I am a Ph.D. student in the Thomas Lord Department of Computer Science,University of Southern California (USC), working in the Software Quality Lab (SQL Lab), supervised by Prof. William G.J. Halfond. I received my undergraduate degree in B.Sc. in Software Engineering degree at University of Dhaka in 2017 supervised by Prof. Kazi Muheymin-Us-Sakib. I was a member of DSSE Research Group.
My research interests align in investigating novel methods merging Software Engineering, Program Analysis, Software Accessibility, and Software Testing for robust, secure software development. Bridging theory with practice through empirical studies and tool development to enhance software reliability and efficiency.
- Personal Pages: https://tawsif93.github.io
- Linkedin: https://www.linkedin.com/in/tawsif93
- Google Scholar: https://scholar.google.com/citations?user=1mBdQ04AAAAJ
- 2024.07: Β Participated in FSE'24
- 2024.04: Β ππ Our paper accepted by FSE 2024
- 2024.01: Β π Our Extended Abstract Poster accepted by ICSE 2024
- 2023.12: Β Participated as Student Volunteer in ESEC/FSE 2023
- 2023.10: Β Presented our paper in ICSME 2023
- 2023.10: Β Participated in ICSME'23, SCAM'23
- 2023.06: Β ππ Our paper accepted by ICSME 2023.
- 2022.08: Β Started my Ph.D. at USC.
- 2022.04: Β π Our paper accepted by SEKE 2022.
ICSE-Companion 2024
xNose: A Test Smell Detector for C#, Partha Protim Paul, Md Tonoy Akanda, Mohammed Raihan Ullah, Dipto Mondal, Nazia Sultana Chowdhury, Fazle M Tawsif et al.ICSME 2023
ScaleFix: An Automated Repair of UI Scaling Accessibility Issues in Android Applications, Ali S. Alotaibi, Paul T. Chiou, Fazle M Tawsif, William G.J. Halfond et al.SEKE 2022
Impact of Combining Syntactic and Semantic Similar- ities on Patch Prioritization while using the Insertion Mutation Operators, MR Ullah, NS Chowdhury, FM Tawsif et al.
PACMSE-FSE 2024
Mobile Bug Report Reproduction via Global Search on the App UI Model, Zhaoxu Zhang, Fazle Mohammed Tawsif, Komei Ryu, Tingting Yu, William GJ Halfond et al.JCS 2020
A Machine Learning Approach to Predict Movie Revenue Based on Pre-Released Movie Metadata, Mahmud, Q. I., Tawsif, F. M., Shuchi, N. Z., Mohaimen, A., Tasnim, A. et al.