Statistical Foundations for Fault Detection

Software engineers have been asking themselves the same question for nearly a century: What parts of our code are likely to break? Having the answer to this question is no longer optional—it's becoming increasingly imperative due to DevSecOps' emphasis on speed, automation, and security. Today's complex software systems rely on a wide variety of components, including cloud-based services, mobile apps, web portals, IoT devices, and much more. Because of this, a single flaw or error in one component could potentially impact thousands of other components or even entire systems. Furthermore, the cost associated with identifying and repairing errors late in the development cycle is significantly greater than the cost of addressing them early. As a result, the primary objective of software engineers is to find faults before they cause problems. To accomplish this goal, software engineers utilize a variety of statistical methodologies that enable them to measure and evaluate the quality of their source code.