Morteza Zakeri Nasrabadi

According to our database, Morteza Zakeri Nasrabadi authored at least 18 papers between 2018 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

Testability-driven development: An improvement to the TDD efficiency.

Saeed Parsa, Morteza Zakeri Nasrabadi, Burak Turhan

Comput. Stand. Interfaces, 2025

2024

Dynamic domain testing with multi-agent Markov chain Monte Carlo method.

Roshan Golmohammadi, Saeed Parsa, Morteza Zakeri Nasrabadi

Soft Comput., July, 2024

Natural language requirements testability measurement based on requirement smells.

Morteza Zakeri Nasrabadi, Saeed Parsa

Neural Comput. Appl., July, 2024

Supporting single responsibility through automated extract method refactoring.

Alireza Ardalani, Saeed Parsa, Morteza Zakeri Nasrabadi, Alexander Chatzigeorgiou

Empir. Softw. Eng., February, 2024

Measuring and improving software testability at the design level.

Morteza Zakeri Nasrabadi, Saeed Parsa, Sadegh Jafari

Inf. Softw. Technol., 2024

Multi-type requirements traceability prediction by code data augmentation and fine-tuning MS-CodeBERT.

Ali Majidzadeh, Mehrdad Ashtiani, Morteza Zakeri Nasrabadi

Comput. Stand. Interfaces, 2024

2023

A systematic literature review on source code similarity measurement and clone detection: Techniques, applications, and challenges.

Morteza Zakeri Nasrabadi, Saeed Parsa, Mohammad Ramezani, Chanchal Roy, Masoud Ekhtiarzadeh

J. Syst. Softw., October, 2023

Method name recommendation based on source code metrics.

Saeed Parsa, Morteza Zakeri Nasrabadi, Masoud Ekhtiarzadeh, Mohammad Ramezani

J. Comput. Lang., January, 2023

A Systematic Literature Review on the Code Smells Datasets and Validation Mechanisms.

Morteza Zakeri Nasrabadi, Saeed Parsa, Ehsan Esmaili, Fabio Palomba

ACM Comput. Surv., 2023

Mitigating Backdoors within Deep Neural Networks in Data-limited Configuration.

Soroush Hashemifar, Saeed Parsa, Morteza Zakeri Nasrabadi

CoRR, 2023

2022

An automated extract method refactoring approach to correct the long method code smell.

Mahnoosh Shahidi, Mehrdad Ashtiani, Morteza Zakeri Nasrabadi

J. Syst. Softw., 2022

Learning to predict test effectiveness.

Morteza Zakeri Nasrabadi, Saeed Parsa

Int. J. Intell. Syst., 2022

Front Cover: International Journal of Intelligent Systems, Volume 37 Issue 8 August 2022.

Morteza Zakeri Nasrabadi, Saeed Parsa

Int. J. Intell. Syst., 2022

An ensemble meta-estimator to predict source code testability.

Morteza Zakeri Nasrabadi, Saeed Parsa

Appl. Soft Comput., 2022

2021

Format-aware learn&fuzz: deep test data generation for efficient fuzzing.

Morteza Zakeri Nasrabadi, Saeed Parsa, Akram Kalaee

Neural Comput. Appl., 2021

A comprehensive survey on non-invasive wearable bladder volume monitoring systems.

Morteza Zakeri Nasrabadi, Hamideh Tabibi, Mahsa Salmani, Mahdieh Torkashvand, Eisa Zarepour

Medical Biol. Eng. Comput., 2021

Learning to Predict Software Testability.

Morteza Zakeri Nasrabadi, Saeed Parsa

Proceedings of the 26th International Computer Conference, Computer Society of Iran, 2021

2018

Neural Fuzzing: A Neural Approach to Generate Test Data for File Format Fuzzing.

Morteza Zakeri Nasrabadi, Saeed Parsa, Akram Kalaee

CoRR, 2018