Practical verification of high-level dataraces in transactional memory programs

Abstract

In this paper we present MoTH, a tool that uses static analysis to enable the automatic verification of concurrency anomalies in Transactional Memory Java programs. Currently MoTH detects high-level dataraces and stale-value errors, but it is extendable by plugging-in sensors, each sensor implementing an anomaly detecting algorithm. We validate and benchmark MoTH by applying it to a set of well known concurrent buggy programs and by close comparison of the results with other similar tools. The results achieved so far are very promising, yielding good accuracy while triggering only a very limited number of false warnings.

Static Application-Level Race Detection in STM Haskell using Contracts

“…Several frameworks try to tackle the problem of multiple variables [25,29,28,1,45,38]. In those works, static or dynamic techniques are used in order to infer possible correlations between shared variables.…”

“…This idea is depicted by the concept of high-level data race, introduced by [1]. Such a race occurs when a set of shared memory locations is meant to be accessed atomically, but the memory locations are accessed separately somewhere in the program [45,38]. The interest of these tools is indisputable as they find a lot of races without requiring (a lot of) annotations, but they typically can trigger false positives and false negatives.…”