212 citations · 810 across the 54 of their papers we have counts for
10 papers · 1 filter
Trex: Learning Execution Semantics from Micro-Traces for Binary Similarity
Kexin Pei, Zhou Xuan, Junfeng Yang +2
Detecting semantically similar functions -- a crucial analysis capability with broad real-world security usages including vulnerability detection, malware lineage, and forensics --…
CADET: Debugging and Fixing Misconfigurations using Counterfactual Reasoning
Rahul Krishna, Md Shahriar Iqbal, Mohammad Ali Javidian +2
Modern computing platforms are highly-configurable with thousands of interacting configurations. However, configuring these systems is challenging. Erroneous configurations can cau…
Understanding Local Robustness of Deep Neural Networks under Natural Variations
Ziyuan Zhong, Yuchi Tian, Baishakhi Ray
Deep Neural Networks (DNNs) are being deployed in a wide range of settings today, from safety-critical applications like autonomous driving to commercial applications involving ima…
Deep Learning & Software Engineering: State of Research and Future Directions
Prem Devanbu, Matthew Dwyer, Sebastian Elbaum +6
Given the current transformative potential of research that sits at the intersection of Deep Learning (DL) and Software Engineering (SE), an NSF-sponsored community workshop was co…
Deep Learning based Vulnerability Detection: Are We There Yet?
Saikat Chakraborty, Rahul Krishna, Yangruibo Ding +1
Automated detection of software vulnerabilities is a fundamental problem in software security. Existing program analysis techniques either suffer from high false positives or false…
Patching as Translation: the Data and the Metaphor
Yangruibo Ding, Baishakhi Ray, Premkumar Devanbu +1
Machine Learning models from other fields, like Computational Linguistics, have been transplanted to Software Engineering tasks, often quite successfully. Yet a transplanted model'…
Multitask Learning Strengthens Adversarial Robustness
Chengzhi Mao, Amogh Gupta, Vikram Nitin +4
Although deep networks achieve strong accuracy on a range of computer vision benchmarks, they remain vulnerable to adversarial attacks, where imperceptible input perturbations fool…
Pythia: Grammar-Based Fuzzing of REST APIs with Coverage-guided Feedback and Learning-based Mutations
Vaggelis Atlidakis, Roxana Geambasu, Patrice Godefroid +2
This paper introduces Pythia, the first fuzzer that augments grammar-based fuzzing with coverage-guided feedback and a learning-based mutation strategy for stateful REST API fuzzin…
MTFuzz: Fuzzing with a Multi-Task Neural Network
Dongdong She, Rahul Krishna, Lu Yan +2
Fuzzing is a widely used technique for detecting software bugs and vulnerabilities. Most popular fuzzers generate new inputs using an evolutionary search to maximize code coverage.…
A Transformer-based Approach for Source Code Summarization
Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray +1
Generating a readable summary that describes the functionality of a program is known as source code summarization. In this task, learning code representation by modeling the pairwi…