Daily Archives: March 10, 2026

Authors: Praful Madne, Agrim Khanna, Aary Mahadik, Yash Nanwatkar

Abstract: With the rapid growth of digital education systems, academic institutions require structured task management solutions to manage assignments, grading, and communication effectively. UniTasker is a lightweight, role-based web application designed for diploma-level institutions. The system enables faculty members to create assignments, set deadlines, review submissions, and assign grades, while students can submit tasks and receive automated reminders. This paper surveys existing Learning Management Systems (LMS) and generic task management tools, analyzes their limitations, and evaluates how UniTasker bridges these gaps through a modular three-tier architecture. The system is developed using JSP, JDBC, MySQL, and Apache Tomcat, ensuring low infrastructure requirements and high usability. Future enhancements include attendance tracking.

Published by: vikaspatanker

Authors: GowriDurga A, Kavin S, Thanush S, Elzin Selva M

Abstract: For communication between distributed services, modern software systems mainly rely on REST APIs, especially in microservices architectures. Preventing vulnerabilities and preserving system stability depend on these APIs' dependability and security. Nevertheless, manual API testing is laborious, prone to mistakes, and frequently leads to insufficient test coverage. In order to automate the development and administration of REST API test cases, this article suggests an AI-Based API REST Test Generation framework. The system uses organized test sequences to perform automatic vulnerability detection, intelligently analyze API endpoints, and confirm application reachability. Automated endpoint discovery, authentication validation, parameter testing, and security vulnerability detection techniques like BOLA vulnerabilities and RBAC violations are all included in the framework. The proposed system is implemented as a web-based platform that visually represents the security posture of APIs through a step-wise roadmap. Experimental evaluation demonstrates that the automated framework significantly reduces manual workload while improving the efficiency and accuracy of API testing.

 

 

Published by: vikaspatanker