International Journal of Data Structure Studies

Latest articles

• Published Subscription Original Research 26 Jun 2026

  Traversal Speed Comparison of BFS and DFS in Balanced and Skewed Binary Trees

  By Anand Singh, Abhinav Singh, Padma Mishra

  Abstract: In this paper, we provide an analysis of how well both breadth-first search (BFS) and depth-first search (DFS) algorithms perform while wandering through two kinds of binary trees: balanced and skewed. The research was motivated by the practical application of storing files and directories in a certain type of parent-child relationship through the use of hierarchical file systems (e.g., windows explorer). The result of measuring how fast and versatilely these …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 2, 2026 Read article →

• Published Subscription Review Article 7 May 2026

  Improving Dataset Integrity Through Automated Data Cleaning Techniques

  By Rajani Kanta Sahu, Achinta Kumar Palit, Ushashree Nayak

  Abstract: High-quality data is a fundamental requirement in data science for producing trustworthy analytical insights and effective machine learning models. Problems, including incomplete records, inconsistent entries, duplicate observations, and anomalous values, can severely reduce the accuracy and robustness of predictive systems. As modern datasets continue to expand in both volume and structural complexity, relying on manual data cleaning methods become time-consuming and error-prone, highlighting the growing importance of automated data preprocessing …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 40–45 Read article →

• Published Subscription Review Article 7 May 2026

  Learning Data Structures: Key to Good Programming

  By V. Basil Hans

  Abstract: Data structures are the most crucial feature of good programming and are needed to solve hard computational problems. This model makes use of two different recurrent neural network architectures, specifically long short-term memory (LSTM), and gated recurrent unit (GRU) networks. It explains how selecting and using the correct data structures may speed up computations, optimize memory, and scale code. How data structures and algorithms relate and how to think about …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 29–39 Read article →

• Published Subscription Review Article 7 May 2026

  An Auxiliary Array Indexing Approach for Efficient Binary Search in Linked Lists

  By Rejay Pavunkumar, Royal Rodrigues, Rohini Bagul, Vaishnavi Biradar

  Abstract: The paper covers an algorithm for searching a linked list structure using binary search. Binary search is a classic example of an algorithm that follows the divide-and-conquer approach. Binary search may be used to find elements in an array. Trying to apply the conventional binary search to a linked list simply does not work out very well; it still has an O(n) time complexity, the same as linear search. This …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 21–28 Read article →

• Published Subscription Review Article 28 Apr 2026

  Data Structure Driven Probabilistic Deadlock Resolution in Multiprocessor Systems

  By Kakinada Mahitha Sri Ishwarya, Chegondi Revathi, Manas Kumar Yogi

  Abstract: Deadlock resolution in multiprocessor systems is fundamentally a graph-theoretic and probabilistic decision problem. Existing victim selection heuristics, such as youngest, oldest, and lowest priority, apply static rules that overlook the dynamic runtime state of processes, leading to unnecessary computational loss. This paper reframes the inference-guided preemption (IGP) algorithm as a data-structure-centric solution, highlighting how resource allocation graphs, wait-for graphs, adjacency lists, min-heaps, and hash-based evidence stores interact to enable efficient …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 11–20 Read article →

• Published Subscription Review Article 20 Mar 2026

  Machine Learning Based Sentiment Analysis of Student Feedback in Higher Education

  By Ramani Jaydeep Ramniklal

  Abstract: Educational institutions routinely collect feedback from students to understand their perceptions of academic programs, infrastructure, and campus facilities, to improve the overall quality of the college environment. In current practice, feedback is often gathered using numerical or grade-based rating systems, which tend to oversimplify student opinions and may overlook important details related to their level of satisfaction. In contrast, open-ended textual feedback allows students to clearly express their views, concerns, …

  Published in International Journal of Data Structure Studies · Vol. 4, Issue 1, 2026 · pp. 01–10 Read article →

• Published Subscription Original Research 24 Oct 2025

  Application of B-trees for Design of Optimal Page Replacement Technique in Modern Operating Systems

  By Sai Ganesh Palli, Manas Kumar Yogi

  Abstract: Algorithms related to replacing the memory pages in operating systems are critical components of modern operating systems that manage virtual memory efficiently. Current algorithms such as LRU (Least Recently Used), Clock algorithms as well as FIFO (First-In-First-Out), often struggle with the increasing demands of contemporary applications and larger memory hierarchies. This research work proposes a novel approach utilizing B-tree data structures to design an optimal page replacement technique. The proposed …

  Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 23–30 Read article →

• Published Subscription Review Article 24 Oct 2025

  Securing the Internet of Things: A Survey on Lightweight Blockchain Framework for Enhancing Security and Privacy

  By Nikita Adhana, Shivani Kaushik, Mukesh Kumar, Sujeet Kumar

  Abstract: Modern technologies, supported by the Internet of Things (IoT), have imparted great speed in data sharing between connected devices across several domains of the economy. The Internet of things transformed data collection activities with its creation of smart homes and cities, healthcare, transportation environments, and industrial automation. The fact that there are multiple resource-limited devices, and continuous data transfer of sensitive information has turned the IoT devices less secure and …

  Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 6–14 Read article →

All 36 articles in this journal →