We present an approach to program repair and its application to programs with recursive functions over unbounded data types. Our approach formulates program repair in the framework of deductive synthesis that uses existing program structure as a hint to guide synthesis. We introduce a new specification construct for symbolic tests. We rely on such user-specified tests as well as automatically generated ones to localize the fault and speed up synthesis. Our implementation is able to eliminate errors within seconds from a variety of functional programs, including symbolic computation code and implementations of functional data structures. The resulting programs are formally verified by the Leon system.

We report our progress in scaling deductive synthesis and repair of recursive functional Scala programs in the Leon tool. We describe new techniques, including a more precise mechanism for encoding the space of meaningful candidate programs. Our techniques increase the scope of synthesis by expanding the space of programs we can synthesize and by reducing the synthesis time in many cases. As a new example, we present a run-length encoding function for a list of values, which Leon can now automatically synthesize from specification consisting of the decoding function and the local minimality property of the encoded value.Comment: In Proceedings SYNT 2016, arXiv:1611.0717

Program synthesis and repair have emerged as an exciting area of research, driven by the potential for revolutionary advances in programmer productivity. Among most promising ideas emerging for synthesis are syntax-driven search, probabilistic models of code, and the use of input-output examples. Our paper shows how to combine these techniques and use them for program repair, which is among the most relevant applications of synthesis to general-purpose code. Our approach combines semantic specifications, in the form of pre-and post-conditions and input-output examples with syntactic specifications in the form of term grammars and AST-level statistics extracted from code corpora. We show that synthesis in this framework can be viewed as an instance of graph search, permitting the use of well-understood families of techniques such as A*. We implement our algorithm in a framework for verification, synthesis and repair of functional programs, demonstrating that our approach can repair programs that are beyond the reach of previous tools.

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