dataset · IEEE DataPort · 2019

Code Review Support - A Systematic Mapping Data

Gunawardena, Sanuri

Cited by 0Open access

Abstract

Code review is a widely used quality assurance technique. From the heavy-weight and manual process that it was first introduced as code review has evolved into a more light-weight and tool-assisted process overtime to support modern software development that demands frequent delivery of source code. A large body of research on code review support exists. To help to understand the state of nature, quality, and evaluation of existing code review support, we conducted a systematic mapping study, a form of systematic literature review (SLR). We examined 5 major academic databases for evidence on existing support. We found 334 relevant articles on code review support. The results revealed that even though performing code review using existing forms of support is capable of fulfilling the expectations of reviewers, they possess many challenges and inadequacies revealing improvement opportunities. We report those challenges and inadequacies. Additionally, based on the nature of support and their evaluation, we discuss 6 major observations and future research directions.

Cite this paper

APA 7

Gunawardena, S. (2019). Code Review Support - A Systematic Mapping Data. IEEE DataPort. https://doi.org/10.21227/4re5-v827

MLA 9

Gunawardena, Sanuri. “Code Review Support - A Systematic Mapping Data.” IEEE DataPort, 2019, https://doi.org/10.21227/4re5-v827.

Chicago

Gunawardena, Sanuri. 2019. “Code Review Support - A Systematic Mapping Data.” IEEE DataPort. https://doi.org/10.21227/4re5-v827.

Harvard

Gunawardena, S. (2019) ‘Code Review Support - A Systematic Mapping Data’, IEEE DataPort. Available at: https://doi.org/10.21227/4re5-v827.

BibTeX

@misc{gunawardena2019code,
  title = {{Code Review Support - A Systematic Mapping Data}},
  author = {Gunawardena, Sanuri},
  journal = {IEEE DataPort},
  year = {2019},
  doi = {10.21227/4re5-v827}
}

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