Planning and Scheduling of Software Manufacturing Projects

Abstract

In today's highly competitive and constantly growing market for software products, planning and scheduling of large software projects has become a bottleneck to increasing production productivity. This work is to investigate the mechanisms required to support software project planning and scheduling (SPPS). Our approach is to (1) define SPPS as a reactive process that involves human negotiation, and (2) develop a heuristic search model, that is consistent with the negotiation process, to improve an existing schedule by incrementally revising it. The main contribution of this thesis is that it represents the first major effort in building a problem solving model for SPPS that accommodates the dominant characteristics of SPPS. Our problem solving model is based on the previous results in social analysis of computing, operations research in manufacturing, artificial intelligence in manufacturing planning and scheduling, and the traditional approaches to planning in artificial intelligence, and extends the techniques that have been developed by them in dealing with SPPS. We demonstrate the sufficiency of the model that has been developed on specific test cases that reflect actual software project planning and scheduling circumstances. A program called NEGOPRO that uses our basic model to support SPPS in large software projects has been implemented.