Open Access
| Issue |
E3S Web Conf.
Volume 645, 2025
The 1st International Conference on Green Engineering for Sustainable Future (ICoGESF 2025)
|
|
|---|---|---|
| Article Number | 04002 | |
| Number of page(s) | 12 | |
| Section | Automation and Smart Manufacturing | |
| DOI | https://doi.org/10.1051/e3sconf/202564504002 | |
| Published online | 28 August 2025 | |
- Bengesi, S. et al. Advancements in Generative AI: A Comprehensive Review of GANs, GPT, Autoencoders, Diffusion Model, and Transformers. IEEE Access 12, 9812-9837 (2024). [Google Scholar]
- Karlovs-Karlovskis, U. Generative Artificial Intelligence in Undergraduate Engineering: A Systematic Literature Review. Appl. Comput. Syst. 29, 8-77 (2024). [Google Scholar]
- V.V., H. & I.V., P. the Use of Generative Artificial Intelligence in Software Testing. Syst. Technol. 2, 113-123 (2024). [Google Scholar]
- Aarti. Generative AI in Software Development : an Overview and Evaluation of Modern Coding Tools. Int. J. Multidiscip. Res. 6, 1-9 (2024). [Google Scholar]
- Atemkeng, M. et al. Ethics of Software Programming with Generative AI: Is Programming without Generative AI always radical? (2024). [Google Scholar]
- Prajakta, M., Khade, S. & Sambhe, R. U. A Review of Code Generation, Testing, Maintenance and Security. 08, 1632-1641 (2025). [Google Scholar]
- Giralt, E. & Barcelona, H. Bias and Error Mitigation in Software-Generated Data: An Advanced Search and Optimization Framework Leveraging Generative Code Models. 1-16 (2023). [Google Scholar]
- Golda, A. et al. Privacy and Security Concerns in Generative AI: A Comprehensive Survey. IEEE Access 12, 48126-48144 (2024). [Google Scholar]
- Page, M. J. et al. PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ 372, (2021). [Google Scholar]
- Calegario, F. et al. Exploring the intersection of Generative AI and Software Development. 1-38 (2023). [Google Scholar]
- Alenezi, M. & Akour, M. Ai-Driven Innovations in Software Engineering: A Review of Current Practices and Future Directions. Appl. Sci. 15, 1-26 (2025). [Google Scholar]
- White, J., Hays, S., Fu, Q., Spencer-Smith, J. & Schmidt, D. C. ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design. Gener. AI Eff. Softw. Dev. 71-108 (2024) DOI: 10.1007/978-3-031-55642-5_4. [Google Scholar]
- Banh, L., Holldack, F. & Strobel, G. Copiloting the future: How generative AI transforms Software Engineering. Inf. Softw. Technol. 183, (2025). [Google Scholar]
- Ale, N. K. A Generative AI Framework for Enhancing Software Test Automation: Design, Implementation, and Validation. International Journal of Science and Research (IJSR) vol. 13 571-574 at https://doi.org/10.21275/sr2404032016 (2024). [Google Scholar]
- Benjamin, M. AI and Machine Learning in Software Development. (2025). [Google Scholar]
- Yetiştiren, B., Özsoy, I., Ayerdem, M. & Tüzün, E. Evaluating the Code Quality of AI-Assisted Code Generation Tools: An Empirical Study on GitHub Copilot, Amazon CodeWhisperer, and ChatGPT. (2023). [Google Scholar]
- Cotroneo, D., De Luca, R. & Liguori, P. DeVAIC: A Tool for Security Assessment of AI-generated Code. Inf. Softw. Technol. 177, 107572 (2024). [Google Scholar]
- Gioacchini, L. et al. AutoPenBench: Benchmarking Generative Agents for Penetration Testing. ArXiv at https://doi.org/10.48550/arXiv.2410.03225(2024). [Google Scholar]
- Nagpal, A. AI Copilot for the Modern Developer : Leveraging GenAI in Software Development. 702-711 (2024). [Google Scholar]
- Bajaj, Y. & Samal, M. Accelerating Software Quality: Unleashing the Power of Generative AI for Automated Test-Case Generation and Bug Identification. International Journal for Research in Applied Science and Engineering Technology at https://doi.org/10.22214/ijraset.2023.54628 (2023). [Google Scholar]
- Arora, C., Grundy, J. C. & Abdelrazek, M. Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs. ArXiv at https://doi.org/10.48550/arXiv.2310.13976(2023). [Google Scholar]
- Khan, S. A. & Oshin, N. T. AI-Based Software Testing AI based Software Testing. (2024) DOI: 10.1007/978-981-99-8346-9. [Google Scholar]
- Bazzan, T. et al. Analysing the Role of Generative AI in Software Engineering - Results from an MLR. 163-180 (2024) DOI: 10.1007/978-3-031-71139-8_11. [Google Scholar]
