Pooja Rani, Dr.
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Research Interests
My main research interest lies in the general area of Empirical Software Engineering (SE), Green Software Engineering, Natural Language Processing (NLP), and machine learning applied to SE. My primary research focuses on understanding developer coding practices and using that knowledge to build tools and techniques to assist developers in program comprehension, evolution, and maintenance activities.
Short Biography
I am a senior postdoctoral researcher in the Software Evaluation and Architecture Lab. Before joining SEAL, I was a senior postdoctoral researcher in the Zurich Empirical Software Engineering Team and postdoctoral researcher in the Software Engineering Group. I received my Ph.D. (with honors) in 2022 on the topic of "Assessing Comment Quality in Object-Oriented Languages" in the Software Composition Group at University of Bern under the supervision of Prof. Oscar Nierstrasz and co-supervision of Dr. Sebastiano Panichella.
I graduated with a Master's degree (M.E.) in Software Systems from Birla Institute of Technology and Science, Pilani Campus (BITS Pilani) in 2017. I have worked in the industry in various software engineering profiles. I have worked as a software engineer in Test in Samsung, as a researcher in VMware, and as a developer in People Interactive Ltd. I can say that I have witnessed a glimpse of the real software engineering process in various companies and in various profiles.
You can find more information about recent publications, teaching activtities, talks, and theses on my page.
Teaching
- Advanced Software Engineering (2025)
- Seminar: Advanced Software Engineering (BSc)(2025: Course administration and lectures)
- Seminar: Advanced Software Engineering (MSc)(2025: Course administration and lectures)
Projects (MSc/BSc Thesis and Master Project)
Please find the available projects listed below. If none of the projects interests you, but the topics in general interest you, feel free to contact me.
- Comment analysis
- When do developers find writing code comments in source code worthwhile in the era of AI?
- Ensuring comment/documentation quality
- Github Comment Analysis plugin
- Green software engineering
- Design Science for embedding energy awareness into developer workflows
- How to find energy anti-patterns in source code?
- Developing a green IT dashboard for IDEs
- Developing a sustainability-aware LLM chatbot
- Object-oriented breakpoints for Python or Java
- Polyglot programming
- How to find polyglot smells?
- Do prior programming languages influence the next one?