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_bibliography/publications.bib

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@@ -13,6 +13,7 @@ @inproceedings{yang2024large
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year={2024},
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doi={10.1145/3597503.3623342},
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code={https://github.com/squaresLab/LLMAO},
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project = {ai}
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}
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@@ -30,15 +31,16 @@ @INPROCEEDINGS {Ye2023PreciseBugCollector
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address = {Los Alamitos, CA, USA},
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month = {sep},
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code = {https://github.com/SophieHYe/PreciseBugs},
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project = {benchmarks}
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project = {benchmarks,ai}
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}
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@article{debSyntaxAllYouNeed,
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title = {Syntax Is All You Need: A Universal-Language Approach to Mutant Generation},
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author = {Deb, Sourav and Jain, Kush and {van~Tonder}, Rijnard and {Le~Goues}, Claire and Groce, Alex},
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booktitle = {Proceedings of the 32nd ACM International Conference on the Foundations of Software Engineering (FSE)},
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series = {FSE 24},
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year = {2024}
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year = {2024},
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project = {transform-testing}
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}
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@article{groceFuzzTheMutants,
@@ -83,7 +85,7 @@ @inproceedings{jainContextualPMT
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keywords = {test oracles, mutation analysis, code coverage},
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location = {<conf-loc>, <city>San Francisco</city>, <state>CA</state>, <country>USA</country>, </conf-loc>},
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series = {ESEC/FSE 2023},
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project = {transform-testing}
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project = {transform-testing,ai}
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}
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@@ -102,7 +104,8 @@ @INPROCEEDINGS {raoCATLM
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publisher = {IEEE Computer Society},
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address = {Los Alamitos, CA, USA},
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data = {https://github.com/RaoNikitha/CAT-LM},
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month = {sep}
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month = {sep},
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project = {ai}
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}
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@INPROCEEDINGS {jainOracleGap,
@@ -134,7 +137,7 @@ @article{cruz22crayons
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year = {2023},
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url = {https://doi.org/10.1145/3548684},
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doi = {10.1145/3548684},
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project = {repair,new-repair,static-repair}
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project = {repair,new-repair,static-repair,ai}
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}
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@article{motwani20tse,
@@ -199,7 +202,8 @@ @inproceedings{SOAR2021
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url = {https://doi.org/10.1109/ICSE43902.2021.00023},
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doi = {10.1109/ICSE43902.2021.00023},
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biburl = {https://dblp.org/rec/conf/icse/NiRYLMMG21.bib},
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series = {ICSE '21}
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series = {ICSE '21},
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project = {ai}
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}
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@inproceedings{RamosMLMMG23,
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doi = {10.1109/ASE56229.2023.00117},
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series = {ASE '23},
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code = {https://github.com/squaresLab/MELT/},
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data = {https://doi.org/10.5281/zenodo.8226234}
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data = {https://doi.org/10.5281/zenodo.8226234},
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project = {ai}
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}
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@article{batfix,
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doi = {10.1145/3658668},
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journal = {ACM Transactions on Software Engineering and Methodology},
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month = {April},
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project = {ai}
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}
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author={Dramko, Luke and Lacomis, Jeremy and Schwartz, Edward J and Vasilescu, Bogdan and {Le~Goues}, Claire},
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booktitle={33rd USENIX Security Symposium},
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series={USENIX Security 24},
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year={2024}
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year={2024},
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project = {decomp}
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}
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@article{DramkoDIREData2022,
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year = {2023},
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doi = {10.1145/3546946},
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series = {TOSEM '22},
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project = {ai-sbe},
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project = {decomp,ai}
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}
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@inproceedings{ShypulaSuperoptimization2022,
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booktitle = {Deep Learning for Code Workshop},
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year = {2022},
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series = {DL4C '22},
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project = {ai-sbe},
