Journal of Advanced Research in Computer Technology & Software Applications

A Review of Multi-Layer Semantic Chunking and Enhanced Retrieval-Augmented Generation Frameworks

Pratiksha — 2026-05-07

Retrieval-Augmented Generation (RAG) has become a paradigmatic model of improving the discursive quality and truthfulness of facts, the transparency and domain flexibility of Large Language Models (LLMs) by condensing external knowledge retrieval during generation. Although the traditional RAG architectures have shown significant advancement over the purely parametric language models, they still have marked limitations in regard to fixed-size chunking of text, shallow semantic representations, and access to irrelevant or noisy information. These deficiencies are more acute in long-context, narrative-based, and multi-hop reasoning tasks. This review article conducts an in-depth analysis of the current developments in the field of RAG architectures, in particular, semantic-sensitive retrieval schemes, such as multi-layer semantic chunking, improved embedding algorithms, and smart outlier treatment schemes. The MERCED RAG framework, as presented in recent literature, receives special attention as one of the categories of next-generation RAG systems that seek to address the shortcomings of traditional solutions with hierarchical representations and relevance-sensitive retrieval pipelines. The article summarizes the available methodologies, experimental results, evaluation measures, shortcomings, and research gaps and presents an organized view of future possibilities of scalable, robust, and reliable retrieval-enhanced generation systems.

DOI: https://doi.org/10.24321/3051.4304.202509

Advances in Software Engineering: Integrating Theory of Computation with Practical Software Design and Development

Neelam Verma — 2026-02-06

This review explores the integration of Theory of Computation with modern Software Engineering practices, focusing on how theoretical principles can enhance the design, development, and analysis of software systems. As the fields of computation theory and software engineering rapidly evolve, software engineers are able to tackle increasingly complex problems, leading to improvements in scalability, efficiency, and reliability. By bridging the gap between theoretical concepts, such as automata theory, computational complexity, formal languages, and algorithm design, with practical software development, this article examines how this intersection drives better decision-making, optimizes software solutions, and facilitates the creation of more robust, scalable systems. Additionally, the paper discusses the challenges and opportunities of combining theoretical knowledge with real-world applications, offering insights into current methodologies, best practices, and emerging trends that continue to shape this interdisciplinary approach. The article also highlights key case studies, focusing on areas where theory has had a significant impact on practical software solutions, including compiler design, parallel algorithms, and formal verification. Furthermore, the paper explores future directions, such as the integration of quantum computing, machine learning, and cloud computing with theory, and provides a roadmap for researchers and practitioners seeking to leverage both theory and practice to solve complex software engineering challenges.

Cryptology and Cryptography: Foundations, Techniques, and Applications in Securing Information Systems

Deep Sharma — 2026-02-07

Cryptology and cryptography form the backbone of modern data security. With the increasing importance of data privacy and secure communication in the digital age, cryptology, the science of encryption and decryption, has become essential in securing information systems. This review provides a comprehensive examination of cryptology's foundational principles, techniques, and modern applications in cryptography. By tracing the historical evolution of cryptographic methods and exploring contemporary challenges and solutions, this paper outlines the key cryptographic protocols, algorithms, and their roles in securing data. Furthermore, we explore emerging trends, including quantum cryptography, blockchain technology, and their implications for future information security.

Innovative Applications of Artificial Intelligence in Computer Science

Pavan Sikarwar — 2026-02-07

This review explores the innovative and transformative applications of Artificial Intelligence (AI) in the field of Computer Science. Over the past decade, AI has rapidly advanced, integrating itself into multiple domains, from machine learning (ML) algorithms to natural language processing (NLP) and computer vision. These advancements are reshaping industries, enhancing decision-making processes, and improving user experiences. The paper delves into the most impactful AI applications across various domains such as data analytics, autonomous systems, and software engineering. Furthermore, the review provides a critical analysis of the challenges associated with AI adoption, including issues related to data privacy, bias in algorithms, and ethical considerations. Additionally, the article discusses the future directions of AI research, highlighting emerging trends such as quantum computing, edge AI, and the quest for Artificial General Intelligence (AGI). Through a comprehensive examination of these key aspects, this review aims to provide insights into the evolving landscape of AI in computer science, its real-world implications, and the need for responsible and transparent AI development.

Mathematical Foundations and Algorithm Design: Bridging Theory and Practice in Software Engineering

2026-02-07

This review explores the vital role of mathematical foundations in algorithm design, and how they shape the development of efficient and scalable software systems. Drawing from key areas of discrete mathematics, number theory, graph theory, and optimization, we examine the bridge between theoretical concepts and their practical application in software engineering. The rapid evolution of computing technologies and growing system complexities demand that software engineers not only have strong computational skills but also a firm understanding of mathematical principles that guide algorithm design. This article discusses the importance of algorithms in problem-solving, explores foundational mathematical concepts in algorithm design, and examines how these principles contribute to efficient software engineering practices. Additionally, the review highlights emerging trends in computational complexity, optimization algorithms, and their integration with software systems.

Cyber-Gurukuls: Designing Digital Learning Communities Rooted in Tradition

Jahanvi Arora — 2026-05-06

Several decades ago gurukuls were there in ancient India and these were known as the places of learning where students lived, learned numerous things and were guided by gurus. However, in today’s scenario modern education system with the help of technology has become more advanced but still it lacks a personal connection as well as a value based approach. This paper explains the concept of “Cyber Gurukuls” which is a digital learning platforms with the objective of bringing back spirit of the Gurukul by using different tools like Digital classrooms, Online mentor networks and Smart learning tools. The main aim is to integrate ancient educational values like discipline, respect as well as reach of digital education. By concentrating not only on moral development but also on mentorship and community learning, the cyber gurukuls can provide a better learning experience to the students.

DOI: https://doi.org/10.24321/3051.4304.202506

Database Management Systems: A Comprehensive Survey

Ranjana Kapila — 2026-05-08

DOI: https://doi.org/10.24321/3051.4304.202507

Principles and Practices in Modern Software Design and Architecture

Leena Vincent — 2026-02-07

The field of software design and architecture has experienced rapid and transformative changes over the past few decades, fueled by advancements in computing technologies and methodologies. This review delves into the core principles and contemporary practices that underpin modern software design and architecture, with a particular focus on scalability, maintainability, and flexibility. As systems grow increasingly complex, driven by the adoption of cloud computing, microservices, containerization, and agile methodologies, traditional approaches are evolving to meet the demands of modern development environments. The review examines foundational principles such as modularity, separation of concerns, and abstraction, while also addressing cutting-edge trends such as cloud-native architectures, serverless computing, and AI-driven development. Challenges such as managing system complexity, maintaining security, and integrating legacy systems are also explored. By providing an in-depth analysis of these practices, this article highlights how modern software architectures are being designed to support dynamic, scalable, and resilient applications, ultimately improving system performance and business agility. The review concludes with a discussion of future directions in software architecture, focusing on emerging technologies and their potential impact on the design of next-generation software systems.