A software project dynamics model for process cost, schedule and risk assessment
Behrokh Khoshnevis, Raymond J. Madachy · 1994
A dynamic model of an inspection-based software lifecycle process has been developed to support quantitative evaluation of the process. In conjunction with a knowledge-based method that has been developed for cost estimation and project risk assessment, these modeling techniques can support project planning and management, and aid in process improvement. The model serves to examine the effects of inspection practices on cost, schedule and quality throughout the lifecycle. It uses system dynamics to model the interrelated flows of tasks, errors and personnel throughout different development phases and is calibrated to industrial data. It extends previous software project dynamics research by examining an inspection-based process with an original model, integrating it with the knowledge-based method for risk assessment and cost estimation, and using an alternative modeling platform. While specific enough to investigate inspection practices, it is sufficiently general to incorporate changes for other phenomena. It demonstrates the effects of performing inspections, the effectiveness of varied inspection policies, and the effects of other managerial policies such as manpower allocation. The dynamic effects are tracked throughout the time history of a project to show resource usage, task completions and defect trends per phase. Cumulative metrics and development tradeoffs for decision making are also presented. The knowledge-based method has been implemented on multiple platforms. As an extension to COCOMO, it aids in project planning by identifying, categorizing, quantifying and prioritizing project risks. It also detects cost estimate input anomalies and provides risk control advice in addition to conventional cost and schedule calculation. It extends previous work by focusing on risk assessment, incorporating substantially more rules, going beyond standard COCOMO, performing quantitative validation, and providing a user-friendly interface. The method is being used and enhanced in industrial environments as part of an integrated capability to assist in system acquisition, project planning and risk management. Several types of validation tests are performed against industrial data, existing theory and other prediction models, and practitioners are used to evaluate the model. The results indicate a valid model that can be used for process evaluation and project planning, and serve as a framework for incorporating other dynamic process factors.