Temporal Verification with Transition Invariants

Program verification increases the degree of confidence that a program will perform correctly. Manual verification is an error-prone and tedious task. Its automation is highly desirable. The verification methodology reduces the reasoning about temporal properties of program computations to testing the validity of implication between auxiliary first-order assertions. The synthesis of such auxiliary assertions is the main challenge for automated tools. There already exist successful tools for the verification of safety properties. These properties require that some �bad� states never appear during program computations. The tools construct invariants, which are auxiliary assertions for safety. Invariants are computed symbolically by applying techniques of abstract interpretation. Liveness properties require that some �good� states will eventually appear in every computation. The synthesis of auxiliary assertions for the verification of liveness properties is the next challenge for automated verification tools. This dissertation argues that transition invariants can provide a new basis for the development of automated methods for the verification of liveness properties. We support this thesis as follows. We introduce a new notion of auxiliary assertions called transition invariant. We apply this notion to propose a proof rule for the verification of liveness properties. We provide a viable approach for the automated synthesis of transition invariants by abstract interpretation, which automates the proof rule. For this purpose, we introduce a transition predicate abstraction. This abstraction does not have an inherent limitation to preserve only safety properties. Most liveness properties of concurrent programs only hold under certain assumptions on non-deterministic choices made during program executions. These assumptions are known as fairness requirements. A direct treatment of fairness requirements in a proof rule is desirable. We specialize our proof rule for the direct accounting of two common ways of specifying fairness. Fairness requirements can be imposed either on program transitions or on sets of programs states. We treat both cases via abstract-transition programs and labeled transition invariants respectively. We have developed a basis for the construction of automated tools that can not only prove that a program never does anything bad, but can also prove that the program eventually does something good. Such proofs increase our confidence that the program will perform correctly