I am a postdoctoral researcher in the Software Engineering Group. I have been a PhD Candidate at the University of Bern in the Software Composition Group from January 2018-January 2022. Prior to this, I have done masters in software system from the Birla Institute of Technology and Science-Pilani During my masters, I have worked on “Software Fault Tree Analysis” which is a safety analysis technique to identify a software-related error in early design phase from UML model.
Research Interest
As the complexity of software system increase, it becomes more important to tackle the future problem in the early stages. To support developers in building these complex systems we require tools which can support rapid development, understanding the system, re-using the existing system, reduce testing effort, and automate various tasks for them. My research interest lies in supporting developers with various tools in their IDEs. Currently I am working on gathering and identifying developers information needs regarding code comments for program comprehensions tasks.
Developing smart IDEs | Object-Oriented Programming |
Improving code documentation | Code comments analysis |
Mining repositories |
Project Proposals
Finished Thesis projects
Past Proposals
Teaching Activities
Contact Details
- Email: pooja.rani |at| inf.unibe.ch
- Telephone: +41 31 511 7639
- Address: University of Bern, Software Composition Group,
Room 106, Schützenmattstrasse 14, CH-3012 Bern - Webpage: http://scg.unibe.ch/staff/Pooja-Rani
Publications
2022
- Pooja Rani. Assessing Comment Quality in Object-Oriented Languages. PhD thesis, University of Bern, January 2022. PDF →
2021
- Pooja Rani. Speculative Analysis for Quality Assessment of Code Comments. In 2021 IEEE/ACM 43rd International Conference on Software Engineering: Companion Proceedings (ICSE-Companion), p. 299-303, 2021. DOI PDF →
- Pooja Rani, Sebastiano Panichella, Manuel Leuenberger, Mohammad Ghafari, and Oscar Nierstrasz. What do class comments tell us? An investigation of comment evolution and practices in Pharo Smalltalk. In Empirical Software Engineering 26(6) p. 1—49, 2021. DOI PDF →
- Mathias Birrer, Pooja Rani, Sebastiano Panichella, and Oscar Nierstrasz. Makar: A Framework for Multi-source Studies based on Unstructured Data. In 2021 IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), p. 577-581, 2021. DOI PDF →
- Pooja Rani, Sebastiano Panichella, Manuel Leuenberger, Andrea Di Sorbo, and Oscar Nierstrasz. How to Identify Class Comment Types? A Multi-language Approach for Class Comment Classification. In Journal of Systems and Software 181 p. 111047, 2021. DOI PDF →
- Pooja Rani, Mathias Birrer, Sebastiano Panichella, Mohammad Ghafari, and Oscar Nierstrasz. What Do Developers Discuss about Code Comments?. In 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM), 2021. DOI PDF →
- Pooja Rani, Suada Abukar, Nataliia Stulova, Alexander Bergel, and Oscar Nierstrasz. Do Comments follow Commenting Conventions? A Case Study in Java and Python. In 2021 IEEE 21st International Working Conference on Source Code Analysis and Manipulation (SCAM), 2021. DOI PDF →
2018
- Pooja Rani. Software Analysis using Natural Language Queries. In Seminar Series on Advanced Techniques \& Tools for Software Evolution (SATToSE), 2018. PDF →