Investigating White-Box Attacks for On-Device Models

1 code implementation • 8 Feb 2024 • Mingyi Zhou, Xiang Gao, Jing Wu, Kui Liu, Hailong Sun, Li Li

Our findings emphasize the need for developers to carefully consider their model deployment strategies, and use white-box methods to evaluate the vulnerability of on-device models.

Multisensor fusion-based digital twin in additive manufacturing for in-situ quality monitoring and defect correction

no code implementations • 12 Apr 2023 • Lequn Chen, Xiling Yao, Kui Liu, Chaolin Tan, Seung Ki Moon

Early detection and correction of defects are critical in additive manufacturing (AM) to avoid build failures.

App Review Driven Collaborative Bug Finding

1 code implementation • 7 Jan 2023 • Xunzhu Tang, Haoye Tian, Pingfan Kong, Kui Liu, Jacques Klein, Tegawendé F. Bissyande

Our novelty is that we guide the bug finding process by considering that existing bugs have been hinted within app reviews.

Is this Change the Answer to that Problem? Correlating Descriptions of Bug and Code Changes for Evaluating Patch Correctness

1 code implementation • 8 Aug 2022 • Haoye Tian, Xunzhu Tang, Andrew Habib, Shangwen Wang, Kui Liu, Xin Xia, Jacques Klein, Tegawendé F. Bissyandé

To tackle this problem, our intuition is that natural language processing can provide the necessary representations and models for assessing the semantic correlation between a bug (question) and a patch (answer).

Question Answering

Predicting Patch Correctness Based on the Similarity of Failing Test Cases

1 code implementation • 28 Jul 2021 • Haoye Tian, Yinghua Li, Weiguo Pian, Abdoul Kader Kaboré, Kui Liu, Andrew Habib, Jacques Klein, Tegawendé F. Bissyande

Then, after collecting a large dataset of 1278 plausible patches (written by developers or generated by some 32 APR tools), we use BATS to predict correctness: BATS achieves an AUC between 0. 557 to 0. 718 and a recall between 0. 562 and 0. 854 in identifying correct patches.

Representation Learning

Neural Network Activation Quantization with Bitwise Information Bottlenecks

1 code implementation • 9 Jun 2020 • Xichuan Zhou, Kui Liu, Cong Shi, Haijun Liu, Ji Liu

Recent researches on information bottleneck shed new light on the continuous attempts to open the black box of neural signal encoding.

Computational Efficiency Quantization

iFixR: Bug Report driven Program Repair

2 code implementations • 12 Jul 2019 • Anil Koyuncu, Kui Liu, Tegawendé F. Bissyandé, Dongsun Kim, Martin Monperrus, Jacques Klein, Yves Le Traon

Towards increasing the adoption of patch generation tools by practitioners, we investigate a new repair pipeline, iFixR, driven by bug reports: (1) bug reports are fed to an IR-based fault localizer; (2) patches are generated from fix patterns and validated via regression testing; (3) a prioritized list of generated patches is proposed to developers.

Software Engineering