Browsing by Author "Gunathilake, P"

Now showing 1 - 2 of 2

Embargo
Context-Aware Incremental Learning Pipeline Triggers
(Institute of Electrical and Electronics Engineers Inc., 2025-12-09) Perara, S; Senadheera, D; Gunathilake, P; Gunawardana, C; Thelijjagoda, S; Krishara, J
Modern Continuous Integration/Continuous Delivery pipelines require intelligent and adaptive learning mechanisms to enhance software deployment stability and efficiency. While previous studies have introduced Pull Request prioritization techniques and predictive models for build failures, they do not offer real-time recommendations based on Pull Request criticality and build stability. This research presents a GitHub app based on reinforcement learning for intelligent Pull Request prioritization and deployment advisory in Continuous Integration/Continuous Delivery workflows. T he system combines natural language processing with contextual features to dynamically determine whether a Pull Request should be prioritized for early deployment or flagged for urgent review based on its priority level and associated build failure risk. Due to limited labeled feedback data, the study employs a hybrid approach using supervised learning for initial classification, enhanced by reinforcement learning for continuous adaptation. Using a dataset of 682148 Pull Requests from 28835 repositories, experimental results demonstrate significant improvements in deployment efficiency, achieving 92.01% accuracy in Pull Request classification with strong developer alignment. This research presents a comprehensive solution for optimizing Continuous Integration/Continuous Delivery pipelines through intelligent Pull Request prioritization with deployment advisory.
Embargo
WORDEX: Early Dyslexia Detection and Support
(Institute of Electrical and Electronics Engineers Inc., 2025) Ganegoda, S.H; Dissanayake, O; Samarakoon, S; Jayawardana, N; Thelijjagoda, S; Gunathilake, P
Dyslexia is a prevalent and complex learning disability that affects approximately 5% of primary school students worldwide. It often manifests as persistent difficulties in reading, writing, spelling, and overall academic performance, which can lead to long-term educational and psychological impacts if not addressed early. To facilitate the early identification and support of dyslexic learners aged 7 to 10, this paper introduces Wordex, an innovative and adaptive educational platform. Wordex is designed to screen for multiple dyslexia subtypes and provide targeted interventions through engaging, interactive, and personalized learning activities. The platform features an integrated machine learning-based screening system that analyzes user interactions and performance metrics to assess the risk of dyslexia. Upon identification, the platform delivers tailored remedial exercises that align with national school curricula, aiming to strengthen specific cognitive and linguistic skills. Wordex is developed using a modern technology stack including Spring Boot, Flutter, Python libraries, Firebase, and MongoDB, and incorporates capabilities such as image processing, supervised learning algorithms, real-time progress tracking, and cloud-based data management. A user-centered design approach and iterative testing cycles were employed to ensure the platform is accessible, intuitive, and pedagogically effective. Wordex contributes significantly to the field of educational technology by offering a scalable, research-informed intervention tool. Future enhancements include multilingual support, broader age group coverage, and integration with classroom learning environments.