Analysis and Design of a Framework for Software Design Risk Prediction

This book presents an intelligent framework for identifying, predicting, prioritizing, and estimating software risks during the design phase of the Software Development Life Cycle (SDLC). Software design is exposed to diverse risks arising from requirements, architectural decisions, design activities, programming technologies, validation, and documentation, which can adversely affect software quality, cost, and delivery schedules.The book systematically examines the characteristics, sources, and causes of software design risks and investigates the relationships among identified risk factors. It presents a Bayesian Network-based Risk Prediction Model (RPM) for predicting potential risks, supported by risk trees and graphical analysis. A Fuzzy Inference System (FIS) is employed to prioritize risks according to their severity, detectability, and dependability. Furthermore, an Extreme Learning Machine (ELM)-based approach is presented for risk estimation and impact analysis. Sprache: Englisch Gewicht in Gramm: 358. …