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project = {decomp,ai},
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}
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@inproceedings{ChenVarCLR2022,
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booktitle = {International Conference on Software Engineering},
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year = {2022},
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series = {ICSE '22},
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project = {ai-sbe},
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project = {decomp,ai},
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code = {https://github.com/squaresLab/VarCLR}
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}
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booktitle = {USENIX Security Symposium},
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year = {2022},
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series = {Oakland '22},
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project = {ai-sbe},
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project = {decomp,ai},
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code = {https://github.com/CMUSTRUDEL/DIRTY},
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website = {https://dirtdirty.github.io/explorer.html},
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}
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series = {ICRA '20},
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year = {2020},
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pages = {9367--9373},
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project = {robots}
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project = {robots, ai}
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}
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@inproceedings{durieux20msr,
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doi = {10.1109/MSR.2019.00037},
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location = {Montreal, Canada},
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publisher = {{IEEE}/{ACM}},
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url = {https://doi.org/10.1109/MSR.2019.00037}
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url = {https://doi.org/10.1109/MSR.2019.00037},
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project = {benchmarks}
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@inproceedings{botse19,
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pages = {43-47},
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keywords = {Syntactics;Maintenance engineering;Computer bugs;Tools;Semantics;Software;Automation;software bots;program transformation;automation;software quality;refactoring;automatic program repair},
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doi = {10.1109/BotSE.2019.00019},
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issn = {}
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issn = {},
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project = {new-repair}
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@article{AfzalSOSRepair19,
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year = {2019},
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data = {https://doi.org/10.5281/zenodo.3403077},
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series = {ASE '19},
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project = {ai-sbe},
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project = {decomp,ai}
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@ARTICLE{MARS2019,
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doi = {10.1109/SEAMS.2019.00031},
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numpages = {7},
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publisher = {IEEE},
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project = {ai-sbe,robots}
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project = {robots}
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@inproceedings{WeintropCoBlox2018,
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@article{sw18ebm,
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author = {Claire {Le~Goues} and
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Ciera Jaspan and
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Ipek Ozkaya and
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Mary Shaw and
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Kathryn T. Stolee},
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title = {Bridging the Gap: From Research to Practical Advice},
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abbrv = {IEEE SW},
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journal = {{IEEE} Software},
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volume = {35},
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number = {5},
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pages = {50--57},
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year = {2018},
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doi = {10.1109/MS.2018.3571235},
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}
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@inproceedings{vanTonderSCB2018,
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author = {Rijnard {van~Tonder} and John Kotheimer and Claire {Le~Goues}},
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title = {Semantic Crash Bucketing},
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year = 2018,
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series = {ICPC '18},
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project = {decomp,ai},
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@InProceedings{AfzalTuringTest2018,
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project = {decomp,ai}
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@InProceedings{KinneerManaging2018,
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numpages = 12,
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doi = {10.1145/2931037.2931049},
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project = {ai}
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@InProceedings{TianRecommendation2016,
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publisher = {{IEEE} Computer Society},
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pages = {1--10},
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doi = {10.1109/ICPC.2016.7503715},
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project = {develop}
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project = {develop,ai}
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@InProceedings{OliveiraCrossover2016,
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series = {SANER '18},
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pages = {346--356},
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location = {Campobasso, Italy},
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doi = {10.1109/SANER.2018.8330222}
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doi = {10.1109/SANER.2018.8330222},
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project = {decomp}
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@inproceedings{KatzUnderstanding2017,

