A Formal Notion of Program-Based Test Data Adequacy : October, 1982 (Classic Reprint)

A formal framework for evaluating how well test data reveals a program’s true behavior, and for designing better tests.

Measuring Test Data Adequacy presents a rigorous approach to judging whether a set of tests can distinguish a program from other possible programs. It introduces size-based and mutation-based ideas, explains critical points in testing, and shows how to balance boundary, central, and corner cases in test design. The work blends theory with practical guidance for building effective test suites that reflect real-world programming challenges.

• Definition of size-adequacy and how test data can differentiate programs by their size and structure
• Introduction of mutation analysis as an approximation to ideal adequacy
• Concepts of critical points and how boundary values influence test coverage
• Results linking adequacy to branch coverage and other established testing practices

Ideal for readers who want a formal, component-based view of testing and a framework they can apply when assessing or building test suites.