Publications

An up-to-date list of my publications:

Journal (ISI)

  • Zakeri-Nasrabadi, M., Parsa, S., Ramezani, M. , Roy C. K., & Ekhtiarzadeh, M., (2023). A systematic literature review on source code similarity measurement and clone detection: Techniques, applications, and challenges Journal of Systems and Software, 111796. https://doi.org/10.1016/j.jss.2023.111796

  • Zakeri-Nasrabadi, M., Parsa, S., Esmaili, E., & Palomba, F. (2023). A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms. Journal of Computer Languages, 74, 101177. https://dl.acm.org/doi/abs/10.1145/3596908

  • Parsa, S., Zakeri-Nasrabadi, M., Ekhtiarzadeh, M., & Ramezani, M. (2023). Method name recommendation based on source code metrics. Journal of Computer Languages, 74, 101177. https://doi.org/10.1016/j.cola.2022.101177

  • Zakeri-Nasrabadi, M., & Parsa, S. (2022). An ensemble meta-estimator to predict source code testability. Applied Soft Computing, 129, 109562. https://doi.org/10.1016/j.asoc.2022.109562

  • Shahidi, M., Ashtiani, M., & Zakeri-Nasrabadi, M. (2022). An automated extract method refactoring approach to correct the long method code smell. Journal of Systems and Software, 187, 111221. https://doi.org/10.1016/j.jss.2022.111221

  • Zakeri-Nasrabadi, M, Parsa, S. (2021). Learning to predict test effectiveness. IInternational Journal of Intelligent Systems, 37: 4363- 4392.  https://doi.org/10.1002/int.22722

  • Zakeri-Nasrabadi, M., Tabibi, H., Salmani, M., Torkashvand, M., & Zarepour, E. (2021). A comprehensive survey on non-invasive wearable bladder volume monitoring systems. Medical & Biological Engineering & Computing, 59(7), 1373-1402. https://doi.org/10.1007/s11517-021-02395-x

  • Zakeri-Nasrabadi, M., Parsa, S., & Kalaee, A. (2021). Format-aware learn&fuzz: deep test data generation for efficient fuzzing. Neural Computing and Applications, 33(5), 1497-1513. https://doi.org/10.1007/s00521-020-05039-7

Conference

  • Majidzadeh, A., Ashtiani, M., & Zakeri-Nasrabadi, M. (2023). Code data augmentation to improve language model’s performance in requirement to code traceability link recovery. In Proceedings of the 9th International Conference on Web Research, Tehran, 2023. University of Science and Culture. https://civilica.com/doc/1672065/

  • Zakeri-Nasrabadi, M. , & Parsa, S. (2021). Learning to predict software testability. In 26th International Computer Conference, Computer Society of Iran. Tehran: IEEE. https://doi.org/10.1109/CSICC52343.2021.9420548

  • Zakeri-Nasrabadi, Z., & Zakeri-Nasrabadi, M. (2019). Analysis social phenomena using machine learning techniques: a mixed research framework. In The first conference on artificial intelligence and soft computing in humanities (AISCH-2019). Retrieved from http://aisch.atu.ac.ir/paper?manu=106226

Journal (ISC)

Theses

Ph.D. dissertation

New (September 2022): An early view of my Ph.D. dissertation online appendix is now available at https://m-zakeri.github.io/PhD.

Master thesis

In my M.Sc. thesis, I designed and built IUST-DeepFuzz, a file format fuzzer and provided IUST-PDFCorpus, a large dataset of PDF files and PDF data objects. IUST-DeepFuzz can automatically learn the grammar (structure) of a given input file, then generate and fuzz various test data based on the learned model and some mutation-based methods. You can find all relevant information about my M.Sc. thesis on the IUST-DeepFuzz GitHub repository.

Bachelor project

In my B.Sc. project, I worked on agent-oriented software engineering and developed a multi-agent system to participate in the multi-agent programming contest (MAPC). Unfortunately, the competitions did not hold in the year 2014, for the technical reasons raised by the new scenario, and our team could not participate in the competitions. However, MAPC is alive for me and my teammates. Hence, our final project reports is kept in draft version to be updated ASAP:)

  • My B.Sc. Project Report (draft version) [www]

Find more on IUST course materials.

Research profiles