用博弈论探讨自组织软件团队的效率

Clay Stevens, Jared Soundy, Hau Chan
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引用次数: 2

摘要

在过去的二十年里,软件开发已经从集中的、基于计划的管理转向敏捷方法,比如Scrum。敏捷方法建立在一组共享的核心原则之上,包括自组织的软件开发团队。这样的团队被认为是提高开发人员生产力和团队士气的一种方式,这与学术研究相呼应。然而,最近关于敏捷的工作忽略了考虑开发人员之间的战略行为,特别是在任务分配期间——这是自组织团队的主要功能之一。本文认为,可以很容易地使用博弈论对自组织软件团队进行建模,从而深入了解敏捷开发人员在执行策略时可能采取的行动。为了支持我们的论点,我们提出了一个基于和扩展从既定博弈论研究中得出的概念的自我分配开发任务的一般模型。我们进一步向软件工程社区介绍了从博弈论中得出的两个指标——稳定价格和无政府价格——它们可以用来衡量自组织团队与集中式管理相比的效率。我们演示了如何在一个案例研究中使用这些度量标准,以评估小型团队比大型团队更有效地自我组织的假设,并为该假设提供条件支持。我们的博弈论框架为软件工程界提供了新的视角,为未来的研究开辟了许多途径。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Exploring the Efficiency of Self-Organizing Software Teams with Game Theory
Over the last two decades, software development has moved away from centralized, plan-based management toward agile methodologies such as Scrum. Agile methodologies are founded on a shared set of core principles, including self-organizing software development teams. Such teams are promoted as a way to increase both developer productivity and team morale, which is echoed by academic research. However, recent works on agile neglect to consider strategic behavior among developers, particularly during task assignment–one of the primary functions of a self-organizing team. This paper argues that self-organizing software teams could be readily modeled using game theory, providing insight into how agile developers may act when behaving strategically. We support our argument by presenting a general model for self-assignment of development tasks based on and extending concepts drawn from established game theory research. We further introduce the software engineering community to two metrics drawn from game theory—the price-of-stability and price-of-anarchy—which can be used to gauge the efficiencies of self-organizing teams compared to centralized management. We demonstrate how these metrics can be used in a case study evaluating the hypothesis that smaller teams self-organize more efficiently than larger teams, with conditional support for that hypothesis. Our game-theoretic framework provides new perspective for the software engineering community, opening many avenues for future research.
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