ANALYSIS OF REQUIREMENTS VOLATILITY DURING SOFTWARE DEVELOPMENT LIFE CYCLE USING THE SPSS METHOD

Authors

  • Rakesh Mittapally Business Intelligence Architect/AI and ML Engineer, Virginia, USA. Author

DOI:

https://doi.org/10.34218/IJCET_16_03_027

Keywords:

SPSS Statistics, Analysis And Planning, Technical Requirements, Design And Prototypes, Coding And Product Development, Testing And Risk Assessment And Updates And Maintenance

Abstract

Development teams employ a process known as the process known as Software development Life Cycle (SDLC), Organize high-quality software A method of preparation saves time and money. Minimise risks associated with projects through anticipatory preparation. Process optimisation: Knowing the SDLC's software development process might assist researchers pinpoint areas for development. Researchers can suggest methodologies, strategies, and technologies that can increase the efficiency and effectiveness of the construction process by researching each stage of the SDLC, including requirements collecting, design, implementation, testing, and deployment. Methodological advancements: Analysing the SDLC's software development process may result in the creation of new methods or improvements to already-existing ones. Research may concentrate on DevOps techniques, hybrid approaches that incorporate various SDLC models, or agile methodologies, for instance. These changes make it easier for teams working on software to collaborate better, respond quickly to market demands, and produce software. Quality Assurance: Researchers can find quality assurance practises that can be incorporated into each phase by looking at the software development process inside the SDLC. This comprises strategies for testing, design reviews, code inspections, and requirements validation approaches. Researchers can assist businesses in delivering software products having fewer flaws and greater customer satisfaction by recognising and enhancing assurance of quality practises.IBM created SPSS statistics, a statistical software programme with features for data management, sophisticated analysis, multidimensional analytics, intelligence for business, and criminal investigation. Spa Inc. was founded by IBM for a long period before being bought out in 2009. The most recent versions are marketed under the name IBM SPSS statistics. Analysis and planning, technical requirements, Design and prototypes, Coding and Product Development, Testing and Risk Assessment and Updates and Maintenance.the Cronbach's Alpha Reliability result. The overall Cronbach's Alpha value for the model is .594 which indicates 59% reliability. From the literature review, the above 50% Cronbach's Alpha value model can be considered for analysis.

References

Bassil, Youssef. "A simulation model for the waterfall software development life cycle." arXiv preprint arXiv:1205.6904 (2012). https://doi.org/10.48550/arXiv.1205.6904

Kneuper, Ralf. "Software processes and life cycle models." Cham: Springer (2018). https://doi.org/10.1007/978-3-319-98845-0

Aleem, Saiqa, Luiz Fernando Capretz, and Faheem Ahmed. "Game development software engineering process life cycle: a systematic review." Journal of Software Engineering Research and Development 4, no. 1 (2016): 1-30. https://doi.org/10.1186/s40411-016-0032-7

Nagababu. K, “Evolution and Impact of Data Warehousing in Modern Business and Decision Support Systems” International Journal of Computer Science and Data Engineering., 2025, vol. 2, no. 2, pp. 1–11.doi: https://dx.doi.org/10.55124/jdit.v2i1.249

Nagababu. K, “Optimizing Image Processing in OmniView with EDAS Decision-Making” Journal of Business Intelligence and Data Analytics., 2025, vol. 2, no. 2, pp. 1–12.doi: https://dx.doi.org/10.55124/jbid.v2i2.248

Ramancha, Nitesh Kumar. Quantum Computing in Artificial Intelligence: Enhancing Machine Learning Algorithms with Linear Regression, Random Forest Regression, Support Vector Machines. Journal of Computer Science Applications and Information Technology, vol. 9, no. 1, 2024, pp. 1–16. DOI: 10.15226/2474-9257/9/1/00166.

Ramancha, Nitesh Kumar. "Leveraging Machine Learning for Predictive Modeling in 3D Printing of Composite Materials: A Comparative Study." International Journal of Intellectual Advancements and Research in Engineering Computations (IJIAREC), vol. 11, no. 4, Oct.–Dec. 2023, pp. 39–58. https://doi.org/10.61096/ijiarec.v11.iss4.2023.39-58.

Leau, Yu Beng, WooiKhong Loo, Wai Yip Tham, and Soo Fun Tan. "Software development life cycle AGILE vs traditional approaches." In International Conference on Information and Network Technology, vol. 37, no. 1, pp. 162-167. 2012.

