scholarly journals AVPredictor: Comprehensive prediction and detection of atomicity violations

2019 ◽  
Vol 31 (15) ◽  
Author(s):  
Pengfei Wang ◽  
Jens Krinke ◽  
Xu Zhou ◽  
Kai Lu
Keyword(s):  
Atomicity Violations

Dynamically Detecting DOM-Related Atomicity Violations in JavaScript with Asynchronous Call

2016 ◽  
Author(s):  
Dezhi Wang ◽  
Lei Xu ◽  
Baowen Xu ◽  
Weifeng Zhang
Keyword(s):  
Atomicity Violations

Detecting Atomicity Violations for Event-Driven Node.js Applications

2019 ◽  
Author(s):  
Xiaoning Chang ◽  
Wensheng Dou ◽  
Yu Gao ◽  
Jie Wang ◽  
Jun Wei ◽  
...  
Keyword(s):  
Event Driven ◽  
Atomicity Violations

BAVC: Classifying Benign Atomicity Violations via Machine Learning

2013 ◽  
Vol 765-767 ◽  
pp. 1576-1580 ◽  
Author(s):  
Qi Chang Chen ◽  
Zhan Fang Chen ◽  
Zhuang Liu ◽  
Xin Feng ◽  
Zhen Gang Jiang ◽  
...  
Keyword(s):  
Machine Learning ◽  
Code Region ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Concurrent Programs ◽  
Testing And Debugging ◽  
Atomicity Violation ◽  
Learning Techniques ◽  
Concurrency Errors ◽  
Atomicity Violations

The reality of multi-core hardware has made concurrent programs pervasive. Unfortunately, writing correct concurrent programs is difficult. Atomicity violation, which is caused by concurrent executions unexpectedly violating the atomicity of a certain code region, is one of the most common concurrency errors. However, atomicity violation bugs are hard to find using traditional testing and debugging techniques. In this paper, we investigate an approach based on machine learning techniques (specifically decision tree and support vector machine (SVM)) for classifying the benign atomicity violations from the harmful ones. A benign atomicity violation is known not to affect the program's correctness even it happens. We formulate our problem as a supervised-learning problem and apply these two machine learning techniques to classify the atomicity violation report. Our experimental evaluation shows that the proposed method is effective in identifying the benign atomicity violation warnings.

scholarly journals Precise Detection of Atomicity Violations

2013 ◽  
pp. 8-23 ◽  
Author(s):  
Ricardo J. Dias ◽  
Vasco Pessanha ◽  
João M. Lourenço
Keyword(s):  
Atomicity Violations

scholarly journals Meta-analysis for Atomicity Violations under Nested Locking

2009 ◽  
pp. 248-262 ◽  
Author(s):  
Azadeh Farzan ◽  
P. Madhusudan ◽  
Francesco Sorrentino
Keyword(s):  
Meta Analysis ◽  
Atomicity Violations

scholarly journals Trace-Based Symbolic Analysis for Atomicity Violations

2010 ◽  
pp. 328-342 ◽  
Author(s):  
Chao Wang ◽  
Rhishikesh Limaye ◽  
Malay Ganai ◽  
Aarti Gupta
Keyword(s):  
Symbolic Analysis ◽  
Atomicity Violations

scholarly journals AVIO: Detecting Atomicity Violations via Access-Interleaving Invariants

IEEE Micro ◽  
2007 ◽  
Vol 27 (1) ◽  
pp. 26-35 ◽  
Author(s):  
Shan Lu ◽  
Joseph Tucek ◽  
Feng Qin ◽  
Yuanyuan Zhou
Keyword(s):  
Atomicity Violations
Sign in / Sign up

Export Citation Format

Share Document