Implementing Agile Testing Methodologies in Banking Software Project
DOI:
https://doi.org/10.55544/jrasb.1.4.32Keywords:
Scaled Agile Framework, Large-Scale, Banking and Financial Services, Agile Implementation, Software Development, Business Environment, Enterprise Level, Industrial Sectors, Scope and ImplicationsAbstract
Agile software development has been increasingly popular in a number of sectors in recent years. Financial businesses are used to this tendency since it requires them to respond to changes in their business environments more swiftly. Agile approaches have emerged to address the limitations of old ones. In response to the ever-changing and dynamic nature of the business environment, software development businesses are increasingly implementing agile methodologies. The word "Agile" originally arose in the disciplines of software development and project management around thirty years ago. It is used to research with wide-ranging implications, and it is utilized at different levels and in different circumstances. Scrum, kanban, large-scale scrum (LeSS), spotify model, continuous integration, Scaled Agile Lean Development (SCALeD), and many more variations of the agile methodology have emerged. Initially implemented at the individual software development and team level, agile has developed into projects, programs, solutions, and portfolios over time, ultimately reaching full-service growth into an enterprise level framework. In order to examine agile methodologies, models, and practices in a less researched area of the banking and financial services industry—from software development and modelling to large-scale case study organization levels—a unique methodology to surveying the literature has been presented in this paper. The study's conclusion outlines the contributing variables, best practices, advantages, and lessons that professionals in the banking and financial services industries may apply to create a simplified, agile deployment.
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Vilela J, Castro J, Martins LE, Gorschek T. Integration between requirements engineering and safety analysis: A systematic literature review. Journal of Systems and Software. 2017 Mar 1; 125:68-92.
Bowen S, Maurer F. Process support and knowledge management for virtual teams doing agile software development. In Proceedings 26th Annual International Computer Software and Applications 2002 Aug 26 (pp. 1118-1120). IEEE.
Holz H, Maurer F. Knowledge management support for distributed agile software processes. In International Workshop on Learning Software Organizations 2002 Aug 6 (pp. 60-80). Springer, Berlin, Heidelberg.
Shameem M, Kumar RR, Nadeem M, Khan AA. Taxonomical classification of barriers for scaling agile methods in global software development environment using fuzzy analytic hierarchy process. Applied Soft Computing. 2020 May 1; 90:106122.
Awad, M.A. (2005), “A Comparison between Agile and Traditional Software Development Methodologies, This report is submitted as partial fulfillment of the requirements for the Honours”, The University of Western Australia.
Kumar, G. and Bhatia, P. (2014), “Comparative Analysis of Software Engineering Models from Traditional to Modern Methodologies”, presented at the International Conference on Advanced Computing and Communication Technologies, ACCT.
Liang, J. and Shekhar, S. (2018), “AGILE ADOPTION IN INVESTMENT BANKS”.
Vinekar, V. and Huntley, C.L. (2010), “Agility versus Maturity: Is There Really a Trade-Off?” Computer, Vol. 43 No. 5, pp. 87–89.
Flora, H. (2014), “A Systematic Study on Agile Software Development Methodlogies and Practices”, International Journal of Computer Science and Information Technologies, Vol. 5, pp. 3626–3637.
Javanmard M, Alian M. Comparison between Agile and Traditional software development methodologies. Fen Bilimleri Dergisi (CFD). 2015; 36 (3).
Canty, D. (2015). Agile for project managers. CRC Press.
Carnevale, C., Mazzuca, M., & Venturini, S. (2012). Corporate social reporting in European banks: the effects on firm market value, Corporate Social Responsibility and Environmental Management, 19, 159-177.
Capiluppi, A., Fernandez-Ramil, J., Higman, J., Sharp, H.C., and Smith, N. 2007. An empirical study of the evolution of an agile-developed software system. Proceedings of the 29th International Conference on Software Engineering (Minneapolis, MN, USA, 2007).
