Rahul Krishna
Rahul Krishna
Postdoctoral researcher, Department of Computer Science, Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
Too much automation? The bellwether effect and its implications for transfer learning
R Krishna, T Menzies, W Fu
Proceedings of the 31st IEEE/ACM International Conference on Automated …, 2016
502016
Bellwethers: A Baseline Method For Transfer Learning
R Krishna, T Menzies
IEEE Transactions on Software Engineering, 2018
452018
We don't need another hero? The impact of heroes on software development
A Agrawal, A Rahman, R Krishna, A Sobran, T Menzies
Proceedings of the 40th International Conference on Software Engineering …, 2018
362018
"Sampling" as a Baseline Optimizer for Search-based Software Engineering
J Chen, V Nair, R Krishna, T Menzies
IEEE Transactions on Software Engineering, 2018
362018
Hyperparameter optimization for effort estimation
T Xia, R Krishna, J Chen, G Mathew, X Shen, T Menzies
arXiv preprint arXiv:1805.00336, 2018
302018
The seacraft repository of empirical software engineering data
T Menzies, R Krishna, D Pryor
Retrieved March, 2017
29*2017
Entropy based Binary Particle Swarm Optimization and classification for ear detection
MR Ganesh, R Krishna, K Manikantan, S Ramachandran
Engineering Applications of Artificial Intelligence 27, 115-128, 2014
282014
Applications of psychological science for actionable analytics
D Chen, W Fu, R Krishna, T Menzies
2018 ACM 26th Symposium on the Foundations of Software Engineering (ECSE/FSE …, 2018
212018
What is the connection between issues, bugs, and enhancements? Lessons learned from 800+ software projects
R Krishna, A Agrawal, A Rahman, A Sobran, T Menzies
Proceedings of the 40th International Conference on Software Engineering …, 2018
20*2018
Less is more: Minimizing code reorganization using XTREE
R Krishna, T Menzies, L Layman
Information and Software Technology 88, 53-66, 2017
202017
Characterizing the influence of continuous integration: Empirical results from 250+ open source and proprietary projects
A Rahman, A Agrawal, R Krishna, A Sobran
Proceedings of the 4th ACM SIGSOFT International Workshop on Software …, 2018
16*2018
Whence to learn? transferring knowledge in configurable systems using beetle
R Krishna, V Nair, P Jamshidi, T Menzies
IEEE Transactions on Software Engineering, 2020
14*2020
The 'BigSE' Project: Lessons Learned from Validating Industrial Text Mining
R Krishna, Z Yu, A Agrawal, M Dominguez, D Wolf
Big Data Software Engineering (BIGDSE), 2016 IEEE/ACM 2nd International …, 2016
132016
An Adaptive blind video watermarking technique based on SD-BPSO and DWT-SVD
P Prathik, R Krishna, RA Nafde, K Shreedarshan
2013 International Conference on Computer Communication and Informatics, 1-6, 2013
122013
Learning actionable analytics from multiple software projects
R Krishna, T Menzies
Empirical Software Engineering 25 (5), 3468-3500, 2020
9*2020
iSENSE: Completion-aware crowdtesting management
J Wang, Y Yang, R Krishna, T Menzies, Q Wang
2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE …, 2019
82019
Deep learning based vulnerability detection: Are we there yet
S Chakraborty, R Krishna, Y Ding, B Ray
IEEE Transactions on Software Engineering, 2021
62021
Strengthening the evidence that attack surfaces can be approximated with stack traces
C Theisen, R Krishna, L Williams
North Carolina State University Department of Computer Science TR2015–10 …, 2015
62015
MTFuzz: Fuzzing with a Multi-Task Neural Network
D She, R Krishna, L Yan, S Jana, B Ray
2020 ACM 28th Symposium on the Foundations of Software Engineering (ECSE/FSE), 2020
52020
Actionable=Cluster+Contrast?
R Krishna, T Menzies
Automated Software Engineering Workshop (ASEW), 2015 30th IEEE/ACM …, 2015
32015
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