Mittapally. R, “Optimizing Business Intelligence Solutions: A TOPSIS-based Assessment of Micro Strategy Implementation Alternatives” Journal of Business Intelligence and Data Analytics., 2025, vol. 2, no. 1, pp. 1–14. doi: https://dx.doi.org/10.55124/jbid.v2i1.237

Ramancha, Nitesh Kumar. “Machine Learning Implementation Disparities in Modern Supply Chains: A Performance Analysis Using the EDAS Methodology.” Journal of Computer Science Applications and Information Technology, vol. 7, no. 1, 2022, pp. 1–8. DOI: 10.15226/2474-9257/7/1/001511.

Ramancha, Nitesh Kumar. "Strategic Evaluation of SAP System Upgrades Using TOPSIS Method: A Comparative Analysis." Journal of Computer Science Applications and Information Technology, vol. 6, no. 2, 2021, pp. 1–10.

Bhuvaneswari, T., and S. Prabaharan. "A survey on software development life cycle models." International Journal of Computer Science and Mobile Computing 2, no. 5 (2013): 262-267.

Nurmuliani, Nur, Didar Zowghi, and Steven Powell. "Analysis of requirements volatility during software development life cycle." In 2004 Australian Software Engineering Conference. Proceedings., pp. 28-37. IEEE, 2004.10.1109/ASWEC.2004.1290455

Crnkovic, Ivica, Michel Chaudron, and Stig Larsson. "Component-based development process and component lifecycle." In 2006 International Conference on Software Engineering Advances (ICSEA'06), pp. 44-44. IEEE, 2006.

Nagababu. K, “Innovative Fabrication of Advanced Robots Using the Waspas Method A New Era in Robotics Engineering” International Journal of Robotics and Machine Learning Technologies., 2025, vol. 1, no. 1, pp. 1–12. doi: http://dx.doi.org/10.55124/jmms.v1i1.235

Mittapally R (2023). Evaluating MicroStrategy Mobile and Competing Business Intelligence Solutions: A Multi-Criteria Decision-Making Approach. J Comp Sci Appl Inform Technol. 8(1): 1-9.

Mittapally R (2024). Intelligent Framework Selection: Leveraging MCDM in Web Technology Decisions. J Comp Sci Appl Inform Technol. 9(1): 1-9.

Mishra, Apoorva, and Deepty Dubey. "A comparative study of different software development life cycle models in different scenarios." International Journal of Advance research in computer science and management studies 1, no. 5 (2013).

Nagababu. K, “Machine Learning Approaches to Predict Tensile Strength in Nanocomposite Materials a Comparative Analysis” Journal of Artificial intelligence and Machine Learning., 2024, vol. 2, no. 1, pp. 1–16. doi: http://dx.doi.org/10.55124/jaim.v2i1.255

Mittapally. R, “Security First: Evaluating Cloud Services for Data Protection and Compliance” International Journal of Computer Science and Data Engineering., Int. J. of. Comp. Sci. and Data Eng.2025, 2, 51-59. doi: https://dx.doi.org/10.55124/csdb.v1i1.240

Davis, Noopur. Secure software development life cycle processes: A technology scouting report. Carnegie Mellon University, Software Engineering Institute, 2005.

Ragunath, P. K., S. Velmourougan, P. Davachelvan, S. Kayalvizhi, and R. Ravimohan. "Evolving a new model (SDLC Model-2010) for software development life cycle (SDLC)." International Journal of Computer Science and Network Security 10, no. 1 (2010): 112-119.

Khan, Mumtaz Ahmad, Azra Parveen, and Mohd Sadiq. "A method for the selection of software development life cycle models using analytic hierarchy process." In 2014 International Conference on Issues and Challenges in Intelligent Computing Techniques (ICICT), pp. 534-540. IEEE, 2014.

Khan, Mohd Ehmer, and Farmeena Khan. "Importance of software testing in software development life cycle." International Journal of Computer Science Issues (IJCSI) 11, no. 2 (2014): 120.

Mittapally. R, “Evaluating Machine Learning Techniques for Demand Forecasting in Supply Chains Using MOORA Method” Journal of Artificial Intelligence and Machine Learning., 2025, vol. 3, no. 1, pp. 1–13. doi: https://dx.doi.org/10.55124/jaim.v3i1.259

Davis, Alan M., Edward H. Bersoff, and Edward R. Comer. "A strategy for comparing alternative software development life cycle models." IEEE Transactions on software Engineering 14, no. 10 (1988): 1453-1461.

Chakraborty, Abhijit, Mrinal Kanti Baowaly, Ashraful Arefin, and Ali NewazBahar. "The role of requirement engineering in software development life cycle." Journal of emerging trends in computing and information sciences 3, no. 5 (2012).

