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AI In Modern Software Development: Current Practices, Challenges and Future Possibilities

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Artificial Intelligence is fast emerging as an 
inseparable part of software engineering. Its impact on 
modern software development is significantly high. 
Though writing code or to be more precise, generating 
code through AI systems and tools facilitates the 
development of a wide variety of products, there are 
ethical considerations, risks, and limitations that 
ultimately affect the overall quality of the software. This 
research paper highlights how AI is used in modern 
software design, development, testing, security, and 
management processes and they are flawlessly 
streamlined for enhanced productivity and quality. The 
research describes how AI is important in software 
engineering as firms without employing AI in SDLC are 
susceptible to underperforming. It provides insights into, 
what it could help with in terms of developing modern 
and scalable applications, and the ethics involved in AI driven software engineering. It also highlights 
limitations underlying the applications of AI in the past, 
present, and future. 

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2025-01-21
Artificial Intelligence is fast emerging as an inseparable part of software engineering. Its impact on modern software development is significantly high. Though writing code or to be more precise, generating code through AI systems and tools facilitates the development of a wide variety of products, there are ethical considerations, risks, and limitations that ultimately affect the overall quality of the software. This research paper highlights how AI is used in modern software design, development, testing, security, and management processes and they are flawlessly streamlined for enhanced productivity and quality. The research describes how AI is important in software engineering as firms without employing AI in SDLC are susceptible to underperforming. It provides insights into, what it could help with in terms of developing modern and scalable applications, and the ethics involved in AIdriven software engineering. It also highlights limitations underlying the applications of AI in the past, present, and future.

