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A key challenge in program synthesis is synthesizing programs that use libraries, which most real-world software does. The current state of the art is to model libraries with mock library implementations that perform the same function in a simpler way. However, mocks may still be large and complex, and must include many implementation details, both of which could limit synthesis performance. To address this problem, we introduce JLibSketch, a Java program synthesis tool that allows library behavior to be described with algebraic specifications, which are rewrite rules for sequences of method calls, e.g., encryption followed by decryption (with the same key) is the identity. JLibSketch implements rewrite rules by compiling JLibSketch problems into problems for the Sketch program synthesis tool. More specifically, after compilation, library calls are represented by abstract data types (ADTs), and rewrite rules manipulate those ADTs. We formalize compilation and prove it sound and complete if the rewrite rules are ordered and non-unifiable. We evaluated JLibSketch by using it to synthesize nine programs that use libraries from three domains: data structures, cryptography, and file systems. We found that algebraic specifications are, on average, about half the size of mocks. We also found that algebraic specifications perform better than mocks on seven of the nine programs, sometimes significantly so, and perform equally well on the last two programs. Thus, we believe that JLibSketch takes an important step toward synthesis of programs that use libraries.
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Deriving efficient program transformations from rewrite rules
An efficient optimizing compiler can perform many cascading rewrites in a single pass, using auxiliary data structures such as variable binding maps, delayed substitutions, and occurrence counts. Such optimizers often perform transformations according to relatively simple rewrite rules, but the subtle interactions between the data structures needed for efficiency make them tricky to write and trickier to prove correct. We present a system for semi-automatically deriving both an efficient program transformation and its correctness proof from a list of rewrite rules and specifications of the auxiliary data structures it requires. Dependent types ensure that the holes left behind by our system (for the user to fill in) are filled in correctly, allowing the user low-level control over the implementation without having to worry about getting it wrong. We implemented our system in Coq (though it could be implemented in other logics as well), and used it to write optimization passes that perform uncurrying, inlining, dead code elimination, and static evaluation of case expressions and record projections. The generated implementations are sometimes faster, and at most 40% slower, than hand-written counterparts on a small set of benchmarks; in some cases, they require significantly less code to write and prove correct.
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- PAR ID:
- 10602204
- Publisher / Repository:
- Association for Computing Machinery (ACM)
- Date Published:
- Journal Name:
- Proceedings of the ACM on Programming Languages
- Volume:
- 5
- Issue:
- ICFP
- ISSN:
- 2475-1421
- Format(s):
- Medium: X Size: p. 1-29
- Size(s):
- p. 1-29
- Sponsoring Org:
- National Science Foundation
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