- Pangakis, N., Wolken, S. & Fasching, N. Automated Annotation with Generative AI Requires Validation. ArXiv at https://doi.org/10.48550/arXiv.2306.00176(2023). [Google Scholar]
- Yang, C. et al. AutoVerus: Automated Proof Generation for Rust Code. ArXiv at https://doi.org/10.48550/arXiv.2409.13082(2024). [Google Scholar]
- Sodano, J. T. & DeFranco, J. F. Citizen Development, Low-Code/No-Code Platforms, and the Evolution of Generative AI in Software Development. Computer vol. 58 101-104 at https://doi.org/10.1109/mc.2025.3547073(2025). [Google Scholar]
- Bui, N. D. Q. et al. CodeTF: One-stop Transformer Library for State-of-the-art Code LLM. ArXiv at https://doi.org/10.48550/arXiv.2306.00029(2023). [Google Scholar]
- DeepSeek-AI et al. DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence. 1-19 (2024). [Google Scholar]
- Daniel Ajiga, Patrick Azuka Okeleke, Samuel Olaoluwa Folorunsho & Chinedu Ezeigweneme. Enhancing software development practices with AI insights in hightech companies. Comput. Sci. IT Res. J. 5, 1897-1919 (2024). [Google Scholar]
- Haldar, S. Exploring the Integration of Generative AI Tools in Software Testing Education: A Case Study on ChatGPT and Copilot for Preparatory Testing Artifacts in Postgraduate Learning. IEEE Access 13, 46070-46090 (2025). [Google Scholar]
- Ebert, C., Louridas, P. & Ebert, C. Generative AI for Software Practitioners. IEEE Software vol. 40 30-38 at https://doi.org/10.1109/MS.2023.3265877 (2023). [Google Scholar]
- Ritesh Kumar. Generative AI in Software Architecture: Transforming Design and Development Processes. International Journal on Science and Technology vol. 16 at https://doi.org/10.71097/ijsat.v1.i16.3718(2025). [Google Scholar]
- Baudry, B. et al. Generative AI to Generate Test Data Generators. IEEE Software vol. 41 55-64 at https://doi.org/10.1109/MS.2024.3418570(2024). [Google Scholar]
- Bull, C. & Kharrufa, A. Generative Artificial Intelligence Assistants in Software Development Education: A Vision for Integrating Generative Artificial Intelligence Into Educational Practice, Not Instinctively Defending Against It. IEEE Software vol. 41 52-59 at https://doi.org/10.1109/MS.2023.3300574(2023). [Google Scholar]
- Ronanki, K., Cabrero-Daniel, B., Horkoff, J. & Berger, C. Requirements Engineering Using Generative AI: Prompts and Prompting Patterns. Generative AI for Effective Software Development 109-127 at https://doi.org/10.1007/978-3-031-55642-5_5 (2024). [Google Scholar]
- Tembhekar, P., Devan, M. & Jeyaraman, J. Role of GenAI in Automated Code Generation within DevOps Practices: Explore how Generative AI. Journal of Knowledge Learning and Science Technology ISSN: 2959-6386 (online) at https://doi.org/10.60087/jklst.vol2.n2.p512 (2023). [Google Scholar]
- Ferrag, M. et al. SecureFalcon: The Next Cyber Reasoning System for Cyber Security. ArXiv at https://doi.org/10.48550/arXiv.2307.06616 (2023). [Google Scholar]
- Mehmood, A., Ilyas, Q. M., Ahmad, M. & Shi, Z. Test Suite Optimization Using Machine Learning Techniques: A Comprehensive Study. IEEE Access vol. 12 168645-168671 at https://doi.org/10.1109/ACCESS.2024.3490453(2024). [Google Scholar]
- Lu, Q., Zhu, L., Xu, X., Xing, Z. & Whittle, J. Toward Responsible AI in the Era of Generative AI: A Reference Architecture for Designing Foundation Model-Based Systems. IEEE Software vol. 41 91-100 at https://doi.org/10.1109/MS.2024.3406333 (2024). [Google Scholar]
- Dilip, M. & Modi, B. Transforming Software Development Through Generative AI: A Systematic Analysis of Automated Development Practices. (2024). [Google Scholar]
- Ulfsnes, R., Moe, N. B., Stray, V. & Skarpen, M. Transforming Software Development with Generative AI: Empirical Insights on Collaboration and Workflow. Gener. AI Eff. Softw. Dev. 219-234 (2024) DOI: 10.1007/978-3-031-55642-5_10. [Google Scholar]
- Islam, S. A. M., Bari, M. D. S. & Sarkar, A. Transforming Software Testing in the US: Generative AI Models for Realistic User Simulation. Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 vol. 635-659 at https://doi.org/10.60087/jaigs.v6i1.292 (2024). [Google Scholar]
- Arora, C., Grundy, J. & Abdelrazek, M. Advancing Requirements Engineering Through Generative AI: Assessing the Role of LLMs. Generative AI for Effective Software Development 129-148 at https://doi.org/10.1007/978-3-031-55642-5_ (2024). [Google Scholar]
