Deductive Evaluation: Formal Code Analysis With Low User Burden

We describe a framework for symbolically evaluating iterative C code using a deductive approach that automatically discovers and proves program properties. Although verification is not performed, the method can infer detailed program behavior. Software engineering work flows could be enhanced by this type of analysis. Floyd-Hoare verification principles are applied to synthesize loop invariants, using a library of iteration-specific deductive knowledge. When needed, theorem proving is interleaved with evaluation and performed on the fly. Evaluation results take the form of inferred expressions and type constraints for values of program variables. An implementation using PVS (Prototype Verification System) is presented along with results for sample C functions

Deductive Evaluation: Implicit Code Verification With Low User Burden

We describe a framework for symbolically evaluating C code using a deductive approach that discovers and proves program properties. The framework applies Floyd-Hoare verification principles in its treatment of loops, with a library of iteration schemes serving to derive loop invariants. During evaluation, theorem proving is performed on-the-fly, obviating the generation of verification conditions normally needed to establish loop properties. A PVS-based prototype is presented along with results for sample C functions

Predicate Generation for Learning-Based Quantifier-Free Loop Invariant Inference

We address the predicate generation problem in the context of loop invariant inference. Motivated by the interpolation-based abstraction refinement technique, we apply the interpolation theorem to synthesize predicates implicitly implied by program texts. Our technique is able to improve the effectiveness and efficiency of the learning-based loop invariant inference algorithm in [14]. We report experiment results of examples from Linux, SPEC2000, and Tar utility