Abstract-Exposing inconsistencies can uncover many defects in software specifications. One approach to exposing inconsistencies analyzes two redundant specifications, one operational and the other property-based, and reports discrepancies. This paper describes a "practical" formal method, based on this approach and the SCR (Software Cost Reduction) tabular notation, that can expose inconsistencies in software requirements specifications. Because users of the method do not need advanced mathematical training or theorem proving skills, most software developers should be able to apply the method without extraordinary effort. This paper also describes an application of the method which exposed a safety violation in the contractor-produced software requirements specification of a sizable, safety-critical control system. Because the enormous state space of specifications of practical software usually renders direct analysis impractical, a common approach is to apply abstraction to the specification. To reduce the state space of the control system specification, two "pushbutton" abstraction methods were applied, one which automatically removes irrelevant variables and a second which replaces the large, possibly infinite, type sets of certain variables with smaller type sets. Analyzing the reduced specification with the model checker Spin uncovered a possible safety violation. Simulation demonstrated that the safety violation was not spurious but an actual defect in the original specification.

Abstract. A controversial issue in the formal methods community is the degree to which mathematical sophistication and theorem proving skills should be needed to apply a formal method and its support tools. This paper describes the SCR (Software Cost Reduction) tools, part of a "practical" formal method--a method with a solid mathematical foundation that software developers can apply without theorem proving skills, knowledge of temporal and higher order logics, or consultation with formal methods experts. The SCR method provides a tabular notation for specifying requirements and a set of "light-weight" tools that detect several classes of errors automatically. The method also provides support for more "heavy-duty" tools, such as a model checker. To make model checking feasible, users can automatically apply one or more abstraction methods.

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Salsa is an invariant checker for specifications in SAL (the SCR Abstract Language). To establish a formula as an invariant without any user guidance, Salsa carries out an induction proof that utilizes tightly integrated decision procedures, currently a combination of BDD algorithms and a constraint solver for integer linear arithmetic, for discharging the verification conditions. The user interface of Salsa is designed to mimic the interfaces of model checkers; i.e., given a formula and a system description, Salsa either establishes the formula as an invariant of the system (but returns no proof) or provides a counterexample. In either case, the algorithm will terminate. Unlike model checkers, Salsa returns a state pair as a counterexample and not an execution sequence. Also, due to the incompleteness of induction, users must validate the counterexamples. The use of induction enables Salsa to combat the state explosion problem that plagues model checkers -it can handle specifications whose state spaces are too large for model checkers to analyze. Also, unlike general purpose theorem provers, Salsa concentrates on a single task and gains efficiency by employing a set of optimized heuristics.