• Cross-Modal Predictive Modeling of Mental Health Treatment Outcomes: A Machine Learning Framework for Comparing Psychiatric Counseling Therapy and Therapeutic AI-Chatbots 

  DeSilva, M.T.D.; Kaushalya, P.K.D.K. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Mental health problems are becoming the order of the day and burdening the traditional psychiatric guidance frameworks in terms of expenses, unreachability and waiting durations. Conversely, mental health chatbots that ...
• Deepfake Image and Video Detection System for Sri Lankan Facial Features Using Machine Learning 

  Karunarathna, A.M.T.H.; Abeythunga, W.M.L.S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Deepfakes and other AI-generated manipulated images and videos have become an increasing cyber threat to Sri Lanka as AI-generated multimedia content becomes more accessible to consumers. Global AI-generated multimedia ...
• Explainable Artificial Intelligence Approaches in NLP-Based Text Classification: A Systematic Literature Review 

  Gunasekara, S.A.G.K.; Kaushalya, P.K.D.K. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)
• Machine learning-based performance prediction framework for real-time 3D asset optimization in 3D modeling 

  Praneeth, T.M.K..; Lakshan, W.D.D.; Hewaratna, A.I. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  This study presents a machine learning–based performance prediction framework that enables 3D artists and game developers to estimate rendering cost. such as frame rate, CPU/GPU usage, memory consumption, and draw calls ...
• Enhancing user interface and user experience design of digital banking platforms: a usability-focused approach for senior citizens in Sri Lanka 

  Afraar, A.R.M.; Gunewardhana, H.M.K.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Digital banking services are rapidly expanding in Sri Lanka, offering customers convenient and efficient access to financial services, yet many senior citizens still face difficulties when using mobile and internet banking ...
• Optimizing Red and White Wine Quality Prediction Using Hybrid Ensemble Learning and Interpretable Feature Engineering 

  Dissanayake, D.K.H.; Kumara, B.T.G.S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  The conventional method of wine quality prediction has always been based on sensory testing by human analyst and this has been subjective as well as time consuming, and this type of evaluation is hard to scale to the ...
• A Hybrid LLM-Driven Recommendation System for Selecting Flutter Packages Using Structured Metadata and Stack Overflow Knowledge 

  Bandara, R.M.I.M.; Chathumini, K.G.L.; Kumara, B.T.G.S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  The rapid growth of the Flutter ecosystem has built significant challenges for the developers in choosing the right third-party packages. Existing popularity-based methods fail to capture developer intent or semantic ...
• AI-Driven Risk Prediction in Software Development Environment 

  Sanchayan, R.; Somaweera, W.T.S.; Sandaruwan, R.M.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Software development projects are constantly carried out in circumstances that are highly unexpected and dynamic. Unpredictability caused by frequent demand changes, shifting responsibilities, and delivery schedule ...
• AI Based Flutter Interface Generator Using Natural Language Commands with Social and Ethical Considerations 

  Andarawewa, K.M.; Chathumini, K.G.L. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  The accelerated pace of development of Artificial Intelligence (AI) and the emerging opportunities to automate the generation of user interfaces (UI) are explored in this research, especially within the context of ...
• Detecting Developer Burnout Through Sentiment Trends in Software Repositories Using DistilBERT 

  Samaraweera, S.P.I.L.D.; Adeeba, S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Recent studies have indicated that severe chronic stress relates to burnout, and Software Engineering (SE) is no exception, having greater than 57chronic stress. Conventional methods of evaluation employ surveys and ...
• Semantic Metadata-enhanced Deep Learning Techniques for Duplicate Bug Report Detection 

  Sandunika, D.M.N.; Herath, G.A.C.A. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Duplication of bug reports poses a significant impact on software development efficiency with 12-25% of bugs report being duplicated on large projects. Manual identification techniques are both time consuming and prone ...
• Optimizing API and framework design for improved usability, maintainability, and developer productivity 

  Hashan, G.T.; Somaweera, W.T.S.; Sandaruwan, R.M.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  The use of APIs/ Frameworks in software development today cannot be done without and yet numerous of them still have design defects that hinder usability, maintainability and developer productivity due to lack of systematic ...
• An Empirical Evaluation of Clean Architecture: Impact on Software Quality and Developer Productivity 

  Senadheera, M.A.K.R.; Somaweera, W.T.S.; Sandaruwan, R.M.T. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Clean architecture(CA) is one of the most reliable and most productive architectures in the modern world. By organizing code into distinct layers, each with a clear responsibility, allows developers to build robust, ...
• Enhancing software quality and team productivity in agile development environments through machine learning-based sentiment analysis 

  Dayarathna, K.O.K.S.; Wasalthilaka, W.V.S.K. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Communication in Agile software development plays an important place for task coordination, clarifying requirements and sprint activities supervision. The sentiment shown in these communication messages can provide useful ...
• Analyzing developer misguidance in AI code suggestion tools: a large-scale empirical study 

  Sathursana, K.; Nirubikaa, R. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Artificial Intelligence (AI)-based code suggestion tools are widely used in current software development. These tools save time and help developers at many stages. At the same time, they produce code with some issues-the ...
• Time Series Forecasting of User Engagement in Python Software Applications Based on Usage Logs 

  Janarthan, V.; Erandi, J.D.T.; Tharaka, Y.M.S. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Understanding users’ engagement in Python-based software applications is important for improving usability, maintaining user satisfaction, and strategic future planning. Python usage logs contain important but rarely ...
• An explainable AI-based approach for Java code smell detection to improve software maintainability 

  Wedaarachchi ., R; Herath, G.A.C.A.; Wasalthilaka, W.V.S.K. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Code smells are early indicators of design flaws that compromise long term software maintainability. Traditional static analysis tools often generate false positives or fail to detect context dependent smells because ...
• Classification of Non-Functional Requirements in Software Development using Deep Learning 

  Kavindi, H.M.K.; Herath, G.A.C.A. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Non-functional requirements are the most significant quality attributes that define a software system as being reliable, secure and efficient under the real-world conditions. But, NFRs are often not taken into account ...
• Comparative Analysis of Sentiment Classification Models for Algorithmic Trading 

  Perera, R.D.M.; Ishanka, U.A.P (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Market sentiment, as driven by news and online discussion sites is increasingly impacting algorithmic trading systems. In this work, we analyze financial news headlines from Yahoo Finance, enhanced with related discussion ...
• Automated detection of developer mental health status in collaboration platforms using NLP and activity analysis 

  Abewardhana, M.R.S.C.; Ishanka, U.A.P. (Faculty of Computing. Sabaragamuwa University of Sri Lanka., 2026-01-28)

  Software developers experience significant mental health challenges due to workrelated stressors, making it essential for workplaces to adopt systematic and proactive strategies for identifying and supporting employees ...

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