Jiajun JIANG's Homepage

News

[Jul. 3, 2024]Two papers were accepted by ISSTA 2024. Congrats to all.
[Jun. 22, 2024]Congrats to Chenyang. Our latest research on code naturalness has been accepted by OOPSLA 2024.
[Mar. 2, 2024]Congrats to Junjie. Our latest research on fairness improvement of deep learning models has been accepted by ISSTA 2024. In this paper, we have systematically compared the performance of existing techniques under a unified setting, based on which we have summarized a set of findings that can facilitate future research.
[Oct. 10, 2023]One paper is accepted by TOSEM. In this paper, we proposed a general model post-training framework for improving the performance of DL models in different tasks. This is also a follow-up work of our ASE 2022 paper. Congrats to Junjie, Yingyi and Hanmo.
[Sep. 1, 2023]One paper is accepted by TOSEM. In this paper, we have proposed a novel variable-level fault localization technique by leveraging both static analysis and machine learning techniques. The located variables (or expressions) can not only provide more insightfull information for manual debugging, but can also improve the patch quality in automated program repair. Congrats to Yumeng, Delin and Mengjiao.
[Jul. 30, 2023]One paper is accepted by ISSRE 2023, Congrats to Lin.
[Feb. 8, 2023]One paper is accepted by TOSEM. In this paper, we have conducted a systematic analysis of bugs in deep learning frameworks and provided a set of findings to promote future research. Congrats to Yihua, Qingchao and Shuochuan.
[Jan. 16, 2023]One paper on compiler bug de-duplication is accepted by ISSTA 2023. Congrats to Chen Yang.
[Dec. 23, 2022]One paper is accepted by ICSE SEIP 2023. Congrats to Ming Yan.
[Dec. 9, 2022]Our paper Compiler Test-Program Generation via Memoized Configuration Search is accepted by ICSE 2023. Congrats to Chenyao.
[Jul. 21, 2022]Congrats to Yingyi and Hanmo, our latest research Toward Improving the Robustness of Deep Learning Models via Model Transformation is accepted by ASE 2022. In this paper, we propose a novel "Model Transformation" idea to improve the robustness of DL models, which can defend against different attacks. This is also our first attempt on DL model repair.
[Jun. 3, 2022]Congrats to Chen Yang on being the 3rd place winner at the 2022 ACM's Student Research Competition Grand Finals (undergraduate category) with our latest repair work "Accelerating Redundancy-Based Program Repair via Code Representation Learning and Adaptive Patch Filtering", which won the 1st place at ESEC/FSE 2021 SRC.
[Mar. 5, 2022]I am honored to be a guest editor for the special issue on "Automatic Defects Discovering and Fixing" at ChinaSoft 2022. Looking forward to your contribution.
[Oct. 2, 2021]Our paper Interactive Patch Filtering as Debugging Aid was awarded IEEE TCSE Distinguished Paper Award. Thanks for the recognition.
[Jul. 2, 2021]Our latest paper A Comprehensive Study on Learning-based PE Malware Family Classification Methods was accepted by FSE 2021 industry track. Congrats to Yixuan and Guanhong.
[Jun. 16, 2021]Our paper Interactive Patch Filtering as Debugging Aid was accepted to appear at ICSME 2021. In this paper, we propose the first interactive patch filtering approach and design an Eclipse plugin that can help developers effectively remove incorrect patches via answering a few simple questions. Congrats to Jingjing.
[Jan. 16, 2021]Our paper A Large-scale Study on API Misuses in the Wild was accepted to appear at ICST 2021. We have systematically studied the API misuses over millions of bug fixes from GitHub, and provide guidance for future research on API misuse detection.
[Dec. 31, 2020]Our survey paper Survey of Automatic Program Repair Techniques has systematically summarized the recent research on Automatic Program Repair and will be published on Journal of Software.
[Dec. 16, 2020]The paper Semi-supervised Log-based Anomaly Detection via Probabilistic Label Estimation was accepted by ICSE'21. Congrats to Lin Yang and Weijing.
[Aug. 2, 2020]The paper How to Mitigate the Incident? An Effective Troubleshooting Guide Recommendation Technique for Online Service Systems was accepted by FSE'20 industry track.
[Jun. 16, 2020]I was awarded the "Outstanding Graduate Students" of Peking University.
[Apr. 22, 2020]Our survey paper Survey of Dynamic Analysis Based Program Invariant Synthesis Techniques was published on Journal of Software.
[Oct. 20, 2019]I was awarded the "Merit Student Pacesetter" of Peking University, and won the National Scholarship.
[Aug. 7, 2019]GenPat can be publicly downloaded here, checkout and try it now!
[Aug. 6, 2019]Two papers were accepted at ASE'19. Inferring Program Transformations From Singular Examples via Big Code proposes a general framework, GenPat, which can infer program transformations from only one example. Combining Spectrum-Based Fault Localization and Statistical Debugging: An Empirical Study formally defines a unified model that combines the strength of SBFL and statistical debugging.
[Jul. 25, 2019]Our paper A Manual Inspection of Defects4J Bugs and Its Implications for Automatic Program Repair was accepted as a full research paper on CHINA SCIENCE Information Sciences. In this paper, we manually repaired 50 real-world bugs and provide a number of insights for future study on automatic program repair techniques.
[May 15, 2019]Our program repair tool SimFix is open-source and the replication package for ISSTA'18 paper also can be downloaded now. Link
[Apr. 30, 2018]Our paper Shaping Program Repair Space with Existing Patches and Similar Code was accepted at ISSTA'18. First time it proposed to leverage both existing patches and similar code to refine the search space of patches.
[Mar. 30, 2016]Our paper Transforming Programs between APIs with Many-to-Many Mappings was accepted at ECOOP'16. We have designed a DSL for describing the mapping relations between APIs to ease the procedure of manual definition, based on which our approach can automatically perfrom program transformation and ensure the transformed program is type-safe.