No Arabic abstract
We propose a technique for synthesizing bidirectional programs from the corresponding unidirectional code plus a few input/output examples. The core ideas are: (1) constructing a sketch using the given unidirectional program as a specification, and (2) filling the sketch in a modular fashion by exploiting the properties of bidirectional programs. These ideas are enabled by our choice of programming language, HOBiT, which is specifically designed to maintain the unidirectional program structure in bidirectional programming, and keep the parts that control bidirectional behavior modular. To evaluate our approach, we implemented it in a tool called Synbit and used it to generate bidirectional programs for intricate microbenchmarks, as well as for a few larger, more realistic problems. We also compared Synbit to a state-of-the-art unidirectional synthesis tool on the task of synthesizing backward computations.
The Message Passing Interface specification (MPI) defines a portable message-passing API used to program parallel computers. MPI programs manifest a number of challenges on what concerns correctness: sent and expected values in communications may not match, resulting in incorrect computations possibly leading to crashes; and programs may deadlock resulting in wasted resources. Existing tools are not completely satisfactory: model-checking does not scale with the number of processes; testing techniques wastes resources and are highly dependent on the quality of the test set. As an alternative, we present a prototype for a type-based approach to programming and verifying MPI like programs against protocols. Protocols are written in a dependent type language designed so as to capture the most common primitives in MPI, incorporating, in addition, a form of primitive recursion and collective choice. Protocols are then translated into Why3, a deductive software verification tool. Source code, in turn, is written in WhyML, the language of the Why3 platform, and checked against the protocol. Programs that pass verification are guaranteed to be communication safe and free from deadlocks. We verified several parallel programs from textbooks using our approach, and report on the outcome.
If we can automatically derive compiler optimizations, we might be able to sidestep some of the substantial engineering challenges involved in creating and maintaining a high-quality compiler. We developed Souper, a synthesizing superoptimizer, to see how far these ideas might be pushed in the context of LLVM. Along the way, we discovered that Soupers intermediate representation was sufficiently similar to the one in Microsoft Visual C++ that we applied Souper to that compiler as well. Shipping, or about-to-shi
We present a novel bottom-up method for the synthesis of functional recursive programs. While bottom-up synthesis techniques can work better than top-down methods in certain settings, there is no prior technique for synthesizing recursive programs from logical specifications in a purely bottom-up fashion. The main challenge is that effective bottom-up methods need to execute sub-expressions of the code being synthesized, but it is impossible to execute a recursive subexpression of a program that has not been fully constructed yet. In this paper, we address this challenge using the concept of angelic semantics. Specifically, our method finds a program that satisfies the specification under angelic semantics (we refer to this as angelic synthesis), analyzes the assumptions made during its angelic execution, uses this analysis to strengthen the specification, and finally reattempts synthesis with the strengthened specification. Our proposed angelic synthesis algorithm is based on version space learning and therefore deals effectively with many incremental synthesis calls made during the overall algorithm. We have implemented this approach in a prototype called Burst and evaluate it on synthesis problems from prior work. Our experiments show that Burst is able to synthesize a solution to 95% of the benchmarks in our benchmark suite, outperforming prior work.
We extend a technique called Compiling Control. The technique transforms coroutining logic programs into logic programs that, when executed under the standard left-to-right selection rule (and not using any delay features) have the same computational behavior as the coroutining program. In recent work, we revised Compiling Control and reformulated it as an instance of Abstract Conjunctive Partial Deduction. This work was mostly focused on the program analysis performed in Compiling Control. In the current paper, we focus on the synthesis of the transformed program. Instead of synthesizing a new logic program, we synthesize a CHR(Prolog) program which mimics the coroutining program. The synthesis to CHR yields programs containing only simplification rules, which are particularly amenable to certain static analysis techniques. The programs are also more concise and readable and can be ported to CHR implementations embedded in other languages than Prolog.
Debugging lazy functional programs poses serious challenges. In support of the stop, examine, and resume debugging style of imperative languages, some debugging tools abandon lazy evaluation. Other debuggers preserve laziness but present it in a way that may confuse programmers because the focus of evaluation jumps around in a seemingly random manner. In this paper, we introduce a supplemental tool, the algebraic program stepper. An algebraic stepper shows computation as a mathematical calculation. Algebraic stepping could be particularly useful for novice programmers or programmers new to lazy programming. Mathematically speaking, an algebraic stepper renders computation as the standard rewriting sequence of a lazy lambda-calculus. Our novel lazy semantics introduces lazy evaluation as a form of parallel program rewriting. It represents a compromise between Launchburys store-based semantics and a simple, axiomatic description of lazy computation as sharing-via-parameters. Finally, we prove that the steppers run-time machinery correctly reconstructs the standard rewriting sequence.