Abstract Extensible Markup Language (XML) is the standard medium for data exchange among businesses over the Internet, hence the need for effective management. However, since XML was not designed for storage and retrieval, its management has become an open research area in the database community. Existing mapping techniques for XML-to-relational database adopt either the structural mapping or the model mapping. Though numerous mapping approaches have been developed, mapping and reconstruction time had been problematic, especially when the document size is large and can hardly fit into main memory. In this research, an application codenamed XAPP, a new lightweight application that adopts a novel model mapping approach was developed using Simple API for XML (SAX) parser. XAPP accepts a document with or without Document Type Definition (DTD). It implements two algorithms: one maps XML data to a relational database and improves mapping time, and the other reconstructs an XML document from a relational database to improve reconstruction time and minimise memory usage. The performance of XAPP was analysed and compared with the Document Object Model (DOM) algorithm. XAPP proves to perform significantly better than the DOM-based algorithm in terms of mapping and reconstruction time, and memory efficiency. The correctness of XAPP was also verified.

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[12] Zhu H., Yu H., Fan G., and Sun H., “Mini-XML: An Efficient Mapping Approach between XML and Relational Database,” in Proceedings of IEEE/ACIS 16th International Conference on Computer and Information Science, Wuhan, pp. 839-843, 2017. 588 The International Arab Journal of Information Technology, Vol. 19, No. 4, July 2022 Yetunde Akinwumi holds a BSc degree from AfeBabalola University Ado-Ekiti and MSc degree from Redeemer’s University Ede. She currently works on Information Modeling & Management, Data Design, mobile health management and web programming. She is currently a Research Assistant in Computer Science, Redeemer’s University Ede. Joshua Ayeni holds a PhD from the University of Waterloo UK. He is a Professor of Computer Science, University of Lagos and Redeemer’s University, Ede Nigeria. He is a Fellow of the Computer Registration Council of Nigeria (CPN). He has authored a book in Computer Science and published many articles in reputable peer reviewed journals. His research interest is in the area of formal modelling and simulation. Samson Arekete holds a PhD degree in Computer Science. He is a Professor of Computer Science at the Redeemer’s University, Ede, Nigeria. His research interests are in Artificial Intelligence, Intelligent Agents Systems and Modelling. He has published articles in learned journals and attended conferences. Mba Odim is a Reader (Associate Professor) in The Department of Computer Science, Redeemer’s University, and Ede. He holds a PhD degree in Computer Science and has published widely both local and internationally. He is a member of the Nigeria Computer Society (NCS) the Computer Registration Council of Nigeria (CPN). He holds the Artificial Intelligence Analyst - Mastery and Explorer Awards of IBM. His research interests include but not limited to Machine Learning, Deep Learning, Data Mining, Database Systems and Information Security. Adewale Ogunde is a Professor in Computer Science. He holds a PhD degree in Computer Science and is a registered member of the Computer Professionals Registration Council of Nigeria, Nigeria Computer Society, IAENG and several other professional bodies. He has published widely in both local and international journals. His research interests are in the area of Artificial Intelligence: data mining, machine learning, and Big Data with other intelligent and knowledge- based systems. Bosede Oguntunde holds a PhD degree from the University of Ibadan. Nigeria. She is a Senior Lecturer in Computer Science. Her research interests are in Data Communication, Networking, Bioinformatics and Machine Learning. She has published articles in learned journals and presented papers at conferences.