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Duration Estimation Models for Open Source Software Projects

机译:开源软件项目的持续时间估计模型

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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.
机译:对于依赖开源软件(OSS)开发客户解决方案和产品的软件组织,必须准确估计提供预期功能的时间。虽然OSS由世界各地政府政策支持,但大多数关于软件项目估算的研究都集中在商业许可证的传统项目上。由于OSS参与者在OSS存储库中没有记录了努力数据,因此OSS努力估算是具有挑战性的。但是,OSS数据存储库包含参与者贡献的日期,并且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,使用代码或代码行(LOC)作为独立变量来估计OSS项目持续时间。本研究提出了根据释放期间的每个贡献者的积极天数,提出了改进的贡献者分类。对于WordPress和Swift OSS项目环境,结果表明,使用Cumpits数量的持续时间估计模型比使用LOC的持续时间更好地执行。全日制贡献者的估计模型给出了总持续时间的估计,而具有兼职贡献者的模型会导致对提交数据和数据线的项目持续时间更好地估计。

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