Quantifying Software Reliability At Earl

Problems which originate in early development stages can have a lasting influence on the reliability, safety, and cost of a software system. This book explores the use of a software measurement for early software faults detection and reliability prediction. The preselected software measurement, originally a black-box testing technique, was mathematically formalized to enhance its rigidity, repeatability and scalability, and further extended as an effective requirements faults detection tool. An automation-oriented algorithm was developed for quantifying the impact of the detected requirements faults on software reliability. The feasibility and scalability of the proposed methods were examined using real applications. To address the scalability of the proposed methods, a set of rules was proposed and experimentally evaluated. The methods proposed in this book allow software project stakeholders to effectively detect requirements faults and assess the quality of requirements early in development, and ultimately lead to improved software reliability. Software project practitioners, regulators, and policy makers involved in the certification of software systems can benefit most.