The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches

Reference : The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Ac...


	Document type :	Scientific journals : Article
	Discipline(s) :	Engineering, computing & technology : Computer science
	Focus Areas :	Security, Reliability and Trust
	To cite this reference:	http://hdl.handle.net/10993/54368

Title :	The Best of Both Worlds: Combining Learned Embeddings with Engineered Features for Accurate Prediction of Correct Patches
Language :	English
Author, co-author :	Tian, Haoye [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX]
	Liu, Kui [Huawei]
	Li, Yinghua [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX]
	Kabore, Abdoul Kader [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX]
	Koyuncu, Anil [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX >]
	Habib, Andrew [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX]
	Li, Li [Monash University]
	Wen, Junhao [Chongqing University]
	Klein, Jacques [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX]
	Bissyande, Tegawendé François D Assise [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > TruX >]
Publication date :	2022
Journal title :	ACM Transactions on Software Engineering and Methodology
Publisher :	Association for Computing Machinery (ACM)
Peer reviewed :	Yes
Country :	United States
Keywords :	[en] Program repair ; Patch overfitting ; Patch correctness
Permalink :	http://hdl.handle.net/10993/54368
Framework Programme / European Project :	H2020 ; 949014 - NATURAL - Natural Program Repair

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Open access	2023_TOSEM_Panther__Haoye_.pdf		Author preprint	2.36 MB	View/Open

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