Nagababu. K, “Machine Learning Techniques in Fracture Mechanics a Comparative Study of Linear Regression, Random Forest, and Ada Boost Model” Journal of Artificial intelligence and Machine Learning., 2024, vol. 2, no. 2, pp. 1–13. doi: http://dx.doi.org/10.55124/jaim.v2i2.257

Tuteja, Maneela, and Gaurav Dubey. "A research study on importance of testing and quality assurance in software development life cycle (SDLC) models." International Journal of Soft Computing and Engineering (IJSCE) 2, no. 3 (2012): 251-257.

Mittapally. R, “Redefining Business Intelligence Architecture with the EDAS Optimization Model” Journal of Business Intelligence and Data Analytics., 2025, vol. 3, no. 1, pp. 1–13. doi: https://dx.doi.org/10.55124/jbid.v1i2.249

Mittapally. R, “Predictive Modeling of Surface Roughness in Manufacturing A Study Using Multiple Machine Learning Techniques” International Journal of Robotics and Machine Learning Technologies., 2025, vol. 1, no. 1, pp. 19–33. doi: https://dx.doi.org/10.55124/jmms.v1i1.237

Gurung, Gagan, Rahul Shah, and Dhiraj Prasad Jaiswal. "Software Development Life Cycle Models-A Comparative Study." International Journal of Scientific Research in Computer Science, Engineering and Information Technology, March (2020): 30-37. https://doi.org/10.32628/CSEIT206410

Velmourougan, Suburayan, P. Dhavachelvan, R. Baskaran, and B. Ravikumar. "Software development Life cycle model to build software applications with usability." In 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 271-276. IEEE, 2014.

Ramancha, N. K. "Evaluating the Role of Artificial Intelligence in Solar Energy Optimization Using the COPRAS Method." Advances in Computer Sciences, vol. 4, no. 1, Nov. 2022, p. 123. Boffin Access Limited, doi:10.31021/ACS224123.

Ramancha, Nitesh Kumar. "Data-Driven Decision-Making in Supply Chain Optimization." Advances in Computer Sciences, vol. 4, no. 1, 2022, Boffin Access Limited, doi:10.31021/ACS224124.

Mittapally R (2023). Evaluating Business Intelligence Alternatives: COPRAS vs Traditional Models in MicroStrategy. J Comp Sci Appl Inform Technol. 8(1): 1-9.

Mittapally R (2023). Evaluating MicroStrategy Mobile and Competing Business Intelligence Solutions: A Multi-Criteria Decision-Making Approach. J Comp Sci Appl Inform Technol. 8(1): 1-9.

Chowdhury, A. Z. M., Abhijit Bhowmik, Hasibul Hasan, and Md Shamsur Rahim. "Analysis of the veracities of industry used software development life cycle methodologies." arXiv preprint arXiv:1805.08631 (2018). https://doi.org/10.48550/arXiv.1805.08631

Sultan, Khalid, Abdeslam En-Nouaary, and AbdelwahabHamou-Lhadj. "Catalog of metrics for assessing security risks of software throughout the software development life cycle." In 2008 International Conference on Information Security and Assurance (isa 2008), pp. 461-465. IEEE, 2008.

Mittapally. R, “Predictive Modeling of Surface Roughness in Manufacturing A Study Using Multiple Machine Learning Techniques” International Journal of Robotics and Machine Learning Technologies., 2025, vol. 1, no. 1, pp. 19–33. doi: https://dx.doi.org/10.55124/jmms.v1i1.237

Ramancha, Nitesh Kumar. "A Comparative Study of SAP Migration Approaches: Integration of PROMETHEE Method for Strategic Decision Making." International Journal of Intellectual Advancements and Research in Engineering Computations (IJIAREC), vol. 11, no. 4, Oct.–Dec. 2023, pp. 23–38. https://doi.org/10.61096/ijiarec.v11.iss4.2023.23-38.

Majid, Rogayah A., Nor Laila M. Noor, Wan Adilah Wan Adnan, and Suria Mansor. "A survey on user involvement in software development life cycle from practitioner's perspectives." In 5th International Conference on Computer Sciences and Convergence Information Technology, pp. 240-243. IEEE, 2010.10.1109/ICCIT.2010.5711064

Downloads

Published

2025-06-09

How to Cite

Rakesh Mittapally. (2025). ANALYSIS OF REQUIREMENTS VOLATILITY DURING SOFTWARE DEVELOPMENT LIFE CYCLE USING THE SPSS METHOD. INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING AND TECHNOLOGY, 16(3), 414-432. https://doi.org/10.34218/IJCET_16_03_027