Testing concurrent programs on relaxed memory models

Abstract

High-performance concurrent libraries, such as lock-free data structures and custom synchronization primitives, are notoriously difficult to write correctly. Such code is often implemented without locks, instead using plain loads and stores and low-level operations like atomic compare-and-swaps and explicit memory fences. Such code must run correctly despite the relaxed memory model of the underlying compiler, virtual machine, and/or hardware. These memory models may reorder the reads and writes issued by a thread, greatly complicating parallel reasoning.We propose RELAXER, a combination of predictive dynamic analysis and software testing, to help programmers write correct, highly-concurrent programs. Our technique works in two phases. First, RELAXER examines a sequentially-consistent run of a program under test and dynamically detects potential data races. These races are used to predict possible violations of sequential consistency under alternate executions on a relaxed memory model. In the second phase, RELAXER re-executes the program with a biased random scheduler and with a conservative simulation of a relaxed memory model in order to create with high probability a predicted sequential consistency violation. These executions can be used to test whether or not a program works as expected when the underlying memory model is not sequentially consistent.We have implemented RELAXER for C and have evaluated it on several synchronization algorithms, concurrent data structures, and parallel applications. RELAXER generates many executions of these benchmarks with violations of sequential consistency, highlighting a number of bugs under relaxed memory models.

Automatic inference of memory fences

“…There exist several techniques for program testing and verification under relaxed memory models, and tools have been developed that implement these techniques (cf. [6,7,9,8,22].) To utilize a verification tool (e.g.…”

Counter-Example Guided Fence Insertion under TSO

“…Existing approaches avoid solving the general problem by considering under-approximations, over-approximations, restricted classes of programs, forbidding sequential inconsistent behavior, or by proposing exact algorithms for which termination is not guaranteed. Under-approximations of the program behavior can be achieved through testing [9], bounded model checking [7,6], or by restricting the behavior of the program, e.g., through bounding the sizes of the buffers [18] or the number of switches [5]. Such techniques are useful in practice for finding errors.…”

Partial-coherence abstractions for relaxed memory models

“…Existing Approaches Existing approaches either employ underapproximations such as bounded checking [5] and testing [8], or side-step the problem by focusing on a restricted class of programs. For instance, [32] considers data-race free programs, and [28] focuses on programs free from a particular ("triangular") type of data races.…”