Improving bug detection via context-based code representation learning and attention-based neural networks

Y Li, S Wang, TN Nguyen, S Van Nguyen - Proceedings of the ACM on …, 2019 - dl.acm.org
Bug detection has been shown to be an effective way to help developers in detecting bugs
early, thus, saving much effort and time in software development process. Recently, deep …

FPGA/GPU-based acceleration for frequent itemsets mining: A comprehensive review

L Bustio-Martínez, R Cumplido, M Letras… - ACM Computing …, 2021 - dl.acm.org
In data mining, Frequent Itemsets Mining is a technique used in several domains with
notable results. However, the large volume of data in modern datasets increases the …

[PDF][PDF] Unifying the perspectives of nlp and software engineering: A survey on language models for code

Z Zhang, C Chen, B Liu, C Liao, Z Gong… - arXiv preprint arXiv …, 2023 - simg.baai.ac.cn
In this work we systematically review the recent advancements in code processing with
language models, covering 50+ models, 30+ evaluation tasks, 170+ datasets, and 700 …

Detecting condition-related bugs with control flow graph neural network

J Zhang, X Wang, H Zhang, H Sun, X Liu… - Proceedings of the 32nd …, 2023 - dl.acm.org
Automated bug detection is essential for high-quality software development and has
attracted much attention over the years. Among the various bugs, previous studies show that …

Finding bugs using your own code: detecting functionally-similar yet inconsistent code

M Ahmadi, RM Farkhani, R Williams, L Lu - 30th USENIX security …, 2021 - usenix.org
Probabilistic classification has shown success in detecting known types of software bugs.
However, the works following this approach tend to require a large amount of specimens to …

Static detection of unsafe {DMA} accesses in device drivers

JJ Bai, T Li, K Lu, SM Hu - 30th USENIX Security Symposium (USENIX …, 2021 - usenix.org
Direct Memory Access (DMA) is a popular mechanism for improving hardware I/O
performance, and it has been widely used by many existing device drivers. However, DMA …

Arbitrar: User-guided api misuse detection

Z Li, A Machiry, B Chen, M Naik… - … IEEE Symposium on …, 2021 - ieeexplore.ieee.org
Software APIs exhibit rich diversity and complexity which not only renders them a common
source of programming errors but also hinders program analysis tools for checking them …

APP-Miner: Detecting API Misuses via Automatically Mining API Path Patterns

J Jiang, J Wu, X Ling, T Luo, S Qu… - 2024 IEEE Symposium …, 2024 - ieeexplore.ieee.org
Extracting API patterns from the source code has been extensively employed to detect API
misuses. However, recent studies manually provide pattern templates as prerequisites …

Code-line-level bugginess identification: How far have we come, and how far have we yet to go?

Z Guo, S Liu, X Liu, W Lai, M Ma, X Zhang… - ACM Transactions on …, 2023 - dl.acm.org
Background. Code-line-level bugginess identification (CLBI) is a vital technique that can
facilitate developers to identify buggy lines without expending a large amount of human …

Champ: Characterizing undesired app behaviors from user comments based on market policies

Y Hu, H Wang, T Ji, X Xiao, X Luo… - 2021 IEEE/ACM 43rd …, 2021 - ieeexplore.ieee.org
Millions of mobile apps have been available through various app markets. Although most
app markets have enforced a number of automated or even manual mechanisms to vet each …