Jibesh Patra - Software Lab - Department of Computer Science - TU Darmstadt

Jibesh Patra

TU Darmstadt
Mornewegstraße 32, room 4.3.05
64295 Darmstadt
E-mail: jibesh.patra@crisp-da.de
Telephone number: +49-6151-1622393

About me

I am a Computer Science Ph.D. student at TU Darmstadt advised by Prof. Dr. Michael Pradel. My current research interest is on the reliability and correctness of JavaScript programs.

Education

March 2015 - Present Ph.D. Student at TU Darmstadt, Germany
2013 Masters in Computer Science, NIT Durgapur, India
2009 Bachelor in Computer Science, Bankura Unnayani Institute of Engineering, India

Research Work

ConflictJS: Finding and Understanding Conflicts Between JavaScript Libraries, Jibesh Patra, Pooja N. Dixit, Michael Pradel. ICSE 2018 [pdf]
Automatically Reducing Tree-Structured Test Inputs, Satia Herfert, Jibesh Patra, Michael Pradel. ASE 2017 [pdf]
Learning to Fuzz: Application-Independent Fuzz Testing with Probabilistic, Generative Models of Input Data, Jibesh Patra, Michael Pradel. Technical Report, 2016 [pdf]

Social

Last updated 22 December, 2017

News and Events

01/2019: Our study of obfuscated and minified JavaScript will be presented at The Web Conference 2019 (formerly known as WWW). Congrats to Philippe and Cristian!

01/2019: Marija has successfully defended her Ph.D. thesis on actionable performance analyses for improving software performance.

01/2019: Group retreat in snowy Stuttgart.

12/2018: Our work on NL2Type, which predicts type signatures from natural language information, will appear at ICSE'19. Congrats to Rabee and Jibesh!

11/2018: We are moving: Starting from fall 2019, the Software Lab will be at University of Stuttgart, where Michael has accepted a position as full professor.

11/2018: Daniel receives the Datenlotsen Award (2,500 Euro) for his master thesis (see paper at FSE'18). Congrats!

11/2018: Our paper on Wasabi has been accepted at ASPLOS'19.

9/2018: Releasing Wasabi, the first dynamic analysis framework for WebAssembly (paper).

7/2018: Two new papers: Our work on studying how many of all bugs are detected by static bug detectors and our paper on finding thread-safe classes via machine learning have been accepted at ASE'18.

6/2018: Two papers accepted at OOPSLA'18! One on deep learning to find bugs and one on test generation for higher-order functions.

6/2018: New paper at FSE 2018 on differential testing of debuggers.

6/2018: Our work on change-aware dynamic analysis will be presented at ICSME 2018.

5/2018: Our work on ReDoS vulnerabilities in JavaScript-based web servers has been accepted at USENIX Security 2018.

2/2018: Our work on finding conflicts between JavaScript libraries will be presented at ICSE'18.

11/2017: Our paper on synthesizing programs that expose performance bottlenecks will appear at CGO'18.

10/2017: Our work on preventing code injection attacks on Node.js will appear at NDSS'18.