Publications

  1. "Automated Repair of Asymmetric Web Pages during Resolution of Mobile Friendly Problems" Md. Aquib Azmain, Kishan Kumar Ganguly. The 16th International Conference on Evaluation of Novel Approaches to Software Engineering, ENASE 2021. [PDF] [Certificate] [Presentation]

    This conference held online from April 26 to 27, 2021. I presented the paper as Conference Speaker. Check out the video of that presentation.
  2. "Impact of label noise and efficacy of noise filters in software defect prediction", Shihab Shahriar Khan, Md. Aquib Azmain, Nishat Tasnim Niloy, and Ahmedul Kabir. The 32nd International Conference on Software Engineering and Knowledge Engineering, SEKE 2020, USA, pages 347-352. [PDF]
  3. "On the Evolutionary Properties of Fix Inducing Changes", Syed Fatiul Huq, Md. Aquib Azmain, Nadia Nahar and Md. Tawhid, QuASoQ 2020 in conjunction with the 27th Asia-Pacific Software Engineering Conference (APSEC 2020). [PDF]
  4. "Analyzing software quality and maintainability in object-oriented systems using software metrics", Faria Tasnim, Mahdi Islam, Salequzzaman Khan, Farib Md. Ferdoush, Fatema Haque, Md. Aquib Azmain, 2025 9th International Conference on Management Engineering, Software Engineering and Service Sciences (ICMSS). [PDF]
  5. "Enhancing Software Quality: Python Code Smell Detection using Machine Learning techniques and Refactoring Long Methods using Extract Method Algorithm", Mohammed Sharraf Uddin, Kazi Zunayed Quader Knobo, Jannatul Ferdoshi, Shabab Abdullah, Md. Aquib Azmain, Proceedings of the 2024 10th International Conference on Robotics and Artificial Intelligence. [PDF]
  6. "Unveiling Deception: Evaluating NLP's Effectiveness in Identifying Misleading Responses from Large Language Models", Md Mahim Muntasir Arin, Fahim Hasan, Md. Aquib Azmain, Muntasir Ahmed Ador, Iffat Ara Nazmin, Tawhid Anwar, 2025 7th International Conference on Natural Language Processing (ICNLP) [PDF]
Thesis Supervision
  1. Detecting Developer Emotions in GitHub Commits Using Large Language Models: Implications for Project Health
    Group Members: Zawad Al Akram, Insaniyat Ishan, Mushfiq Zahid, Fahmida Haque Fariha
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  2. Exploring Developer Patterns and Code Similarities: An In-Depth Study Using Code Stylometry, Developer Profiling, and Clone Detection in Software Projects
    Group Members: Apurba Afiat, Taan Gazi Safowan Islam, Sanzida Afrin, Sarker Md Talha, Jumanah Suha Parisa
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  3. Securing the Creative Code: An Investigation into the Security Aspects of AI-Generated Code
    Group Members: Md. Nayeemul Hasan, Shoeb Mahmood, Jarin Islam, Mahbuba Zaman
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  4. Deep Reinforcement Learning Based Climate-Aware Irrigation Scheduling for Boro Rice Cultivation in Mymensingh, Bangladesh
    Group Members: Md. Naimur Rahman, Lamia Saiyara, Nahian Quader Labib, Chowdhury Shadab Aiman
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  5. Learning Developer Style: A Stylometric Framework for Attribution, Detection and Profiling
    Group Members: Sudipta Nandi, Mohammad Sayed Safi Sams, Nabil Al Hami
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  6. Academic Burnout Detection Using Behavioural Data Analysis
    Group Members: Steve D Costa, Abiduddin Afnan, Abrar Zahin, Zannatun Tazree Tisha
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  7. AI-Assisted Code Generation Tools: A New Frontier in Software Development
    Group Members: Utshob Bose, Dipra Kamal, Zaima Mashiat Nabi, Ibtisum Jaman, Tasnia TaslimHossain
    [Undergraduate Thesis | Summer 2025 | CSE, BRACU]
  8. Early and Late Fusion Ensemble Methods for Predicting Bug Severity from Bug Report
    Group Members: Md. Farhan Farooq, MD. Shahariar Nawshad Nabil
    [Undergraduate Thesis | Spring 2025 | CSE, BRACU]
  9. An LLM-Based Framework for Automated Python Test Generation and Mutation Testing Evaluation [PDF]
    Group Members: Sadnan Nafis, Abdullah Al Walid, Amatus Subhan Anuja
    [Undergraduate Thesis | Spring 2025 | CSE, BRACU]
