Software used in safety-critical systems--such as automotive, avionics, and healthcare applications, where failures could result in serious harm or loss of life--must perform as prescribed. How can software developers and programmers offer assurance that the system will perform as needed and with what level of confidence? In the first post in this series, I introduced the concept of the assurance case as a means to justify safety, security, or reliability claims by relating evidence to the claim via an argument. In this post I will discuss Baconian probability and eliminative induction, which are concepts we use to explore properties of confidence that the assurance case adequately justifies its claim about the subject system.
From the braking system in your automobile to the software that controls the aircraft that you fly in, safety-critical systems are ubiquitous. Showing that such systems meet their safety requirements has become a critical area of work for software and systems engineers. "We live in a world in which our safety depends on software-intensive systems," editors of IEEE Software wrote in the magazine's May/June issue. "Organizations everywhere are struggling to find cost-effective methods to deal with the enormous increase in size and complexity of these systems, while simultaneously respecting the need to ensure their safety." The Carnegie Mellon Software Engineering Institute (SEI) is addressing this issue with a significant research program into assurance cases. Our sponsors are regularly faced with assuring that complex software-based systems meet certain kinds of requirements such as safety, security, and reliability. In this post, the first in a series on assurance cases and confidence, I will introduce the concept of assurance cases and show how they can be used to argue that a safety requirement (or other requirement such as security) has been met.