Duration Estimation Models for Open Source Software Projects

Donatien Koulla Moulla, A. Abran, Kolyang
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引用次数: 4

Abstract

For software organizations that rely on Open Source Software (OSS) to develop customer solutions and products, it is essential to accurately estimate how long it will take to deliver the expected functionalities. While OSS is supported by government policies around the world, most of the research on software project estimation has focused on conventional projects with commercial licenses. OSS effort estimation is challenging since OSS participants do not record effort data in OSS repositories. However, OSS data repositories contain dates of the participants’ contributions and these can be used for duration estimation. This study analyses historical data on WordPress and Swift projects to estimate OSS project duration using either commits or lines of code (LOC) as the independent variable. This study proposes first an improved classification of contributors based on the number of active days for each contributor in the development period of a release. For the WordPress and Swift OSS projects environments the results indicate that duration estimation models using the number of commits as the independent variable perform better than those using LOC. The estimation model for full-time contributors gives an estimate of the total duration, while the models with part-time and occasional contributors lead to better estimates of projects duration with both for the commits data and the lines of data.
开源软件项目的持续时间估计模型
对于依赖于开源软件(OSS)来开发客户解决方案和产品的软件组织来说,准确地估计交付预期功能所需的时间是至关重要的。虽然OSS得到了世界各地政府政策的支持,但大多数关于软件项目评估的研究都集中在具有商业许可的传统项目上。由于OSS参与者没有在OSS存储库中记录工作数据,因此OSS工作量估计是具有挑战性的。然而,OSS数据存储库包含参与者贡献的日期,这些可以用于持续时间估计。本研究分析了WordPress和Swift项目的历史数据,以提交或代码行(LOC)作为自变量来估计OSS项目的持续时间。这项研究首先提出了一个改进的基于每个贡献者在一个版本的开发期间的活跃天数的贡献者分类。对于WordPress和Swift OSS项目环境,结果表明,使用提交次数作为自变量的持续时间估计模型比使用LOC的持续时间估计模型性能更好。全职贡献者的估计模型给出了总持续时间的估计,而兼职和偶尔贡献者的模型可以更好地估计项目持续时间,包括提交数据和数据行。
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