Dynamic analyses are a standard approach to analyzing and testing concurrent programs. Such techniques observe program traces σ and analyze them to infer the presence or absence of bugs. At its core, each analysis maintains a partial order P that ...

Existing data race detectors for task-based programs incur significant run time and space overheads. The overheads arise because of frequent lookups in fine-grained tree data structures to check whether two accesses can happen in parallel. This work ...

Dynamic techniques are a scalable and effective way to analyze concurrent programs. Instead of analyzing all behaviors of a program, these techniques detect errors by focusing on a single program execution. Often a crucial step in these techniques is to ...

Node.js has been widely-used as an event-driven server-side architecture. To improve performance, a task in a Node.js application is usually divided into a group of events, which are non-deterministically scheduled by Node.js. Developers may assume that ...

Event-based races are the main source of concurrency errors in Android apps. Prior approaches for scalable detection of event-based races have been dynamic. Due to their dynamic nature, these approaches suffer from coverage and false negative issues. We ...

Asynchronous programming model is commonly used in mobile systems and Web 2.0 environments. Asynchronous race detectors use algorithms that are an order of magnitude performance and space inefficient compared to conventional data race detectors. We ...

Happens-before memory model (HMM) is used as the basis of Java memory model (JMM). Although HMM itself is simple, some complex axioms have to be introduced in JMM to prevent the causality loop, which causes absurd out-of-thin-air reads that may break ...

Data races are ubiquitous in multi-threaded applications, but they are by no means easy to detect. One of the most important reasons is the complexity of thread interleavings. A volume of research has been devoted to the interleaving-insensitive ...

Software-Defined Networking (SDN) control software executes in highly asynchronous environments where unexpected concurrency errors can lead to performance or, worse, reachability errors. Unfortunately, detecting such errors is notoriously challenging, ...

Techniques and tools for verification of multi-threaded programs must cope with the huge number of possible thread interleavings. Tools based on systematic exploration of a program state space employ partial order reduction to avoid redundant thread ...

This paper addresses the static analysis of an important class of X10 programs, namely those with finish/async parallelism, and affine loops and array reference structure as in the polyhedral model. For such programs our analysis can certify whenever a ...

Data races are among the most reliable indicators of programming errors in concurrent software. For at least two decades, Lamport's happens-before (HB) relation has served as the standard test for detecting races--other techniques, such as lockset-based ...

Recent paradigm shifts in distributed computing such as the advent of cloud computing pose new challenges to the analysis of distributed executions. One important new characteristic is that the management staff of computing platforms and the developers ...

Multi-core chips enable parallel processing for general purpose applications. Unfortunately, parallel programs may contain synchronization defects. Such defects are difficult to detect due to nondeterministic interleavings of parallel threads. Current ...

This paper presents a rigorous mathematical theory for the detection of data races in threaded programs. After creating a structure with precise definitions and theorems, it goes on to develop four algorithms with the goal of detecting at least one race ...

We present a new method for dynamically detecting potential data races in multithreaded programs. Our method improves on the state of the art in accuracy, in usability, and in overhead. We improve accuracy by combining two previously known race ...