Search for: All records

Concurrency bugs are hard to discover and reproduce, even in well-synchronized programs that are free of data races. Thankfully, prior work on controlled concurrency testing (CCT) has developed sophisticated algorithms---such as partial-order based and selectively uniform sampling---to effectively search over the space of thread interleavings. Unfortunately, in practice, these techniques cannot easily be applied to real-world Java programs due to the difficulties of controlling concurrency in the presence of the managed runtime and complex synchronization primitives. So, mature Java projects that make heavy use of concurrency still rely on naive repeated stress testing in a loop. In this paper, we take a first-principles approach for elucidating the requirements and design space to enable CCT on arbitrary real-world JVM applications. We identify practical challenges with classical design choices described in prior work---such as concurrency mocking, VM hacking, and OS-level scheduling---that affect bug-finding effectiveness and/or the scope of target applications that can be easily supported. Based on these insights, we present Fray, a new platform for performing push-button concurrency testing (beyond data races) of JVM programs. The key design principle behind Fray is to orchestrate thread interleavings without replacing existing concurrency primitives, using a concurrency control mechanism called shadow locking for faithfully expressing the set of all possible program behaviors. With full concurrency control, Fray can test applications using a number of search algorithms from a simple random walk to sophisticated techniques like PCT, POS, and SURW. In an empirical evaluation on 53 benchmark programs with known bugs (SCTBench and JaConTeBe), Fray with random walk finds 70% more bugs than JPF and 77% more bugs than RR's chaos mode. We also demonstrate Fray's push-button applicability on 2,664 tests from Apache Kafka, Lucene, and Google Guava. In these mature projects, Fray successfully discovered 18 real-world concurrency bugs that can cause 371 of the existing tests to fail under specific interleavings. We believe that Fray serves as a bridge between classical academic research and industrial practice--- empowering developers with advanced concurrency testing algorithms that demonstrably uncover more bugs, while simultaneously providing researchers a platform for large-scale evaluation of search techniques. 

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.