References

  • Hernández-Ledesma, G., Ramos, E. G., y Fernández, C. A. F., Aguilar-Cisneros, J. R., Rosas-Sumano, J. J., & Morales-Ignacio, L. A. (2017). Selection of Best Software Engineering Practices: A Multi-Criteria Decision Making Approach. Res. Comput. Sci., 136, 47-60. 2. Farley, D. (2021). Modern Software Engineering: Doing What Works to Build Better Software Faster. Netherlands: Pearson Education. 3. Seemann, M. (2021). Code That Fits in Your Head: Heuristics for Software Engineering. United Kingdom: Pearson Education. 4. Pantiuchina, J., Mondini, M., Khanna, D., Wang, X., & Abrahamsson, P. (2017). Are software startups applying agile practices? The state of the practice from a large survey. In Agile Processes in Software Engineering and Extreme Programming: 18th International Conference, XP 2017, Cologne, Germany, May 22-26, 2017, Proceedings 18 (pp. 167-183). Springer International Publishing. 5. Barenkamp, M., Rebstadt, J., & Thomas, O. (2020). Applications of AI in classical software engineering. AI Perspectives, 2(1), 1. 6. Amershi, S., Begel, A., Bird, C., DeLine, R., Gall, H., Kamar, E., ... & Zimmermann, T. (2019, May). Software engineering for machinelearning: A case study. In 2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Practice (ICSE-SEIP) (pp. 291-300). IEEE. 7. Marar, H. W. (2024). Advancements in software engineering using AI. Computer Software and Media Applications, 6(1), 3906. 8. Shneiderman, B. (2020). Bridging the gap between ethics and practice: guidelines for reliable, safe, and trustworthy human-centered AI systems. ACM Transactions on Interactive Intelligent Systems (TiiS), 10(4), 1-31. 9. Philipson, G. (2004). A short history of software. In Management, Labour Process and Software Development (pp. 13-44). Routledge. 10. Mijwel, M. M. (2015). History of Artificial Intelligence Yapay Zekânın T arihi. Computer Science,(April 2015), 3-4. 11. Vaidya, J., & Asif, H. (2023). A Critical Look at AI-Generate Software: Coding with the New AI Tools is Both Irresistible and Dangerous. Ieee Spectrum, 60(7), 34-39. 12. De Silva, D., & Alahakoon, D. (2022). An artificial intelligence life cycle: From conception to production. Patterns, 3(6). 13. Liu, B., Li, G., Zhang, H., Jin, Y., Wang, Z., & Shao, D. (2024). The Gap Between Trustworthy AI Research and Trustworthy Software Research: A Tertiary Study. ACM Computing Surveys, 57(3), 1-40. 14. Kulkarni, R. H., & Padmanabham, P. (2017). Integration of artificial intelligence activities in software development processes and measuring the effectiveness of integration. Iet Software, 11(1), 18-26. 15. Padmanaban, P. H., & Sharma, Y. K. (2019). Implication of Artificial Intelligence in Software Development Life Cycle: A state of the art review. 2019 IJRRA all rights reserved. 16. Liang, J. T., Yang, C., & Myers, B. A. (2024, February). A large-scale survey on the usability of AI programming assistants: Successes and challenges. In Proceedings of the 46th IEEE/ACM International Conference on Software Engineering (pp. 1-13). 17. Pinto, G., De Souza, C., Rocha, T., Steinmacher, I., Souza, A., & Monteiro, E. (2024, April). Developer Experiences with a Contextualized AI Coding Assistant: Usability, Expectations, and Outcomes. In Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering-Software Engineering for AI (pp. 81-91). 18. Maninger, D., Narasimhan, K., & Mezini, M. (2024, April). Towards Trustworthy AI Software Development Assistance. In Proceedings of the 2024 ACM/IEEE 44th International Conference on Software Engineering: New Ideas and Emerging Results (pp. 112-116). 19. Perry, N., Srivastava, M., Kumar, D., & Boneh, D. (2023, November). Do users write more insecure code with AI assistants?. In Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security (pp. 2785-2799). 20. Heusser, M., & Larsen, M. (2023). Software Testing Strategies: A testing guide for the 2020s. Packt Publishing Ltd. 21. Kasowaki, L., & Akara, N. (2023). Exploratory Testing Strategies for Software Quality Assurance (No. 11360). EasyChair. 22. Donvir, A., Panyam, S., Paliwal, G., & Gujar, P. (2024, October). The Role of Generative AI Tools in Application Development: A Comprehensive Review of Current Technologies and Practices. In 2024 International Conference on Engineering Management of Communication and Technology (EMCTECH) (pp. 1-9). IEEE. 23. Korzeniowski, Ł., & Goczyła, K. (2019). Artificial intelligence for software development: the present and the challenges for the future. Biuletyn Wojskowej Akademii Technicznej, 68(1). 24. Hossain Faruk, M. J., Pournaghshband, H., & Shahriar, H. (2022, October). AI-oriented software engineering (AIOSE): challenges, opportunities, and new directions. In International Conference on Software Process Improvement (pp. 3-19). Cham: Springer International Publishing. 25. Khaliq, Z., Farooq, S. U., & Khan, D. A. (2022). Artificial intelligence in software testing: Impact, problems, challenges and prospect. arXiv preprint arXiv:2201.05371. 26. Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobiezky, F., Zellinger, W., ... & Moser, B. (2020). Ai system engineering—key challenges and lessons learned. Machine Learning and Knowledge Extraction, 3(1), 56-83. 27. Prather, J., Reeves, B. N., Leinonen, J., MacNeil, S., Randrianasolo, A. S., Becker, B. A., ... & Briggs, B. (2024, August). The widening gap: The benefits and harms of generative ai for novice programmers. In Proceedings of the 2024 ACM Conference on International Computing Education ResearchVolume 1 (pp. 469-486). 28. Santa Barletta, V., Cassano, F., Pagano, A., & Piccinno, A. (2022, November). New perspectives for cyber security in software development: when end-user development meets artificial intelligence. In 2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (pp. 531-534). IEEE. 29. Artificial Intelligence Methods For Software Engineering. (2021). Singapore: World Scientific Publishing Company. 30. Lean and Agile Software Development: 6th International Conference, LASD 2022, Virtual Event, January 22, 2022, Proceedings. (2022). Germany: Springer International Publishing. 31. Lee, K., Qiufan, C. (2021). AI 2041: Ten Visions for Our Future. United States: Crown. 32. Artificial Intelligence Methods For Software Engineering. (2021). Singapore: World Scientific Publishing Company. In International Conference on Software Process Improvement (pp. 3-19). Cham: Springer International Publishing. 25. Khaliq, Z., Farooq, S. U., & Khan, D. A. (2022). Artificial intelligence in software testing: Impact, problems, challenges and prospect. arXiv preprint arXiv:2201.05371. 26. Fischer, L., Ehrlinger, L., Geist, V., Ramler, R., Sobiezky, F., Zellinger, W., ... & Moser, B. (2020). Ai system engineering—key challenges and lessons learned. Machine Learning and Knowledge Extraction, 3(1), 56-83. 27. Prather, J., Reeves, B. N., Leinonen, J., MacNeil, S., Randrianasolo, A. S., Becker, B. A., ... & Briggs, B. (2024, August). The widening gap: The benefits and harms of generative ai for novice programmers. In Proceedings of the 2024 ACM Conference on International Computing Education ResearchVolume 1 (pp. 469-486). 28. Santa Barletta, V., Cassano, F., Pagano, A., & Piccinno, A. (2022, November). New perspectives for cyber security in software development: when end-user development meets artificial intelligence. In 2022 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (3ICT) (pp. 531-534). IEEE. 29. Artificial Intelligence Methods For Software Engineering. (2021). Singapore: World Scientific Publishing Company. 30. Lean and Agile Software Development: 6th International Conference, LASD 2022, Virtual Event, January 22, 2022, Proceedings. (2022). Germany: Springer International Publishing. 31. Lee, K., Qiufan, C. (2021). AI 2041: Ten Visions for Our Future. United States: Crown. 32. Artificial Intelligence Methods For Software Engineering. (2021). Singapore: World Scientific Publishing Company.