We present an approach to learn contracts for object-oriented programs where guarantees of correctness of the contracts are made with respect to a test generator. Our contract synthesis approach is based on a novel notion of tight contracts and an online learning algorithm that works in tandem with a test generator to synthesize tight contracts. We implement our approach in a tool called Precis and evaluate it on a suite of programs written in C#, studying the safety and strength of the synthesized contracts, and compare them to those synthesized by Daikon.
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Bierre, Amin ; Parker, David (Ed.)
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We identify a decidable synthesis problem for a class of pro- grams of unbounded size with conditionals and iteration that work over infinite data domains. The programs in our class use uninterpreted functions and relations, and abide by a restriction called coherence that was recently identified to yield decidable verification. We formulate a powerful grammar-restricted (syntax-guided) synthesis problem for coherent uninterpreted programs, and we show the problem to be decidable, identify its precise complexity, and also study several variants of the problem.more » « less
