A distributed problem-solving framework for probabilistic software effort estimation

作     者：Pendharkar, Parag C. Rodger, James A. 

作者机构：Penn State Harrisburg Sch Business Adm Informat Syst Middletown PA 17057 USA Indiana Univ Penn Eberly Coll Business & Informat Technol Indiana PA 15705 USA 

出 版 物：《EXPERT SYSTEMS》 (专家系统；国际知识工程杂志)

年 卷 期：2012年第29卷第5期

页      面：492-505页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：distributed problem solving software effort estimation probabilistic reasoning 

摘      要：Distributed problem-solving (DPS) systems use a framework of human organizational notions and principles of intelligent systems to solve complex problems. Human organizational notions are used to decompose a complex problem into sub-problems that can be solved using intelligent systems. The solutions of these sub-problems are combined to solve the original complex problem. In this paper, we propose a DPS system for probabilistic estimation of software development effort. Using a real-world software engineering dataset, we compare the performance of the DPS system with a neural network (NN) and show that the performance of the DPS system is equal to or better than that of the NN with the additional benefits of modularity, probabilistic estimates, greater interpretability, flexibility and capability to handle incomplete input data.