materials/sw18ebm.pdf

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research.md

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@@ -12,7 +12,7 @@ publications list, and consider contacting us directly or filing an issue with
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this page at
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[https://github.com/squaresLab/squaresLab.github.io](https://github.com/squaresLab/squaresLab.github.io).
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We try to be reasonably thorough, but note that this page does not attempt list every paper squaresLab has ever published; see [publications](/publications) for a complete list.
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We try to be reasonably thorough, but note that this page does not attempt to reference every paper squaresLab has ever published; see [publications](/publications) for a more complete list.
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## Program Transformation and Repair
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their performance and quality of created patches. We also develop approaches to
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automate other types of transformation, including API updates and migration. This work has produced
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frameworks and toolsets for automatic program transformation and repair, as well
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as datasets for its evaluation. You might be looking for:
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as datasets for its evaluation.
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{% capture transform_text %}
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* [S3 and JFix](https://xuanbachle.github.io/semanticsrepair/): semantics-based
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repair for Java programs.
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* [Static repair of framework directive violations](/publications/#coker21framefix)
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* [SOSrepair](/publications/AfzalSOSRepair19) (and its predecessor, [SearchRepair](/publications/#KeSearchRepair2015)) SearchRepair and SOSRepair extend and use semantic code search over large repositories of candidate code bases to produce high-quality bug patches.
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* [Crayons](/publications/#cruz22crayons), statically repairing locking API violations in the Linux kernel.
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* [SOSrepair](/publications/AfzalSOSRepair19) (and its predecessor, [SearchRepair](/publications/#KeSearchRepair2015)) SearchRepair and SOSRepair extend and use semantic code search over repositories of candidate code snippets to produce high-quality bug patches.
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* [Crayons](/publications/#cruz22crayons) statically repairs locking API violations in the Linux kernel.
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**Related Publications:**
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repositories, results, and reproduction instructions, as well as a historical
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list of largely GenProg-specific papers (through about 2016).
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Papers specific to GP-based repair are listed under search-based softwre engineering, below
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Papers analyzing or evaluating specific components of GP-based repair are (additionally) listed under search-based software engineering.
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{% endcapture %}
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{% endcapture %}
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Our interest in applying AI to software engineering started with search-based techniques. Much of our work in this space has been repair-specific, though we have also looked at the application of GP and related search-based approaches for self-adaptive systems and knowledge reuse at the model level. Relevant publications (for both code and models/plans, excluding those that are proposing new APR approaches) include:
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Our interest in applying AI to software engineering started with search-based techniques. Much of our work in this space has been repair-specific, though we have also looked at the application of GP and related search-based approaches for self-adaptive systems and knowledge reuse at the model level as well. Relevant publications (for both code and models/plans, excluding those that propose new APR approaches, with incidental contributions in SBSE algorithm design) include:
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<div id="sbseAccordian">
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</div>
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## Decompilation and reverse engineering
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## Tools for Humans
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**Related Publications:**
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- [A Study on the Use of IDE Features for Debugging](/publications/#AfzalMSRChallenge2018)
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- [A Deeper Look into Bug Fixes: Patterns, Replacements, Deletions, and Additions](/publications/#SotoMSRChallenge2016)
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{% capture decomp_papers %}
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{% bibliography --query @*[project~=decomp] %}
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{% endcapture %}
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Our work on improving developer experiences by integrating program analysis with AI includes a line of research on reverse engineering, specifically to improve decompilation and decompiler output.
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<div id="decompAccordian">
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<div class="card">
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<div class="card-header" id="headingDecomp">
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<h5 class="mb-0">
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<button class="btn btn-link" data-toggle="collapse" data-target="#collapseDecomp" aria-expanded="true" aria-controls="collapseDecomp">
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Decompilation and reverse engineering
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</button>
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</h5>
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</div>
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<div id="collapseDecomp" class="collapse" aria-labelledby="headingDecomp" data-parent="#decompAccordian">
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<div class="card-body">{{ decomp_papers | markdownify }}</div>
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</div>
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</div>
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</div>
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## AI and LLMs
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{% capture ai_papers %}
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{% bibliography --query @*[project~=ai] %}
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{% endcapture %}
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Our work often leverages advances in AI to develop new development tools and QA approaches to improve testing and program transformation. (This list excludes SBSE-specific work.)
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<div id="aiAccordian">
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<div class="card">
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<div class="card-header" id="headingAi">
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<h5 class="mb-0">
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<button class="btn btn-link" data-toggle="collapse" data-target="#collapseAi" aria-expanded="true" aria-controls="collapseAi">
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AI and LLMs for SE
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</button>
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</h5>
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</div>
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<div id="collapseAi" class="collapse" aria-labelledby="headingAi" data-parent="#aiAccordian">
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<div class="card-body">{{ ai_papers | markdownify }}</div>
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</div>
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</div>
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</div>
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## Understanding Develop[ment/er] Practices
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#### Selected Developer Studies
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## Tools for Humans
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**Related Publications:**
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- [A Study on the Use of IDE Features for Debugging](/publications/#AfzalMSRChallenge2018)
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- [A Deeper Look into Bug Fixes: Patterns, Replacements, Deletions, and Additions](/publications/#SotoMSRChallenge2016)
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* [Framework Debugging](https://squareslab.github.io/materials/CokerQualitative2019.pdf): an investigation into the challenges of debugging framework application problems. One important finding was that in framework debugging, developers have a difficult time determining the correct way to implement a fix.
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* [Social Attributes on Commit Integration](https://squareslab.github.io/materials/AfzalMSRChallenge2018.pdf): a quick investigation on how the GitHub social attributes of developers can be used to predict if a commit will be accepted or not.
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* [Prioritizing Exceptions with Behavior Metrics](https://squareslab.github.io/materials/CokerBehavior2017.pdf): a study performed in collaboration with [ABB Inc.](https://new.abb.com) that recommended which exception to fix based on the next actions that users took with the tool after an exception occurred.

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