Yapay Zeka Tabanlı No-Code Platformlarının Yazılım Geliştirme Süreçlerine Etkisi: Literatür Taraması

Year 2025, Volume: 13 Issue: 1, 383 - 401, 30.01.2025

Osman Koç , İbrahim Yücedağ , Ümit Şentürk

https://doi.org/10.29130/dubited.1554356

Abstract

Bu literatür taraması, yapay zeka (artificial intelligence – AI) tabanlı kodsuz (no-code – NC) yazılım
geliştirme platformlarının yazılım süreçlerine olan etkilerini inceler. Çalışma, özellikle yazılım geliştirme süreçlerinin hızlanması, maliyetlerin azaltılması ve iş süreçlerinin optimizasyonu üzerinde durmaktadır. Literatürde yer alan mevcut çalışmalar, bu tür platformların teknik olmayan kullanıcıların bile karmaşık uygulamalar geliştirmelerini nasıl kolaylaştırdığını ve zaman-maliyet optimizasyonunu nasıl daha iyi hale getirdiğini göstermektedir. Bu inceleme, NC platformlarının, AI destekli araçlarla nasıl daha etkin ve verimli hale geldiğini, bu entegrasyonların mevcut yazılım geliştirme ekosistemini nasıl dönüştürdüğünü ortaya koymaktadır. Makale, AI tabanlı NC platformların potansiyel faydalarını ve karşılaşılabilecek zorlukları tartışarak, bu teknolojilerin yazılım endüstrisindeki gelecek vaatlerini vurgulamaktadır.

Keywords

Kodsuz, Az kodlu, Yapay zeka, Web geliştirme, Yazılım geliştirme maliyeti

The Impact of Artificial Intelligence Enhanced No-Code Software Development Platforms on Software Processes: A Literature Review

Abstract

This literature review examines the impact of artificial intelligence-based (AI-based) no-code software
development platforms on software processes. The study primarily focuses on accelerating software development processes, reducing costs, and optimizing business operations. Existing studies in the literature demonstrate how these types of platforms facilitate complex application development even for non-technical users and enhance time-cost optimization. This review highlights how no-code platforms have become more effective and efficient with AI-supported tools, transforming the current software development ecosystem. The article discusses the potential benefits and challenges of AI-based no-code platforms, emphasizing their promising future in the software industry.

