在敏捷过程中为工作量估算实现体验工厂

D. Taibi, Valentina Lenarduzzi, Philipp Diebold, M. I. Lunesu
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引用次数: 14

摘要

【背景】在敏捷过程中,系统地收集历史数据所需的工作并不总是可分配的,历史数据管理通常委托给开发人员的经验,他们需要记住以前的项目细节。然而,即使训练有素,开发人员也不能准确地记住大量的细节,从而导致在开发过程中做出错误的决定。[目的]本文的目标是以敏捷的方式实现体验工厂的运营,即定义一种使用敏捷方法收集历史项目数据的策略。[方法]我们提供了一种机制来理解是否必须收集一个措施,基于投资时间回报率(ROIT)。为了验证这种方法,我们用一个探索性的案例研究实例化了工厂,将四个没有使用我们方法的项目与一个在37周后使用了我们方法的项目和两个从一开始就使用我们方法的项目进行了比较。[结果]所提出的方法可以帮助开发人员不断提高他们的估计精度,并且所收集的度量具有非常积极的ROIT。【结论】从这第一个经验中,我们可以得出这样的结论:体验工厂可以有效地应用于敏捷过程,支持开发人员提高他们的性能,减少潜在的决策错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Operationalizing the Experience Factory for Effort Estimation in Agile Processes
[Background] The effort required to systematically collect historical data is not always allocable in agile processes and historical data management is usually delegated to the developers' experience, who need to remember previous project details. However, even if well trained, developers cannot precisely remember a huge number of details, resulting in wrong decisions being made during the development process. [Aims] The goal of this paper is to operationalize the Experience Factory in an agile way, i.e., defining a strategy for collecting historical project data using an agile approach. [Method] We provide a mechanism for understanding whether a measure must be collected or not, based on the Return on Invested Time (ROIT). In order to validate this approach, we instantiated the factory with an exploratory case study, comparing four projects that did not use our approach with one project that used it after 12 weeks out of 37 and two projects that used it from the beginning. [Results] The proposed approach helps developers to constantly improve their estimation accuracy with a very positive ROIT of the collected measure. [Conclusions] From this first experience, we can conclude that the Experience Factory can be applied effectively to agile processes, supporting developers in improving their performance and reducing potential decision mistakes.
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