ENHANCING DEVELOPER PRODUCTIVITY WITH AI-DRIVEN TOOLS: THE FUTURE OF CODING ASSISTANCE
Keywords:
Artificial Intelligence In Software Development, Developer Productivity Enhancement, AI-Assisted Code Generation, Ethical AI Implementation, Software Engineering EvolutionAbstract
This article explores the transformative impact of AI-driven tools on software development practices, examining how these technologies are reshaping developer productivity, code quality, and overall software engineering processes. The article analyzes various aspects of AI integration in development environments, including package management systems, code embeddings, and retrieval-augmented generation, while also investigating the ethical considerations and evolving role of developers. Through a comprehensive analysis of multiple research studies and industry implementations, this article demonstrates how AI-assisted development is revolutionizing traditional workflows, enhancing code quality, reducing technical debt, and accelerating innovation cycles across different sectors. The article also addresses the significance of proper AI tool optimization, the importance of developer skill evolution, and the broader societal implications of these technological advancements in software development.
References
K. Koskinen, "AI-assisted Software Development Effort Estimation," Master of Science in Technology Thesis University of Turku Department of Computing Software Engineering 2021. Available: https://www.utupub.fi/bitstream/handle/10024/152199/Koskinen_Karri_opinnayte.pdf?sequence=1
Daria Glushkova, "The influence of Artificial intelligence on productivity in Software development," Politecnico di Torino, 2023. [Online]. Available: https://webthesis.biblio.polito.it/secure/28435/1/tesi.pdf
J. Schouwenaar, "Understanding the impact of an AI coding assistant, GitHub’s Copilot, on developers and their work experiences," Eindhoven University of Technology, 2023. Available: https://pure.tue.nl/ws/portalfiles/portal/320756654/MTP_thesis_report_Joella_Schouwenaar.pdf
Yogesh K. Dwivedi, Anuj Sharma, et al., "Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions," Technological Forecasting and Social Change Volume 192, July 2023, 122579. Available: https://www.sciencedirect.com/science/article/pii/S0040162523002640
Alexey Ignatiev, et al., "Towards Efficient Optimization in Package Management Systems," International Conference on Software Engineering, 2014. Available: https://alexeyignatiev.github.io/assets/pdf/ijms-icse14-preprint.pdf
Justin Cappos, Justin Samuel, Scott Baker, John H. Hartman, "Package Management Security," University of Arizona, 2013. Available: https://ssl.engineering.nyu.edu/papers/cappos_pmsec_tr08-02.pdf
Tajinder Kumar Saini, et al., "Measuring Impact of Generative AI in Software Development and Innovation," Intelligent IT Solutions for Sustainability in Industry 5.0 Paradigm (pp.57-67), 2024. Available: https://www.researchgate.net/publication/382008611_Measuring_Impact_of_Generative_AI_in_Software_Development_and_Innovation
Yonatha Almeida, Danyllo Albuquerque, "AICodeReview: Advancing code quality with AI-enhanced reviews," Software Impacts, vol. 15, 100547, 2024. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S2352711024000487
Ridi Ferdiana, "The Impact of Artificial Intelligence on Programmer Productivity," International Conference On Software Engineering And Information Technology (Icoseit) 2024 at : Bandung, Indonesia volume: 2. Available: https://www.researchgate.net/publication/378962192_The_Impact_of_Artificial_Intelligence_on_Programmer_Productivity
D. Ajiga, "Enhancing software development practices with AI insights in high- tech companies," IEEE Software Engineering Institute, Technical Report TR-2024-003, 2024. Available: https://www.researchgate.net/profile/Daniel-Ajiga/publication/383410449_Enhancing_software_development_practices_with_AI_insights_in_high-tech_companies
Vinay Puri, "Measuring the Impact of AI Initiatives on Organizational Productivity: Best Practices and Tips," International Research Journal of Engineering and Technology (IRJET), 2024. Available: https://www.researchgate.net/publication/383064720_Measuring_the_Impact_of_AI_Initiatives_on_Organizational_Productivity_Best_Practices_and_Tips
Rimsha Naeem, Marko Kohtamäki & Vinit Parida, "Artificial intelligence enabled product–service innovation: past achievements and future directions," Review of Managerial Science, vol. 18, no. 1, pp. 89-112, 2024. Available: https://link.springer.com/article/10.1007/s11846-024-00757-x
Jan H.R. Woerner, Aleksandra, et al., "Transformative Potentials and Ethical Considerations of AI Tools in Higher Education: Case Studies and Reflections," IEEE SoutheastCon 2024. Available: https://ieeexplore.ieee.org/document/10500042
Oluwaseun Lottu, "Towards a conceptual framework for ethical AI development in IT systems," World Journal of Advanced Research and Reviews 21(3):408-415, 2024. Available: https://www.researchgate.net/publication/379429840_Towards_a_conceptual_framework_for_ethical_AI_development_in_IT_systems
Likoebe M. Marupinga, et al., "The evolution of software development orchestration: current state and an agenda for future research," European Journal of Information Systems, vol. 29, no. 6, pp. 585-604, 2020. Available: https://www.tandfonline.com/doi/full/10.1080/0960085X.2020.1831834
Bruna Moema Dias Bahmed, "Integrated Development Environments: Exploring the Impact of the Implementation of Artificial Intelligence on Workflow Efficiency and its Potential for Developer Displacement," University of Bologna, 2024. [Online]. Available: https://amslaurea.unibo.it/id/eprint/32224/1/Integrated%20Development%20Environments%20Exploring%20the%20Impact%20of%20the%20Implementation%20of%20Artificial%20Intelligence%20on%20Workflow%20Efficiency%20and%20its%20Potential%20for%20Developer%20Displacement.pdf
