返回
Enhancing concurrency vulnerability detection through AST-based static
DOI:10.1016/j.jss.2025.112352.png)
摘要
En 中文
As multi-threaded and highly concurrent programs are increasingly used, their inherent uncertainty significantly impacts program stability. Traditional testing methods often struggle to effectively detect specific concurrency vulnerabilities because these vulnerabilities are triggered only under particular circumstances, making detection at the vulnerability-triggering level challenging. In view of this, we propose a static fuzz mutation testing method based on Abstract Syntax Tree (AST). This method leverages the fine-grained granularity of ASTs to optimize test suites for concurrency vulnerabilities detection. Initially, We analyze and classify the concurrency vulnerabilities found in Go source code, and generate vulnerability feature mutation operators (mutation operators with concurrency vulnerability feature). Next, we propose static fuzz mutation method and heuristic algorithms at the AST level and apply them to mutators. Ultimately, we screened over 200 code slices from 8 open-source projects for static fuzz mutation testing. The results indicate that introducing vulnerability feature mutation operators improved the number of mutant by approximately 22.15% across various types of concurrency vulnerability samples. This enhancement elevated the probability of triggering concurrency vulnerabilities in the program. After incorporating data from the Go language standard library, experiments further confirmed that our proposed static fuzz mutation testing method can effectively improve the accuracy of concurrency vulnerability detection.
Keyword:
Concurrent programs
Mutation testing
Abstract Syntax Tree
Static fuzz mutation
Go language
期刊
IF:
4.1
论文数:
5.4K
被引数:
8.4K
机构
引用论文
An Accurate Metaheuristic Mountain Gazelle Optimizer for Parameter Estimation of Single- and Double-Diode Photovoltaic Cell Models用于单二极管和双二极管光伏电池模型参数估计的精确元启发式山瞪羚优化器
Mathematics
IF0
Differentiation of Human Embryonic Stem Cells to Regional Specific Neural Precursors in Chemically Defined Medium Conditions
PLoS ONE
IF0
Variable participation in the defense of communal feeding territories by blue monkeys in the Kakamega Forest, Kenya
Behaviour
IF0