Chintala, S. and Mohan, N. (2015), “The intricacies of software testing”,
Birkinshaw, J., What to Expect From Agile. MIT Sloan Management Review, 59 (2), pp. 39-42, 2018.
Bruhl, V., Agile methods in the German banking sector – some evidence on expectations, experiences and success factors, CFS Working Paper Series, No. 669, Goethe University Frankfurt, Center for Financial Studies (CFS), Frankfurt a. M., pp. 1 – 37, 2021.
Christou, T.I., Palaiologou, E., Using the agile unified process in banking. IEEE Software, 27 (3), pp. 72-79, 2010.
Conforto, E.C., Salum F., Amaral D.C., da Silva S.L., de Almeida L.F.M., Can Agile Project Management be Adopted by Industries Other than Software Development? Project Management Journal. 45 (3), pp. 21-34, 2014.
Denning, S., The next frontier for Agile: strategic management. Strategy & Leadership, 45 (2), pp. 12-18, 2017.
Dhevina, D., Teguh R., Bob H., Andi W., Fahmi A., Challenges of Agile Adoption in Banking Industry: A Systematic Literature Review. 25th International Computer Science and Engineering Conference (ICSEC), 2021.
Mikalsen, M., Moe, N.B., Stray, V., Nyrud, H., Agile Digital Transformation: A Case Study of Interdependencies. International Conference on Information Systems (ICIS), pp. 1 – 9, 2018.
Roses, L., Windmoller, A., Carmo, E., Favorability conditions in the adoption of agile method practices for software development in a public banking. Journal of Information Systems and Technology Management. 13, 2016.
Serrador, P., & Pinto, J. K., Does Agile work? - A quantitative analysis of agile project success. International Journal of Project Management, 33 (5), pp. 1040-1051, 2015.
Bharadwaj A, El Sawy OA, Paviou PA, Venkatraman N (2013) Digital business strategy: toward a next generation of insights. MIS Q 37(2):471–482.
Birkinshaw J (2018) What to expect from agile. MIT Sloan Manag Rev 59(2):39–42.
Boehm B (1979) Guidelines for verifying and validating software requirements and design specifcation. EURO IFIP 79:711–719.
Ciric D, Lalic B, Gracanin D, Palcic I, Zivlak N (2018) Agile project management in new product development and innovation processes: challenges and benefts beyond software domain. IEEE International Symposium on Innovation and Entrepreneurship (TEMS-ISIE): 1–9.
Doz YL, Kosonen M (2010) Embedding strategic agility: a leadership agenda for accelerating business model renewal. Long Range Plann 43:370–382
Dybå T, Dingsøyr T (2008) Empirical studies of agile software development: a systematic review. Inf Softwere Techno 50(9–10):833–859.
Flewelling P (2018) The Agile developer’s Handbook: Get more value from your software development: get the best out of the Agile methodology. Packt Publishing, Birmingham.
Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2019). Secure federated learning framework for distributed AI model training in cloud environments. International Journal of Open Publication and Exploration (IJOPE), 7(1), 31. Available online at https://ijope.com.
Savita Nuguri, Rahul Saoji, Krishnateja Shiva, Pradeep Etikani, & Vijaya Venkata Sri Rama Bhaskar. (2021). OPTIMIZING AI MODEL DEPLOYMENT IN CLOUD ENVIRONMENTS: CHALLENGES AND SOLUTIONS. International Journal for Research Publication and Seminar, 12(2), 159–168. https://doi.org/10.36676/jrps.v12.i2.1461
Kaur, J., Choppadandi, A., Chenchala, P. K., Nuguri, S., & Saoji, R. (2022). Machine learning-driven IoT systems for precision agriculture: Enhancing decision-making and efficiency. Webology, 19(6), 2158. Retrieved from http://www.webology.org.
Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2021). Adaptive AI-based deep learning models for dynamic control in software-defined networks. International Journal of Electrical and Electronics Engineering (IJEEE), 10(1), 89–100. ISSN (P): 2278–9944; ISSN (E): 2278–9952
Kavuri, S., & Narne, S. (2020). Implementing effective SLO monitoring in high-volume data processing systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(2), 558. http://ijsrcseit.com
Kavuri, S., & Narne, S. (2021). Improving performance of data extracts using window-based refresh strategies. International Journal of Scientific Research in Science, Engineering and Technology, 8(5), 359-377. https://doi.org/10.32628/IJSRSET
Narne, S. (2022). AI-driven drug discovery: Accelerating the development of novel therapeutics. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 196. http://www.ijritcc.org
Kavuri, S., & Narne, S. (2020). Implementing effective SLO monitoring in high-volume data processing systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 6(2), 558. http://ijsrcseit.com
Kavuri, S., & Narne, S. (2021). Improving performance of data extracts using window-based refresh strategies. International Journal of Scientific Research in Science, Engineering and Technology, 8(5), 359-377. https://doi.org/10.32628/IJSRSET
Narne, S. (2022). AI-driven drug discovery: Accelerating the development of novel therapeutics. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 196. http://www.ijritcc.org
Rinkesh Gajera , "Leveraging Procore for Improved Collaboration and Communication in Multi-Stakeholder Construction Projects", International Journal of Scientific Research in Civil Engineering (IJSRCE), ISSN : 2456-6667, Volume 3, Issue 3, pp.47-51, May-June.2019
Balachandar, P. (2020). Title of the article. International Journal of Scientific Research in Science, Engineering and Technology, 7(5), 401-410. https://doi.org/10.32628/IJSRSET23103132
Paulraj, B. (2022). Building Resilient Data Ingestion Pipelines for Third-Party Vendor Data Integration. Journal for Research in Applied Sciences and Biotechnology, 1(1), 97–104. https://doi.org/10.55544/jrasb.1.1.14
Paulraj, B. (2022). The Role of Data Engineering in Facilitating Ps5 Launch Success: A Case Study. International Journal on Recent and Innovation Trends in Computing and Communication, 10(11), 219–225. https://doi.org/10.17762/ijritcc.v10i11.11145
Paulraj, B. (2019). Automating resource management in big data environments to reduce operational costs. Tuijin Jishu/Journal of Propulsion Technology, 40(1). https://doi.org/10.52783/tjjpt.v40.i1.7905
Balachandar Paulraj. (2021). Implementing Feature and Metric Stores for Machine Learning Models in the Gaming Industry. European Economic Letters (EEL), 11(1). Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1924
Bhatt, S. (2020). Leveraging AWS tools for high availability and disaster recovery in SAP applications. International Journal of Scientific Research in Science, Engineering and Technology, 7(2), 482. https://doi.org/10.32628/IJSRSET2072122
Kavuri, S., & Narne, S. (2020). Implementing effective SLO monitoring in high-volume data processing systems. International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 5(6), 558. https://doi.org/10.32628/CSEIT206479
Swethasri Kavuri, " Advanced Debugging Techniques for Multi-Processor Communication in 5G Systems, IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 9, Issue 5, pp.360-384, September-October-2023. Available at doi : https://doi.org/10.32628/CSEIT239071
Mehra, A. (2021). The impact of public-private partnerships on global educational platforms. Journal of Informatics Education and Research, 1(3), 9–28. http://jier.org
