Zobrazeno 1 - 10
of 87
pro vyhledávání: '"Devanbu, Prem"'
Autor:
Spiess, Claudio, Gros, David, Pai, Kunal Suresh, Pradel, Michael, Rabin, Md Rafiqul Islam, Alipour, Amin, Jha, Susmit, Devanbu, Prem, Ahmed, Toufique
Machine learning models are widely used but can also often be wrong. Users would benefit from a reliable indication of whether a given output from a given model should be trusted, so a rational decision can be made whether to use the output or not. F
Externí odkaz:
http://arxiv.org/abs/2402.02047
Pre-trained language models are effective in a variety of natural language tasks, but it has been argued their capabilities fall short of fully learning meaning or understanding language. To understand the extent to which language models can learn so
Externí odkaz:
http://arxiv.org/abs/2306.11943
Autor:
Hussain, Aftab, Rabin, Md Rafiqul Islam, Ahmed, Toufique, Ayoobi, Navid, Xu, Bowen, Devanbu, Prem, Alipour, Mohammad Amin
In this work, we study literature in Explainable AI and Safe AI to understand poisoning of neural models of code. In order to do so, we first establish a novel taxonomy for Trojan AI for code, and present a new aspect-based classification of triggers
Externí odkaz:
http://arxiv.org/abs/2305.03803
In this 4-page manuscript we discuss the problem of long-term AI Safety from a Software Engineering (SE) research viewpoint. We briefly summarize long-term AI Safety, and the challenge of avoiding harms from AI as systems meet or exceed human capabil
Externí odkaz:
http://arxiv.org/abs/2304.14597
The relationship of comments to code, and in particular, the task of generating useful comments given the code, has long been of interest. The earliest approaches have been based on strong syntactic theories of comment-structures, and relied on textu
Externí odkaz:
http://arxiv.org/abs/2010.01410
Autor:
Devanbu, Prem, Dwyer, Matthew, Elbaum, Sebastian, Lowry, Michael, Moran, Kevin, Poshyvanyk, Denys, Ray, Baishakhi, Singh, Rishabh, Zhang, Xiangyu
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 conducted in co-location with the 34th IEEE/ACM International Conference
Externí odkaz:
http://arxiv.org/abs/2009.08525
Berger et al., published in TOPLAS 2019, is a critique of our 2014 FSE conference abstract and its archival version, the 2017 CACM paper: A Large-Scale Study of Programming Languages and Code Quality in Github. In their paper Berger et al. make acade
Externí odkaz:
http://arxiv.org/abs/1911.07393
Natural code is known to be very repetitive (much more so than natural language corpora); furthermore, this repetitiveness persists, even after accounting for the simpler syntax of code. However, programming languages are very expressive, allowing a
Externí odkaz:
http://arxiv.org/abs/1910.03704
Code corpora, as observed in large software systems, are now known to be far more repetitive and predictable than natural language corpora. But why? Does the difference simply arise from the syntactic limitations of programming languages? Or does it
Externí odkaz:
http://arxiv.org/abs/1806.02437
Autor:
Larios Vargas, E., Aniche, Maurício, Treude, Christoph, Bruntink, Magiel, Gousios, G., Devanbu, Prem, Cohen, Myra, Zimmermann, Thomas
Publikováno v:
Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering
ACM (Association for Computing Machinery) Conference Proceedings: Engineering Conference and Symposium on the Foundations of Software Engineering(ESEC/FSE’20),November8–13,2020,VirtualEvent,USA.ACM,New York,NY,USA,12pages
ESEC/FSE 2020-Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering: The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
ESEC/FSE 2020-Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
ESEC/SIGSOFT FSE
ACM (Association for Computing Machinery) Conference Proceedings: Engineering Conference and Symposium on the Foundations of Software Engineering(ESEC/FSE’20),November8–13,2020,VirtualEvent,USA.ACM,New York,NY,USA,12pages
ESEC/FSE 2020-Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering: The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering
ESEC/FSE 2020-Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering
ESEC/SIGSOFT FSE
The selection of third-party libraries is an essential element of virtually any software development project. However, deciding which libraries to choose is a challenging practical problem. Selecting the wrong library can severely impact a software p
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::373978a9ccaca43179c099bf4a924da3
http://resolver.tudelft.nl/uuid:dfcd6e6b-cb63-4d64-98de-194b419d3cd3
http://resolver.tudelft.nl/uuid:dfcd6e6b-cb63-4d64-98de-194b419d3cd3