Saikat Dutta
About Me
I am an incoming Tenure-Track Assistant Professor in the Department of Computer Science at Cornell University, starting Fall 2024!

Prospective students: I am looking for skilled and motivated undergraduates, PhD students, and postdocs to join my group. If you are interested in working with me at the intersection of Software Engineering and Machine Learning, please drop me an email and apply to the Cornell CS PhD program.

I am currently a Postdoctoral Researcher in the Computer & Information Science Department at the University of Pennsylvania, working with Mayur Naik. I obtained my PhD in Computer Science from the University of Illinois Urbana-Champaign in 2023. You can find my CV here.

New:
Are you an undergraduate student interested in research? Please apply to the 2024 UIUC+ Summer Undergraduate Research in Software Engineering! Open to international students!
Research Interests
My research interests are at the intersection of Software Engineering and Machine Learning. I am particularly interested in 1) developing novel techniques and tools to improve the reliability of Machine Learning-based systems, and 2) leveraging Machine Learning to address challenging tasks in Software Engineering.

My research focuses on following themes: Apart from these topics, I also developed novel inference algorithms and robustness analyses for probabilistic programming [UAI 2023] [ATVA 2021].
News
  • New:
    Passed PhD Final Defense! Find my dissertation here.
  • New:
    Our paper ASTRA: Understanding the Practical Impact of Robustness for Probabilistic Programs has been accepted to UAI 2023!
  • New:
    Our paper Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests has been accepted to ICSE 2023!
  • Our paper To Seed or Not to Seed? An Empirical Analysis of Usage of Seeds for Testing in Machine Learning Projects has been accepted to ICST 2022!
  • Our paper InspectJS: Leveraging Code Similarity and User-Feedback for Effective Taint Specification Inference for JavaScript has been accepted to ICSE-SEIP 2022!
  • More News
  • Our paper SixthSense: Debugging Convergence Problems in Probabilistic Programs via Program Representation Learning has been accepted to FASE 2022!
  • Our paper AQUA: Automated Quantized Inference for Probabilistic Programs has been accepted to ATVA 2021!
  • Our paper TERA: Optimizing Stochastic Regression Tests in Machine Learning Projects has been accepted to ISSTA 2021!
  • Our paper FLEX: Fixing Flaky Tests in Machine-Learning Projects by Updating Assertion Bounds has been accepted to ESEC/FSE 2021!
  • I will be interning at Amazon Web Services (AWS) with the Automated Reasoning Group (ARG) for Summer 2021!
  • Our paper on Detecting Flaky Tests in Probabilistic and Machine Learning Applications was accepted to ISSTA 2020!
  • I will be interning at Microsoft Research, Redmond with the RISE group for Summer 2020!
    Looking forward to it!
  • Awarded Facebook PhD Fellowship 2020
    Thanks Facebook!
  • Our paper, Storm: Program Reduction for Testing and Debugging Probabilistic Programming Systems, has been accepted to FSE 2019
  • Selected for 3M Foundation Fellowship 2018-19
  • Our paper on ProbFuzz, "Testing Probabilistic programming systems" has been accepted to FSE 2018
  • Attended PLDI 2018 at Philadelphia, USA (20-22 June, 2018)
  • Our recent work on Automated Sensitivity Analysis was published in IEEE TSE Volume 43, Issue 12
  • Attended Midwest Programming Language Summit 2017 at Bloomington, Indiana
  • Attended Automated Software Engineering Conference (ASE 2017) at UIUC
Selected Publications
Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests
45th International Conference on Software Engineering (ICSE 2023)
Steven Xia, Saikat Dutta, Sasa Misailovic, Darko Marinov, and Lingming Zhang
FLEX: Fixing Flaky Tests in Machine-Learning Projects by Updating Assertion Bounds
29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2021)
Saikat Dutta, August Shi, and Sasa Misailovic
Testing Probabilistic Programming Systems
26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2018)
Saikat Dutta, Owolabi Legunsen, Zixin Huang, Sasa Misailovic
All Publications
2024
Debugging Convergence Problems in Probabilistic Programs via Program Representation Learning with SixthSense
