Rahul Krishna

IBM Research (Application Modernization)

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Research Staff Member, IBM Research, NY.

imralk AT gmail DOT com

I work in the intersection of Machine Learning and Programming Languages for modernizing and mainitaining cloud-native applications. Prior to this, I was Post doctoral fellow at Columbia University working with Dr. Baishakhi Ray where my research explored the ways in which Machine Learning can be used to trigger, detect, and repair various problem across the software lifecycle.

I obtained my PhD at NC State University, guided by Dr. Tim Menzies. I worked on actionable analytics for software engineering. I created algorithms that go beyond prediction to provide insights that might help developers make better decisions. I focused on data mining approaches (e.g., transfer learning) that can create insights even when there isn’t enough data.

news

Jan 24, 2022 Unicorn has been acepted EuroSys’22
Nov 15, 2021 A tutorial on refactoring application to microservices with mono2micro was presented in ASE.
Aug 26, 2021 Deep Learning based Vulnerability Detection: Are We There Yet? has been published at TSE.
Jul 1, 2021 Mono2Micro has been accepted at FSE ‚Äė21 Industry track.
Mar 1, 2021 Joined IBM as a Research Staff Member in the Hybrid Cloud Division.

selected publications

  1. EuroSys
    Unicorn: Reasoning about Configurable System Performance through the lens of Causality
    Iqbal, Md Shahriar,  Krishna, Rahul, Javidian, Mohammad Ali, Ray, Baishakhi, and Jamshidi, Pooyan
    In The European Conference on Computer Systems (EuroSys). 2022
  2. FSE
    Mono2Micro: A practical and effective tool for decomposing monolithic Java applications to microservices
    Kalia, Anup K, Xiao, Jin,  Krishna, Rahul, Sinha, Saurabh, Vukovic, Maja, and Banerjee, Debasish
    In Proceedings of the 29th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE). 2021
  3. TSE
    Deep learning based vulnerability detection: Are we there yet?
    Chakraborty, Saikat,  Krishna, Rahul, Ding, Yangruibo, and Ray, Baishakhi
    IEEE Transactions on Software Engineering. 2021
  4. FSE
    MTFuzz: Fuzzing with a Multi-Task Neural Network
    She, Dongdong,  Krishna, Rahul, Yan, Lu, Jana, Suman, and Ray, Baishakhi
    In Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ECSE/FSE). 2020
  5. TSE
    ConEx: Efficient exploration of big-data system configurations for better performance
    Krishna, Rahul, Tang, Chong, Sullivan, Kevin, and Ray, Baishakhi
    IEEE Transactions on Software Engineering 2020
  6. TSE
    Whence to learn? transferring knowledge in configurable systems using beetle
    Krishna, Rahul, Nair, Vivek, Jamshidi, Pooyan, and Menzies, Tim
    IEEE Transactions on Software Engineering 2020