Ankur Mehra. (2019). Driving Growth in the Creator Economy through Strategic Content Partnerships. International Journal for Research Publication and Seminar, 10(2), 118–135. https://doi.org/10.36676/jrps.v10.i2.1519
Ankur Mehra. (2022). Effective Team Management Strategies in Global Organizations. Universal Research Reports, 9(4), 409–425. https://doi.org/10.36676/urr.v9.i4.1363
Ankur Mehra. (2022). Effective Team Management Strategies in Global Organizations. Universal Research Reports, 9(4), 409–425. https://doi.org/10.36676/urr.v9.i4.1363
Ankur Mehra. (2022). Effective Team Management Strategies in Global Organizations. Universal Research Reports, 9(4), 409–425. https://doi.org/10.36676/urr.v9.i4.1363
Ankur Mehra. (2022). The Role of Strategic Alliances in the Growth of the Creator Economy. European Economic Letters (EEL), 12(1). Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1925
Bizel, G., Parmar, C., Singh, K., Teegala, S., & Voddi, V. K. R. (2021). Cultural health moments: A search analysis during times of heightened awareness to identify potential interception points with digital health consumers. Journal of Economics and Management Sciences, 4(4), 35. https://doi.org/10.30560/jems.v4n4p35
Reddy, V. V. K., & Reddy, K. K. (2021). COVID-19 case predictions: Anticipating future outbreaks through data. NeuroQuantology, 19(7), 461–466. https://www.neuroquantology.com/open-access/COVID-19+Case+Predictions%253A+Anticipating+Future+Outbreaks+Through+Data_14333/?download=true
Santhosh Palavesh. (2019). The Role of Open Innovation and Crowdsourcing in Generating New Business Ideas and Concepts. International Journal for Research Publication and Seminar, 10(4), 137–147. https://doi.org/10.36676/jrps.v10.i4.1456
Santosh Palavesh. (2021). Developing Business Concepts for Underserved Markets: Identifying and Addressing Unmet Needs in Niche or Emerging Markets. Innovative Research Thoughts, 7(3), 76–89. https://doi.org/10.36676/irt.v7.i3.1437
Palavesh, S. (2021). Co-Creating Business Concepts with Customers: Approaches to the Use of Customers in New Product/Service Development. Integrated Journal for Research in Arts and Humanities, 1(1), 54–66. https://doi.org/10.55544/ijrah.1.1.9
Santhosh Palavesh. (2022). Entrepreneurial Opportunities in the Circular Economy: Defining Business Concepts for Closed-Loop Systems and Resource Efficiency. European Economic Letters (EEL), 12(2), 189–204. https://doi.org/10.52783/eel.v12i2.1785
Santhosh Palavesh. (2022). The Impact of Emerging Technologies (e.g., AI, Blockchain, IoT) On Conceptualizing and Delivering new Business Offerings. International Journal on Recent and Innovation Trends in Computing and Communication, 10(9), 160–173. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10955
Santhosh Palavesh. (2021). Business Model Innovation: Strategies for Creating and Capturing Value Through Novel Business Concepts. European Economic Letters (EEL), 11(1). https://doi.org/10.52783/eel.v11i1.1784
Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810
Challa, S. S. S. (2020). Assessing the regulatory implications of personalized medicine and the use of biomarkers in drug development and approval. European Chemical Bulletin, 9(4), 134-146.
D.O.I10.53555/ecb.v9:i4.17671
EVALUATING THE EFFECTIVENESS OF RISK-BASED APPROACHES IN STREAMLINING THE REGULATORY APPROVAL PROCESS FOR NOVEL THERAPIES. (2021). Journal of Population Therapeutics and Clinical Pharmacology, 28(2), 436-448. https://doi.org/10.53555/jptcp.v28i2.7421
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5), 380-387.
