publications

2024

1. A study on classifying Stack Overflow questions based on difficulty by utilizing contextual features

   Maliha Noushin Raida, Zannatun Naim Sristy, Nawshin Ulfat, and 3 more authors

   Journal of Systems and Software, 2024

   DOI

2023

1. Effectiveness of Data Augmentation and Ensembling Using Transformer-Based Models for Sentiment Analysis: Software Engineering Perspective

   Zubair Tusar., Sadat Sharfuddin., Muhtasim Abid., and 2 more authors

   2023

   DOI
2. The Ugly Side of Stack Overflow: An In-depth Exploration of the Social Dynamics of New Users’ Engagement and Community Perception of Them

   Abdullah Al Jobair, Suzad Mohammad, Zahin Raidah Maisha, and 2 more authors

   In Evaluation of Novel Approaches to Software Engineering, 2023

   Abs

   Stack Overflow (SO) is the most popular knowledge-sharing platform for novice to experienced programmers. It is growing gradually with its rapidly expanding community of new users. However, the hostile environment towards new users has been a burning issue for several years, which hinders the enhancement of a skillful community. In this research, we study a subset of users registered in the last 45 days or have a reputation of less than or equal to 50 and term them “neophytes.” We study if neophytes experience an unwelcoming environment when cooperating on Stack Overflow; if so, we determine the potential reasons behind this problem and determine how much adverse situation affects neophytes’ activity. According to our findings, neophytes face difficulty while cooperating on the platform and 9 potential reasons (such as deletion or closing of posts, no answer to the post, rude comments, misconception of SO rules and culture, and steep learning curve) are responsible behind this difficulty. Moreover, the activeness of regular users is 6.71 times more than the neophytes who face adverse situations. It depicts that facing adverse situations reduces the activeness of neophytes. The study aims to address the problems and pathways to maintain a friendly environment for all. The findings of our research study can be used to develop guidance in making the SO community more user-friendly and aid researchers in future studies to improve the Stack Overflow environment.

2022

1. The Integrity of Source Code Commenting: Benchmark Dataset and Empirical Analysis

   Maksuda Islam, Mohammad Safayat Hossen, Ahsanul Haque, and 2 more authors

   2022
2. An Empirical Study on Neophytes of Stack Overflow: How Welcoming the Community is towards Them

   Abdullah Al Jobair., Suzad Mohammad., Zahin Raidah Maisha., and 2 more authors

   2022

   DOI

2021

1. Use of relevancy and complementary information for discriminatory gene selection from high-dimensional gene expression data

   Md Nazmul Haque, Sadia Sharmin, Amin Ahsan Ali, and 2 more authors

   PLOS ONE, 2021

   DOI

2020

1. An Ensemble Approach to Detect Code Comment Inconsistencies using Topic Modeling.

   Fazle Rabbi, Md Nazmul Haque, Md Eusha Kadir, and 2 more authors

   In SEKE, 2020

2019

1. Nurse care activity recognition: a GRU-based approach with attention mechanism

   Md. Nazmul Haque, Mahir Mahbub, Md. Hasan Tarek, and 2 more authors

   In Adjunct Proceedings of the 2019 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2019 ACM International Symposium on Wearable Computers, London, United Kingdom, 2019

   DOI
2. GRU-based Attention Mechanism for Human Activity Recognition

   Md. Nazmul Haque, M. Tanjid Hasan Tonmoy, Saif Mahmud, and 3 more authors

   In 2019 1st International Conference on Advances in Science, Engineering and Robotics Technology (ICASERT), 2019

   DOI

2018

1. Bug Severity Classification Based on Class-Membership Information

   Sayeda Shamma Alia, Md. Nazmul Haque, Sadia Sharmin, and 2 more authors

   In 2018 Joint 7th International Conference on Informatics, Electronics & Vision (ICIEV) and 2018 2nd International Conference on Imaging, Vision & Pattern Recognition (icIVPR), 2018

   DOI