基于环境证据的软件工作量估计
Circumstantial-Evidence-Based Judgment for Software Effort Estimation
摘要：
软件工作量估算的专家判断是通过专家的经验，针对类似项目或活动的实际工作量的直接证据。然而，直接证据的可用性意味着需要合适的专家和过去的数据。本文提出的基于环境证据的判断方法，注重人类知识中积累的开发经验，通过理性推理，可以对新项目不同方案的实施努力进行定性评估。为了演示基于环境证据的判断过程，本文采用基于命题学习理论的诊断推理方法，在不同技术和环境下实现Web服务组合项目时，对不同的工作量估计进行了推断和比较。范例表明，我们提出的工作可以帮助确定项目实施前的努力权衡。总的来说，基于环境证据的判断不是专家判断的替代品，而是对专家判断的补充，以促进和改善软件工作量估计。
英文摘要：
Expert judgment for software effort estimation is oriented toward direct evidences that refer to actual effort of similar projects or activities through experts' experiences. However, the availability of direct evidences implies the requirement of suitable experts together with past data. The circumstantial-evidence-based judgment proposed in this paper focuses on the development experiences deposited in human knowledge, and can then be used to qualitatively estimate implementation effort of different proposals of a new project by rational inference. To demonstrate the process of circumstantial-evidence-based judgment, this paper adopts propositional learning theory based diagnostic reasoning to infer and compare different effort estimates when implementing a Web service composition project with some different techniques and contexts. The exemplar shows our proposed work can help determine effort tradeoff before project implementation. Overall, circumstantial-evidence-based judgment is not an alternative but complementary to expert judgment so as to facilitate and improve software effort estimation.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
