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We transport multi-stage programming from functional to relational programming, with novel constructs to give programmers control over staging and non-determinism. We stage interpreters written as relations, in which the programs under interpretation can contain holes representing unknown expressions or values. By compiling the known parts without interpretive overhead and deferring interpretation to run time only for the unknown parts, we compound the benefits of staging (e.g., turning interpreters into compilers) and relational interpretation (e.g., turning functions into relations and synthesizing from sketches). We extend miniKanren with staging constructs and apply the resulting multi-stage language to relational interpreters for subsets of Racket and miniKanren as well as a relational recognizer for context-free grammars. We demonstrate significant performance gains across multiple synthesis problems, systematically comparing unstaged and staged computation, as well as indicatively comparing with an existing hand-tuned relational interpreter. 

Greybox fuzzing and mutation testing are two popular but mostly independent fields of software testing research that have so far had limited overlap. Greybox fuzzing, generally geared towards searching for new bugs, predominantly uses code coverage for selecting inputs to save. Mutation testing is primarily used as a stronger alternative to code coverage in assessing the quality of regression tests; the idea is to evaluate tests for their ability to identify artificially injected faults in the target program. But what if we wanted to use greybox fuzzing to synthesize high-quality regression tests? In this paper, we develop and evaluate Mu2, a Java-based framework for incorporating mutation analysis in the greybox fuzzing loop, with the goal of producing a test-input corpus with a high mutation score. Mu2 makes use of a differential oracle for identifying inputs that exercise interesting program behavior without causing crashes. This paper describes several dynamic optimizations implemented in Mu2 to overcome the high cost of performing mutation analysis with every fuzzer-generated input. These optimizations introduce trade-offs in fuzzing throughput and mutation killing ability, which we evaluate empirically on five real-world Java benchmarks. Overall, variants of Mu2 are able to synthesize test-input corpora with a higher mutation score than state-of-the-art Java fuzzer Zest. 

San Diego, CA 

We present a fully lock-free variant of our recent Montage system for persistent data structures. The variant, nbMontage, adds persistence to almost any nonblocking concurrent structure without introducing significant overhead or blocking of any kind. Like its predecessor, nbMontage is buffered durably linearizable: it guarantees that the state recovered in the wake of a crash will represent a consistent prefix of pre-crash execution. Unlike its predecessor, nbMontage ensures wait-free progress of the persistence frontier, thereby bounding the number of recent updates that may be lost on a crash, and allowing a thread to force an update of the frontier (i.e., to perform a sync operation) without the risk of blocking. As an extra benefit, the helping mechanism employed by our wait-free sync significantly reduces its latency. Performance results for nonblocking queues, skip lists, trees, and hash tables rival custom data structures in the literature – dramatically faster than achieved with prior general-purpose systems, and generally within 50% of equivalent non-persistent structures placed in DRAM.