Double blind reviews in software engineering venues: Practicability, promises and perils
- Published
- Accepted
- Subject Areas
- Data Mining and Machine Learning, Data Science, Software Engineering
- Keywords
- Double Blind Reviewing, Single Blind Reviewing, ICSE, Reviewing, Peer Review
- Copyright
- © 2016 Beller et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
- Cite this article
- 2016. Double blind reviews in software engineering venues: Practicability, promises and perils. PeerJ PrePrints 4:e1757v1 https://doi.org/10.7287/peerj.preprints.1757v1
Abstract
The peer review process is central to the scientific method, the advancement and spread of research as well as crucial for individual careers. However, the single blind review process currently used in most Software Engineering (SE) venues is susceptible towards apparent and hidden biases, since reviewers know the identity of authors. In this paper, we perform a study on the benefits and costs that are associated with introducing double-blind reviews in SE venues. We surveyed the SE community’s opinion, interviewed experts on double-blind reviewing, and estimated the likelihood of reviewers being able to guess the authors. Our results indicate that double-blind reviewing could be introduced in large SE conferences at lower-than-generally believed costs and that the majority of the SE community is in favor of introducing it.
Author Comment
This pre-print is a fluid publication. We continue updating and improving it as we receive the community’s feedback.