Ashok Choppadandi. (2022). Exploring the Potential of Blockchain Technology in Enhancing Supply Chain Transparency and Compliance with Good Distribution Practices (GDP). International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 336–343. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10981
Challa, S. S. S., Chawda, A. D., Benke, A. P., & Tilala, M. (2020). Evaluating the use of machine learning algorithms in predicting drug-drug interactions and adverse events during the drug development process. NeuroQuantology, 18(12), 176-186. https://doi.org/10.48047/nq.2020.18.12.NQ20252
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality Management Systems in Regulatory Affairs: Implementation Challenges and Solutions. Journal for Research in Applied Sciences and Biotechnology, 1(3), 278–284. https://doi.org/10.55544/jrasb.1.3.36
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, & Sneha Aravind. (2022). Strategies for Effective Product Roadmap Development and Execution in Data Analytics Platforms. International Journal for Research Publication and Seminar, 13(1), 328–342. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1515
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, & Sneha Aravind. (2022). Leveraging Data Analytics to Improve User Satisfaction for Key Personas: The Impact of Feedback Loops. International Journal for Research Publication and Seminar, 11(4), 242–252. https://doi.org/10.36676/jrps.v11.i4.1489
Ranjit Kumar Gupta, Sagar Shukla, Anaswara Thekkan Rajan, Sneha Aravind, 2021. "Utilizing Splunk for Proactive Issue Resolution in Full Stack Development Projects" ESP Journal of Engineering & Technology Advancements 1(1): 57-64.
Sagar Shukla. (2021). Integrating Data Analytics Platforms with Machine Learning Workflows: Enhancing Predictive Capability and Revenue Growth. International Journal on Recent and Innovation Trends in Computing and Communication, 9(12), 63–74. Retrieved from https://ijritcc.org/index.php/ijritcc/article/view/11119
Sneha Aravind. (2021). Integrating REST APIs in Single Page Applications using Angular and TypeScript. International Journal of Intelligent Systems and Applications in Engineering, 9(2), 81 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6829
Aravind, S., Cherukuri, H., Gupta, R. K., Shukla, S., & Rajan, A. T. (2022). The role of HTML5 and CSS3 in creating optimized graphic prototype websites and application interfaces. NeuroQuantology, 20(12), 4522-4536. https://doi.org/10.48047/NQ.2022.20.12.NQ77775
Rishabh Rajesh Shanbhag, Rajkumar Balasubramanian, Ugandhar Dasi, Nikhil Singla, & Siddhant Benadikar. (2022). Case Studies and Best Practices in Cloud-Based Big Data Analytics for Process Control. International Journal for Research Publication and Seminar, 13(5), 292–311. https://doi.org/10.36676/jrps.v13.i5.1462
Siddhant Benadikar. (2021). Developing a Scalable and Efficient Cloud-Based Framework for Distributed Machine Learning. International Journal of Intelligent Systems and Applications in Engineering, 9(4), 288 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6761
Siddhant Benadikar. (2021). Evaluating the Effectiveness of Cloud-Based AI and ML Techniques for Personalized Healthcare and Remote Patient Monitoring. International Journal on Recent and Innovation Trends in Computing and Communication, 9(10), 03–16. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11036
Challa, S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of PharmaResearch, 7(5), 380-387.
Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25
Chaturvedi, R., & Sharma, S. (2022). Enhancing healthcare staffing efficiency with AI-powered demand management tools. Eurasian Chemical Bulletin, 11(Regular Issue 1), 675-681. https://doi.org/10.5281/zenodo.13268360
Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475
Dr. Saloni Sharma, & Ritesh Chaturvedi. (2017). Blockchain Technology in Healthcare Billing: Enhancing Transparency and Security. International Journal for Research Publication and Seminar, 10(2), 106–117. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1475