  10. Advanced Noise Reduction and Feature Enhancement in Medical CT Brain Imaging Using Deep Learning [PDF]
    Group Members: Zawadul Kafi Nahee, Sabrina Rahman Mazumder, Shouvik Banerjee Argha, Mashrur Safir Shabab, Sahriar Wahid Galib
    [Co-supervision | Undergraduate Thesis | Spring 2025 | CSE, BRACU]
  11. From Toxicity to Constructive Dialogue: An LLM-Driven Detoxification Approach with Multi-Source Parallel Data [PDF]
    Group Members: d Fardin Parvez, Aswadul Karim Rashik, MD Yameem Daiyan Deepto, Mostakim Ul Haq, Alex Noor Khan
    [Co-supervision | Undergraduate Thesis | Spring 2025 | CSE, BRACU]
  12. Detecting misleading information in LLMs responses[PDF]
    Group Members: Md Mahim Muntasir Arin, Muntasir Ahmed Ador, Iffat Ara Nazmin, Fahim Hasan, Syed Ashik Mahamud
    [Undergraduate Thesis | Fall 2024 | CSE, BRACU]
  13. Developing Usability Heuristics for Bangladeshi E-Commerce Websites: A Desktop and Mobile Focused Approach [PDF]
    Group Members: Namirul Islam, Nayel Zahir, Tahmim Hassan
    [Co-supervision | Undergraduate Thesis | Summer 2024 | CSE, BRACU]
  14. Unveiling Agricultural Insights: Leveraging Deep Learning for Enhanced Diagnostic Accuracy in Maize Disease Detection with Explainable Artificial Intelligence [PDF]
    Group Members: Basit Hussain, Malika Muradi, Christian Boateng, Eliya Christopher Nandi, Imenagitero Ulysse Tresor
    [Co-supervision | Undergraduate Thesis | Summer 2024 | CSE, BRACU]
  15. Enhancing Software Quality: Python Code Smell Detection using Machine Learning techniques and Refactoring Long Methods using Extract Method Algorithm [PDF]
    Group Members: Jannatul Ferdoshi, Shabab Abdullah, Kazi Zunayed Quader Knobo, Mohammed Sharraf Uddin
    [Undergraduate Thesis | Spring 2024 | CSE, BRACU]
  16. Analyzing Software Quality and Maintainability in Object-Oriented Systems using Software Metrics [PDF]
    Group Members: Faria Tasim, Farib Md. Ferdoush, Salequzzaman Khan, Mahdi Islam, Fatema Haque
    [Undergraduate Thesis | Summer 2024 | CSE, BRACU]
Research Experience
  • Improving symmetric structure during resolution of mobile friendly problems in web pages: Mobile friendly problem (MFP) causes the low quality of the website visibility and has a potential risk to decrease usability for a mobile user. The solution proposed an automatic repair technique that generates symmetric mobile friendly patches for a web page. [PDF]
  • On the evolutionary properties of fix inducing changes: Analyzing Fix-Inducing Changes (developer code that introduce bugs) provides the opportunity to estimate bugs beforehand. This study analyzes the evolution of FICs to visualize patterns associated with the introduction of bugs throughout and within project releases. [PDF]
  • Noise filters in software defect prediction: By using a diverse set of classifiers, imbalance-methods and noise filters, this study empirically investigates how the presence of label noise in post-release defect prediction datasetsaffect performance and evaluates the effectiveness of noisefilters in minimizing the adverse effects of noise. [PDF]
  • An Improved Creative Adversarial Network: A novel method for painting generation that explicitly seeks to maximize creativity of produced paintings is proposed. Our method reinterprets and formalizes the notion of creativity and borrows ideas from adversarial sample generation to propose a simple and efficient algorithm for creative art generation. [PDF]
  • Towards the detection and refactoring of message chains: Message Chain is a code smell which occurs when inefficient responsibility delegations create chains of consequent method calls, resulting incode that becomes difficult to interpret and maintain. This study proposes a method of detecting and suggesting the refactoring for Message Chains. [PDF]
  • A machine learning-based inference and analysis of crop production based on climate parameters in Bangladesh: Using standard approaches of machine learning – linear regression, support vector machine, random forest and more – this study provides appropriate prediction models for all the crops considered and infers the numeric effect of various climate factors on the unit production of the crops. [PDF]