A comparison of pair versus solo programming under different objectives: An analytical approach
成果类型:
Article
署名作者:
Dawande, Milind; Johar, Monica; Kumar, Subodha; Mookerjee, Vijay S.
署名单位:
University of Texas System; University of Texas Dallas; University of North Carolina; University of North Carolina Charlotte; University of Washington; University of Washington Seattle; University of Texas System; University of Texas Dallas
刊物名称:
INFORMATION SYSTEMS RESEARCH
ISSN/ISSBN:
1047-7047
DOI:
10.1287/isre.1070.0147
发表日期:
2008
页码:
71-92
关键词:
genetic algorithm
摘要:
This study compares the performances of pair development (an approach in which a pair of developers jointly work on the same piece of code), solo development, and mixed development under two separate objectives: effort minimization and time minimization. To this end, we develop analytical models to optimize module-developer assignments in each of these approaches. These models are shown to be strongly NP-hard and solved using a genetic algorithm. The solo and pair development approaches are compared for a variety of problem instances to highlight project characteristics that favor one of the two practices. We also propose a simple criterion that can reliably recommend the appropriate approach for a given problem instance. Typically, for efficient knowledge sharing between developers or for highly connected systems, the pair programming approach is preferable. Also, the pair approach is better at leveraging expertise by pairing experts with less skilled partners. Solo programming is usually desirable if the system is large or the effort needed either to form a pair or to code efficiently in pairs is high. Solo programming is also appropriate for projects with a tight deadline, whereas the reverse is true for projects with a lenient deadline. The mixed approach (i.e., an approach where both the solo and pair practices are used in the same project) is only indicated when the system consists of groups of modules that are sufficiently different from one another.
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