Saloni Sharma. (2020). AI-Driven Predictive Modelling for Early Disease Detection and Prevention. International Journal on Recent and Innovation Trends in Computing and Communication, 8(12), 27–36. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/11046
Chaturvedi, R., & Sharma, S. (2022). Assessing the Long-Term Benefits of Automated Remittance in Large Healthcare Networks. Journal for Research in Applied Sciences and Biotechnology, 1(5), 219–224. https://doi.org/10.55544/jrasb.1.5.25
Pavan Ogeti, Narendra Sharad Fadnavis, Gireesh Bhaulal Patil, Uday Krishna Padyana, Hitesh Premshankar Rai. (2022). Blockchain Technology for Secure and Transparent Financial Transactions. European Economic Letters (EEL), 12(2), 180–188. Retrieved from https://www.eelet.org.uk/index.php/journal/article/view/1283
Fadnavis, N. S., Patil, G. B., Padyana, U. K., Rai, H. P., & Ogeti, P. (2020). Machine learning applications in climate modeling and weather forecasting. NeuroQuantology, 18(6), 135-145. https://doi.org/10.48047/nq.2020.18.6.NQ20194
Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889
Gireesh Bhaulal Patil. (2022). AI-Driven Cloud Services: Enhancing Efficiency and Scalability in Modern Enterprises. International Journal of Intelligent Systems and Applications in Engineering, 10(1), 153–162. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/6728
Patil, G. B., Padyana, U. K., Rai, H. P., Ogeti, P., & Fadnavis, N. S. (2021). Personalized marketing strategies through machine learning: Enhancing customer engagement. Journal of Informatics Education and Research, 1(1), 9. http://jier.org
Krishnateja Shiva. (2022). Leveraging Cloud Resource for Hyperparameter Tuning in Deep Learning Models. International Journal on Recent and Innovation Trends in Computing and Communication, 10(2), 30–35. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10980
Shiva, K., Etikani, P., Bhaskar, V. V. S. R., Palavesh, S., & Dave, A. (2022). The rise of robo-advisors: AI-powered investment management for everyone. Journal of Namibian Studies, 31, 201-214.
Bhaskar, V. V. S. R., Etikani, P., Shiva, K., Choppadandi, A., & Dave, A. (2019). Building explainable AI systems with federated learning on the cloud. Journal of Cloud Computing and Artificial Intelligence, 16(1), 1–14.
Ogeti, P., Fadnavis, N. S., Patil, G. B., Padyana, U. K., & Rai, H. P. (2022). Blockchain technology for secure and transparent financial transactions. European Economic Letters, 12(2), 180-192. http://eelet.org.uk
Vijaya Venkata Sri Rama Bhaskar, Akhil Mittal, Santosh Palavesh, Krishnateja Shiva, Pradeep Etikani. (2020). Regulating AI in Fintech: Balancing Innovation with Consumer Protection. European Economic Letters (EEL), 10(1). https://doi.org/10.52783/eel.v10i1.1810
Dave, A., Shiva, K., Etikani, P., Bhaskar, V. V. S. R., & Choppadandi, A. (2022). Serverless AI: Democratizing machine learning with cloud functions. Journal of Informatics Education and Research, 2(1), 22-35. http://jier.org
Dave, A., Etikani, P., Bhaskar, V. V. S. R., & Shiva, K. (2020). Biometric authentication for secure mobile payments. Journal of Mobile Technology and Security, 41(3), 245-259.
Saoji, R., Nuguri, S., Shiva, K., Etikani, P., & Bhaskar, V. V. S. R. (2021). Adaptive AI-based deep learning models for dynamic control in software-defined networks. International Journal of Electrical and Electronics Engineering (IJEEE), 10(1), 89–100. ISSN (P): 2278–9944; ISSN (E): 2278–9952
Narendra Sharad Fadnavis. (2021). Optimizing Scalability and Performance in Cloud Services: Strategies and Solutions. International Journal on Recent and Innovation Trends in Computing and Communication, 9(2), 14–21. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10889
Nitin Prasad. (2022). Security Challenges and Solutions in Cloud-Based Artificial Intelligence and Machine Learning Systems. International Journal on Recent and Innovation Trends in Computing and Communication, 10(12), 286–292. Retrieved from https://www.ijritcc.org/index.php/ijritcc/article/view/10750
Prasad, N., Narukulla, N., Hajari, V. R., Paripati, L., & Shah, J. (2020). AI-driven data governance framework for cloud-based data analytics. Volume 17, (2), 1551-1561.
