Changes in software source codes are unavoidable and source code of software is repetitively modified to meet user’s huge requirements. Largely there are three types of code changes occur in the source code namely, bug repair, feature enhancement and addition of new features. The change due to bug fix, improvement and accumulation of new features brings uncertainties in the bug removal rate. In the present work, these uncertainties have been explicitly modeled and using three-dimensional wiener processes that define the three types of fluctuation; we have come up with an entropy prediction modelling framework. The analytical solution of the equation is interpreted using Itô’s process. The models are fitted on three real life projects namely Avro, Hive and Pig of Apache open source software. The experimental findings show that present models exhibit accurate estimation results and have strong prediction skills.

软件源代码的更改是不可避免的，并且软件源代码会不断修改以满足用户的巨大需求。在源代码中，大致有三种类型的代码更改，即错误修复，功能增强和新功能添加。由于错误修复，改进和新功能的积累而导致的更改带来了错误清除率的不确定性。在目前的工作中，已经明确地对这些不确定性进行了建模，并使用了定义三种波动类型的三维维纳过程。我们提出了一个熵预测建模框架。方程的解析解使用Itô过程进行解释。这些模型适合于三个现实生活项目，即Apache开源软件的Avro，Hive和Pig。