The International Journal on Software Tools for Technology Transfer (STTT 2024)
Zixin Huang, Saikat Dutta, and Sasa Misailovic
Extended version of the FASE 2022 paper
2023
Understanding the Effectiveness of Large Language Models in Detecting Security Vulnerabilities
Avishree Khare, Saikat Dutta, Ziyang Li, Alaia Solko-Breslin, Rajeev Alur, Mayur Naik
Randomness-Aware Testing of Machine Learning-based Systems
Ph.D. Dissertation, University of Illinois Urbana-Champaign, July 2023
Saikat Dutta
ASTRA: Understanding the Practical Impact of Robustness for Probabilistic Programs
39th Conference on Uncertainty in Artificial Intelligence (UAI 2023)
Zixin Huang, Saikat Dutta, and Sasa Misailovic
Balancing Effectiveness and Flakiness of Non-Deterministic Machine Learning Tests
45th International Conference on Software Engineering (ICSE 2023)
Steven Xia, Saikat Dutta, Sasa Misailovic, Darko Marinov, and Lingming Zhang
2022
To Seed or Not to Seed? An Empirical Analysis of Usage of Seeds for Testing in Machine Learning Projects
15th IEEE International Conference on Software Testing, Verification and Validation (ICST 2022)
Saikat Dutta, Anshul Arunachalam and Sasa Misailovic
InspectJS: Leveraging Code Similarity and User-Feedback for Effective Taint Specification Inference for JavaScript
44th International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP 2022)
Saikat Dutta, Diego Garbervetsky, Shuvendu Lahiri, Max Schäfer
SixthSense: Debugging Convergence Problems in Probabilistic Programs via Program Representation Learning
25th International Conference on Fundamental Approaches to Software Engineering (FASE 2022)
Saikat Dutta, Zixin Huang, and Sasa Misailovic
2021
Automated Quantized Inference for Probabilistic Programs with AQUA
Innovations in Systems and Software Engineering: A NASA Journal (ISSE NASA)
Zixin Huang, Saikat Dutta, and Sasa Misailovic
Extended version of our ATVA 2021 paper
AQUA: Automated Quantized Inference for Probabilistic Programs
19th International Symposium on Automated Technology for Verification and Analysis (ATVA 2021)
Zixin Huang, Saikat Dutta, and Sasa Misailovic
FLEX: Fixing Flaky Tests in Machine-Learning Projects by Updating Assertion Bounds
29th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2021)
Saikat Dutta, August Shi, and Sasa Misailovic
TERA: Optimizing Stochastic Regression Tests in Machine Learning Projects
30th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2021)
Saikat Dutta, Jeeva Selvam, Aryaman Jain, and Sasa Misailovic
2020
Detecting Flaky Tests in Probabilistic and Machine Learning Applications
29th ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA 2020)
Saikat Dutta, August Shi, Rutvik Choudhary, Zhekun Zhang, Aryaman Jain, and Sasa Misailovic
2019
Storm: Program Reduction for Testing and Debugging Probabilistic Programming Systems
27th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2019)
Saikat Dutta, Wenxian Zhang, Zixin Huang, Sasa Misailovic
2018
Testing Probabilistic Programming Systems
26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (FSE 2018)
Saikat Dutta, Owolabi Legunsen, Zixin Huang, Sasa Misailovic
2013-17
AutoSense: A Framework for Automated Sensitivity Analysis of Program Data
IEEE Transactions on Software Engineering (TSE 2017)
Bernard Nongpoh, Rajarshi Ray, Saikat Dutta, Ansuman Banerjee
Enhancing branch prediction using software evolution
10th IEEE International Conference on Networking, Architecture, and Storage (NAS 2015)
Saikat Dutta, Moumita Das, Ansuman Banerjee
A New Approach for Minimal Environment Construction for Modular Property Verification
24th Asian Test Symposium (ATS 2015)
Saikat Dutta, Soumi Chattopadhyay, Ansuman Banerjee, Pallab Dasgupta
A Framework for Fast Service Verification and Query Execution for Boolean Service Rules>
9th Asia-Pacific Services Computing Conference (APSCC 2015)
Soumi Chattopadhyay, Saikat Dutta, Ansuman Banerjee
Daikon to Prioritize and Group Unit Bugs
Formal Aspects of Component Software - 10th International Symposium (FACS 2013)
Nehul Jain, Saikat Dutta, Ansuman Banerjee, Anil K. Ghosh, Lihua Xu, Huibiao Zhu
Service
ASE 2024 Program Committee
MLSYS 2024 Program Committee
TSE 2022 Reviewer
PLDI 2021 Artifact Evaluation Committee
OOPSLA 2020 Artifact Evaluation Committee