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A Comparison of Pair Versus Solo Programming Under Different Objectives: An Analytical Approach

机译:对与不同目标下的单人编程的比较:一种分析方法

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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.
机译:这项研究比较了配对开发(一对开发人员在同一段代码上共同工作的一种方法),单独开发和混合开发在两个单独目标下的性能:工作量最小化和时间最小化。为此,我们开发了分析模型来优化每种方法中的模块开发人员分配。这些模型显示出很强的NP难度,并使用遗传算法求解。比较了各种问题实例的单人开发和结对开发方法,以突出支持两种实践之一的项目特征。我们还提出了一个简单的标准,可以针对给定的问题实例可靠地推荐适当的方法。通常,为了在开发人员之间或对于高度连接的系统之间进行有效的知识共享,配对编程方法是首选。此外,结对方式更适合通过将专家与技能水平较低的合作伙伴配对来利用专业知识。如果系统很大或者成对或高效成对编码所需的工作量很大,则通常需要进行单人编程。单独编程也适用于期限紧迫的项目,反之亦然适用于期限紧迫的项目。仅当系统由彼此足够不同的模块组组成时,才指示混合方法(即,在同一项目中同时使用单独练习和配对练习的方法)。

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