Integer linear programming for Constrained Multi-Aspect Committee Review Assignment

Karimzadehgan, Maryam; Zhai, ChengXiang

doi:10.1016/j.ipm.2011.09.004

Cited by 21 publications

(33 citation statements)

References 30 publications

(44 reference statements)

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“…The RAP becomes a pressing concern because of the increasing trend of peer review practices by many people such as conference organizers, journal editors and grant administrators [6]. Similarly, in the field of peer code review, the research on reviewer assignment is needed urgently since it plays the roles of both assuring program's quality and enhancing learning outcomes [20].…”

Section: Discussionmentioning

confidence: 99%

“…Integer linear programming is a very successful and popular method being used to solve the RAP [2,14,6]. Based on these work, we recommend a new approach to study the code reviewer assignment problem with integer linear programming.…”

Section: Methodsmentioning

confidence: 99%

“…Chen and Fan built up a model to measure the match degree between a reviewer's research domain knowledge with a proposal [1]. The match fitness between reviewers with assigned proposal (or paper manuscript) determines the review quality greatly [24] and the fact of having a good match helps improve the overall productivity [6]. Therefore, the review assignment problem is an important research topic [17].…”

Section: Introductionmentioning

confidence: 99%

“…Matching between reviewers' competence and review subjects such as research proposals and manuscripts significantly affects the review quality and productivity [24,6]. Despite the similarities between a paper review and a code review, it is not easy to investigate the similar phenomena in a code review because a code review often happens within a small software development team and the level of competence of a reviewer or an author is hard to measure.…”

Section: Introductionmentioning

confidence: 99%

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A code reviewer assignment model incorporating the competence differences and participant preferences

Wang

et al. 2016

Foundations of Computing and Decision Sciences

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Abstract.A good assignment of code reviewers can effectively utilize the intellectual resources, assure code quality and improve programmers' skills in software development. However, little research on reviewer assignment of code review has been found. In this study, a code reviewer assignment model is created based on participants' preference to reviewing assignment. With a constraint of the smallest size of a review group, the model is optimized to maximize review outcomes and avoid the negative impact of "mutual admiration society". This study shows that the reviewer assignment strategies incorporating either the reviewers' preferences or the authors' preferences get much improvement than a random assignment. The strategy incorporating authors' preference makes higher improvement than that incorporating reviewers' preference. However, when the reviewers' and authors' preference matrixes are merged, the improvement becomes moderate. The study indicates that the majority of the participants have a strong wish to work with reviewers and authors having highest competence. If we want to satisfy the preference of both reviewers and authors at the same time, the overall improvement of learning outcomes may be not the best.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A code reviewer assignment model incorporating the competence differences and participant preferences

Wang

et al. 2016

Foundations of Computing and Decision Sciences

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“…We show that our proposed method can improve the performance of expert matching in comparison with the state-of-the-art techniques for multi aspect/skill expert matching such as Greedy Next Best [2] and Integer linear programming [3].…”

Section: Coverage Condition) 4)mentioning

confidence: 93%

Multi-aspect group formation using facility location analysis

Neshati

Beigy

Hiemstra

2012

Proceedings of the Seventeenth Australasian Document Computing Symposium

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In this paper, we propose an optimization framework to retrieve an optimal group of experts to perform a given multi-aspect task/project. Each task needs a diverse set of skills and the group of assigned experts should be able to collectively cover all required aspects of the task. We consider three types of multiaspect team formation problems and propose a unified framework to solve these problems accurately and efficiently. Our proposed framework is based on Facility Location Analysis (FLA) which is a well known branch of the Operation Research (OR). Our experiments on a real dataset show significant improvement in comparison with the state-of-the art approaches for the team formation problem.

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