Big Data Analytics using Machine Learning Techniques on Cloud Platforms. (2019). International Journal of Business Management and Visuals, ISSN: 3006-2705, 2(2), 54-58. https://ijbmv.com/index.php/home/article/view/76
Shah, J., Narukulla, N., Hajari, V. R., Paripati, L., & Prasad, N. (2021). Scalable machine learning infrastructure on cloud for large-scale data processing. Tuijin Jishu/Journal of Propulsion Technology, 42(2), 45-53.
Narukulla, N., Lopes, J., Hajari, V. R., Prasad, N., & Swamy, H. (2021). Real-time data processing and predictive analytics using cloud-based machine learning. Tuijin Jishu/Journal of Propulsion Technology, 42(4), 91-102
Secure Federated Learning Framework for Distributed Ai Model Training in Cloud Environments. (2019). International Journal of Open Publication and Exploration, ISSN: 3006-2853, 7(1), 31-39. https://ijope.com/index.php/home/article/view/145
Paripati, L., Prasad, N., Shah, J., Narukulla, N., & Hajari, V. R. (2021). Blockchain-enabled data analytics for ensuring data integrity and trust in AI systems. International Journal of Computer Science and Engineering (IJCSE), 10(2), 27–38. ISSN (P): 2278–9960; ISSN (E): 2278–9979. DOI: 10.36227/techrxiv.171340711.17793838/v1
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2019). Investigating the use of natural language processing (NLP) techniques in automating the extraction of regulatory requirements from unstructured data sources. Annals of Pharma Research, 7(5),
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2021). Navigating regulatory requirements for complex dosage forms: Insights from topical, parenteral, and ophthalmic products. NeuroQuantology, 19(12), 15.
Challa, S. S. S., Tilala, M., Chawda, A. D., & Benke, A. P. (2022). Quality management systems in regulatory affairs: Implementation challenges and solutions. Journal for Research in Applied Sciences
Vijay Kumar Reddy Voddi, Komali Reddy Konda(2022), “Success and Struggle: Countries that Minimized COVID-19 Cases and the Factors Behind Their Outcomes,”ResMilitaris,Volume -12, Issue -5 (2022 ) Keywords: COVID-19, Pandemic Response, Public Health Strategies, Case Minimization, GlobalHealth,Epidemiology,https://resmilitaris.net/issue-content/success-and-struggle-countries-that-minimized-covid-19-cases-and-the-factors-behind-their-outcomes-4043
Vijay Kumar Reddy, Komali Reddy Konda(2021),“Unveiling Patterns: Seasonality Analysis of COVID-19 Data in the USA”, Keywords: COVID-19, Seasonality, SARS-CoV-2, Time Series Analysis, Environmental Factors, USA, Neuroquantology | October 2021 | Volume 19 | Issue 10 | Page 682-686|Doi: 10.48047/nq.2021.19.10.NQ21219
Vijay Kumar Reddy, Komali Reddy Konda(2021), “COVID-19 Case Predictions: Anticipating Future Outbreaks Through Data” Keywords: COVID-19, Case Predictions, Machine Learning, Time Series Forecasting, Pandemic Response, Epidemiological Modeling, NeuroQuantology | July 2021 | Volume 19 | Issue 7 | Page 461-466| doi: 10.48047/nq.2021.19.7.NQ21136
Vijay Kumar Reddy Voddi, Komali Reddy Konda(2021),“Spatial Distribution And Dynamics Of Retail Stores In New York City,” Pages: 9941-9948 Keywords: Retail Distribution, Urban Planning, Economic Disparities, Gentrification, Online Shopping Trends.https://www.webology.org/abstract.php?id=5248
T Jashwanth Reddy, Voddi Vijay Kumar Reddy, T Akshay Kumar (2018),” Population Diagnosis System,” Published in International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), Keywords: Apache Hadoop 1.2.1,Apache hive-0.12.0,Population Diagnosis System, My SQL. https://ijarcce.com/upload/2018/february-18/IJARCCE%2038.pdf
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