglish
Pages (from-to)1198-1236
Number of pages39
JournalEmpirical Software Engineering
Volume20
Issue number5
DOIs
StatePublished - 4 Oct 2015

Keywords

  • Empirical case studies
  • Experiments
  • Reproducible
  • Software maintenance
  • TraceLab

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