- Baron, P. Are AI detection and plagiarism similarity scores worthwhile in the age of ChatGPT and other Generative AI? Scholarship of Teaching and Learning in the South at https://doi.org/10.36615/sotls.v8i2.411 (2024). [Google Scholar]
- Banerjee, A., Ahmad, A., Bhalla, P. & Goyal, K. Assessing the Efficacy of ChatGPT in Solving Questions Based on the Core Concepts in Physiology. Cureus vol. 15 at https://doi.org/10.7759/cureus.43314(2023). [Google Scholar]
- Baqar, M. Balancing Innovation and Ethics in AI-Driven Software Development 1. 1 Introduction to AI Tools in Software Development Ethical Implications on Code Ownership. 1-20. [Google Scholar]
- Hsu, H.-P. Can Generative Artificial Intelligence Write an Academic Journal Article? Opportunities, Challenges, and Implications. Irish Journal of Technology Enhanced Learning at https://doi.org/10.22554/ijtel.v7i2.152(2023). [Google Scholar]
- Loh, E. ChatGPT and generative AI chatbots: challenges and opportunities for science, medicine and medical leaders. BMJ Leader vol. 8 at https://doi.org/10.1136/leader-2023-000797 (2023). [Google Scholar]
- Xiao, T., Hata, H., Treude, C. & Matsumoto, K. Generative AI for Pull Request Descriptions: Adoption, Impact, and Developer Interventions. ArXiv at https://doi.org/10.1145/3643773 (2024). [Google Scholar]
- Nama, P. Integrating AI in testing automation: Enhancing test coverage and predictive analysis for improved software quality. 13, 769-782 (2024). [Google Scholar]
- T’oth, R., Bisztray, T. & Erdodi, L. LLMs in Web-Development: Evaluating LLM- Generated PHP code unveiling vulnerabilities and limitations. ArXiv at https://doi.org/10.48550/arXiv.2404.14459(2024). [Google Scholar]
- Russo, D. Navigating the Complexity of Generative AI Adoption in Software Engineering. ACM Transactions on Software Engineering and Methodology vol. 33 1-50 at https://doi.org/10.1145/3652154 (2023). [Google Scholar]
- Tosi, D. Studying the Quality of Source Code Generated by Different AI Generative Engines: An Empirical Evaluation. Future Internet vol. 16 188 at https://doi.org/10.3390/fi16060188 (2024). [Google Scholar]
- Pandey, R., Singh, P., Wei, R. & Shankar, S. Transforming Software Development: Evaluating the Efficiency and Challenges of GitHub Copilot in Real-World Projects. ArXiv at https://doi.org/10.48550/arXiv.2406.17910(2024). [Google Scholar]
- Storey, M.-A. D., Russo, D., Novielli, N., Kobayashi, T. & Wang, D. A Disruptive Research Playbook for Studying Disruptive Innovations. ACM Transactions on Software Engineering and Methodology vol. 33 1-29 at https://doi.org/10.1145/3678172 (2024). [Google Scholar]
- White, J. Building Living Software Systems with Generative & Agentic AI. ArXiv at https://doi.org/10.48550/arXiv.2408.01768 (2024). [Google Scholar]
- Sridharan, S. et al. Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces. ArXiv at https://doi.org/10.48550/arXiv.2305.14516(2023). [Google Scholar]
- Jackson, V. et al. Creativity, Generative AI, and Software Development: A Research Agenda. ArXiv at https://doi.org/10.48550/arXiv.2406.01966(2024). [Google Scholar]
- Stalnaker, T. et al. Developer Perspectives on Licensing and Copyright Issues Arising from Generative AI for Software Development. 1, 1-38 (2024). [Google Scholar]
- Sauvola, J., Tarkoma, S., Klemettinen, M., Riekki, J. & Doermann, D. Future of software development with generative AI. Autom. Softw. Eng. 31, 1-8 (2024). [Google Scholar]
- Håkansson, A. & Phillips-Wren, G. Generative AI and Large Language Models - Benefits, Drawbacks, Future and Recommendations. Procedia Comput. Sci. 246, 5458-5468 (2024). [Google Scholar]
- Layman, L. & Vetter, R. Generative Artificial Intelligence and the Future of Software Testing. Computer vol. 57 27-32 at https://doi.org/10.1109/mc.2023.3306998 (2024). [Google Scholar]
- Nguyen-Duc, A. et al. Generative Artificial Intelligence for Software Engineering - A Research Agenda. ArXiv at https://doi.org/10.48550/arXiv.2310.18648 (2023). [Google Scholar]
- Bahi, A. Integrating Generative AI for Advancing Agile Software Development and Mitigating Project Management Challenges. Int. J. Adv. Comput. Sci. Appl. 15, 54-61 (2024). [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

