D2a: A dataset built for ai-based vulnerability detection methods using differential analysis
Static analysis tools are widely used for vulnerability detection as they understand programs
with complex behavior and millions of lines of code. Despite their popularity, static analysis …
with complex behavior and millions of lines of code. Despite their popularity, static analysis …
Machine learning for actionable warning identification: A comprehensive survey
Actionable Warning Identification (AWI) plays a crucial role in improving the usability of static
code analyzers. With recent advances in Machine Learning (ML), various approaches have …
code analyzers. With recent advances in Machine Learning (ML), various approaches have …
An empirical assessment of machine learning approaches for triaging reports of a java static analysis tool
Despite their ability to detect critical bugs in software, developers consider high false
positive rates to be a key barrier to using static analysis tools in practice. To improve the …
positive rates to be a key barrier to using static analysis tools in practice. To improve the …
Analyzing source code vulnerabilities in the D2A dataset with ML ensembles and C-BERT
Static analysis tools are widely used for vulnerability detection as they can analyze
programs with complex behavior and millions of lines of code. Despite their popularity, static …
programs with complex behavior and millions of lines of code. Despite their popularity, static …
Hypergraph clustering based on modularity feature projection for high-order relationship community detection of microorganisms
Y Ma, Y Ma, X Jiang - Methods, 2022 - Elsevier
Microbial community is an important part of organisms or ecosystems to maintain health and
stability. Analyzing the interaction of microorganisms in the ecosystem and mining the co …
stability. Analyzing the interaction of microorganisms in the ecosystem and mining the co …
[BUCH][B] Probabilistic program abstractions
SJ Holtzen - 2017 - search.proquest.com
Abstraction is a fundamental tool for reasoning about a complex system. Program
abstraction has been utilized to great effect for analyzing deterministic programs. At the heart …
abstraction has been utilized to great effect for analyzing deterministic programs. At the heart …
Abstracting probabilistic models: Relations, constraints and beyond
V Belle - Knowledge-Based Systems, 2020 - Elsevier
Abstraction is a powerful idea widely used in science, to model, reason and explain the
behavior of systems in a more tractable search space, by omitting irrelevant details. While …
behavior of systems in a more tractable search space, by omitting irrelevant details. While …
[PDF][PDF] 贝叶斯程序分析
张昕, 王冠成, 吴宜谦, 陈逸凡, **天驰, 张羿凡… - 电子学报, 2024 - ejournal.org.cn
程序分析在软件开发和维护中发挥着关键作用. 然而, 传统基于逻辑的程序分析方法在处理现代
复杂, 大规模和动态特性丰富的软件系统时往往效果有限, 其根源在于软件系统中的不确定性 …
复杂, 大规模和动态特性丰富的软件系统时往往效果有限, 其根源在于软件系统中的不确定性 …
Exploring Explicit Uncertainty for Binary Analysis (EUBA)
MA Leger, MC Darling, ST Jones, LE Matzen… - 2021 - osti.gov
Reverse engineering (RE) analysts struggle to address critical questions about the safety of
binary code accurately and promptly, and their supporting program analysis tools are simply …
binary code accurately and promptly, and their supporting program analysis tools are simply …
Abstracting Probabilistic Models: A Logical Perspective
V Belle - arxiv preprint arxiv:1810.02434, 2018 - arxiv.org
Abstraction is a powerful idea widely used in science, to model, reason and explain the
behavior of systems in a more tractable search space, by omitting irrelevant details. While …
behavior of systems in a more tractable search space, by omitting irrelevant details. While …