Keywords

No-Code, Low-Code, AI, Web development, Software development cost

References

• [1] TÜSİAD Yazılım Çalışma Grubu et al., “Türkiye’de Yazılım Ekosisteminin Geleceği,” Deloitte, Jan. 2021.
• [2] M. R. DeLisi and C. Howley, “Gartner Forecasts Worldwide Low-Code Development Technologies Market to Grow 20% in 2023,” Gartner. Accessed: Aug. 01, 2024. [Online]. Available: https://www.gartner.com/en/newsroom/press-releases/2022-12-13-gartner-forecasts-worldwide-low code-development-technologies-market-to-grow-20-percent-in-2023
• [3] H. El Kamouchi, M. Kissi, and O. El Beggar, “Low-code/No-code Development : A systematic literature review,” in Proceedings - SITA 2023: 2023 14th International Conference on Intelligent Systems: Theories and Applications, Institute of Electrical and Electronics Engineers Inc., 2023. doi: 10.1109/SITA60746.2023.10373712.
• [4] Z. Jiang, F. F. Xu, J. Araki, and G. Neubig, “How Can We Know What Language Models Know?”, doi: 10.1162/tacl.
• [5] D. Jurafsky and J. H. Martin, “Speech and Language Processing An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition with Language Models Third Edition draft Summary of Contents.”
• [6] B. Akbulut, “Büyük Dil Modelleri: Dilin Evrimi ve Yapay Zekâ (Bölüm 2),” Medium. Accessed: Jul. 25, 2024. [Online]. Available: https://medium.com/kodluyoruz/büyük-dil-modelleri-dilin-evrimi-ve-yapay-zekâ-bölüm-2-458ddea54f09
• [7] B. Akbulut, “Generative AI: Yapay Zekâ Dünyasının Yaratıcı Gücü ~ Bölüm 1,” Medium. Accessed: Jul. 25, 2024. [Online]. Available: https://medium.com/kodluyoruz/%C3%BCretken-yapay zek%C3%A2-yapay-zek%C3%A2-d%C3%BCnyas%C4%B1n%C4%B1n-yarat%C4%B1c%C4%B1 g%C3%BCc%C3%BC-b%C3%B6l%C3%BCm-1-a7fc1ad65dd6
• [8] P. van Lunteren, “EcoAssist: A no-code platform to train and deploy custom YOLOv5 object detection models,” J Open Source Softw, vol. 8, no. 88, p. 5581, Aug. 2023, doi: 10.21105/joss.05581.
• [9] M. Moskal, “No-Code Application Development on the Example of Logotec App Studio Platform,” Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Srodowiska, vol. 11, no. 1, pp. 54–57, 2021, doi: 10.35784/IAPGOS.2429.
• [10] T. Nur and F. 1, “ELT FORUM 12(1) (2023) Journal of English Language Teaching Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay,” Journal of English Language Teaching, vol. 6, no. 1, 2017, [Online]. Available: http://journal.unnes.ac.id/sju/index.php/elt
• [11] Ö. Aydin and E. Karaarslan, “OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare.” [Online]. Available: https://ssrn.com/abstract=4308687
• [12] L. Floridi and M. Chiriatti, “GPT-3: Its Nature, Scope, Limits, and Consequences,” Dec. 01, 2020, Springer Science and Business Media B.V. doi: 10.1007/s11023-020-09548-1.
• [13] J. Liu, C. Liu, P. Zhou, R. Lv, K. Zhou, and Y. Zhang, “Is ChatGPT a Good Recommender? A Preliminary Study,” Oct. 2023.
• [14] P. Dhoke and P. Lokulwar, “Evaluating the Impact of No-Code/Low-Code Backend Services on API Development and Implementation: A Case Study Approach,” in 2023 14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023, Institute of Electrical and Electronics Engineers Inc., 2023. doi: 10.1109/ICCCNT56998.2023.10306945.
• [15] OpenAI et al., “GPT-4 Technical Report,” Mar. 2023, [Online]. Available: http://arxiv.org/abs/2303.08774
• [16] M. Wermelinger, “Using GitHub Copilot to Solve Simple Programming Problems,” in SIGCSE 2023 - Proceedings of the 54th ACM Technical Symposium on Computer Science Education, Association for Computing Machinery, Inc, Mar. 2023, pp. 172–178. doi: 10.1145/3545945.3569830.
• [17] M. Kytö, “Copilot for Microsoft 365: A Comprehensive End-user Training Plan for Organizations.”
• [18] B. Hui et al., “Qwen2.5-Coder Technical Report,” Sep. 2024, [Online]. Available: http://arxiv.org/abs/2409.12186
• [19] A. Grattafiori et al., “The Llama 3 Herd of Models,” Jul. 2024, [Online]. Available: http://arxiv.org/abs/2407.21783
• [20] Y. Sonoda et al., “Diagnostic performances of GPT-4o, Claude 3 Opus, and Gemini 1.5 Pro in ‘Diagnosis Please’ cases,” Jpn J Radiol, Nov. 2024, doi: 10.1007/s11604-024-01619-y.
• [21] “Kodlama için en iyi 5 büyük dil modeli,” Innova. Accessed: Aug. 13, 2024. [Online]. Available: https://www.innova.com.tr/blog/kodlama-icin-en-iyi-5-buyuk-dil-modeli
• [22] “Comparison of Models: Quality, Performance & Price Analysis,” Artificial Analysis. Accessed: Dec. 28, 2024. [Online]. Available: https://artificialanalysis.ai/models
• [23] A. Verma, “‘The Future Of Coding Is No Coding At All’ — Did GitHub CEO Predict Traditional Programming’s Death?,” Fossbytes, Oct. 13, 2017. Accessed: Nov. 20, 2024. [Online]. Available: https://fossbytes.com/coding-automation programming-github-ceo/
• [24] H. Liu, C. Zhang, S. Sun, H. Zhou, Y. Xie, and T. Jiang, “Universal No-code Web Design Tool for Substation Digital Monitoring System,” in IMCEC 2024 - IEEE 6th Advanced Information Management, Communicates, Electronic and Automation Control Conference, Institute of Electrical and Electronics Engineers Inc., 2024, pp. 1391–1394. doi: 10.1109/IMCEC59810.2024.10575868.
• [25] F. Sufi, “Algorithms in Low-Code-No-Code for Research Applications: A Practical Review,” Feb. 01, 2023, MDPI. doi: 10.3390/a16020108.
• [26] N. Fraser, Ten Things We’ve Learned from Blockly. IEEE, 2015
• [27] H. Marc and P. Mileff, “Introduction to Mendix,” Production Systems and Information Engineering, vol. 11, no. 3, p. 64, doi: 10.32968/psaie.2023.3.5.
• [28] Available: “User Interfaces - Software Development Life Cycle,” Mendix. Accessed: Aug. 21, 2024. [Online]. https://www.mendix.com/evaluation-guide/app-lifecycle/develop/ux-multi-channel-apps/user-interfaces/
• [29] M. Fadaee, “Building The Foundation for an AI-Integrated Career Coaching Application with FlutterFlow,” Bachelor’s Thesis, HAMK, 2024.
• [30] A. Jassy, “One of the most tedious but critical tasks activity.. – Amazon Q,” Linkedin. Accessed: Aug. 29, 2024. [Online]. Available: https://www.linkedin.com/posts/andy-jassy-8b1615_one-of-the most-tedious-but-critical-tasks-activity-7232374162185461760-AdSz/
• [31] W. Filipek, “Top No-Code AI Tools of 2024: In-Depth Guide,” Buildfire. Accessed: Aug. 28, 2024. [Online]. Available: https://buildfire.com/no-code-ai-tools/
• [32] “BuildFire App Builder Web Site.” Accessed: Aug. 28, 2024. [Online]. Available: https://buildfire.com/
• [33] M. Annamalai et al., Sharding the Shards: Managing Datastore Locality at Scale with Akkio. Usenix, 2018. [Online]. Available: https://www.usenix.org/conference/osdi18/presentation/annamalai
• [34] E. Huovila, “USE OF MACHINE LEARNING IN SUPPLY CHAIN MANAGEMENT-CASE STUDY WITH DATAROBOT.”
• [35] D. Agustian, P. P. G. P. Pertama, P. N. Crisnapati, and P. D. Novayanti, “Implementation of Machine Learning Using Google’s Teachable Machine Based on Android,” in 3rd International Conference on Cybernetics and Intelligent Systems, ICORIS 2021, Institute of Electrical and Electronics Engineers Inc., 2021. doi: 10.1109/ICORIS52787.2021.9649528.
• [36] “Lobe AI GitHub Page,” Lobe. Accessed: Aug. 28, 2024. [Online]. Available: https://www.lobe.ai/
• [37] T. Özdoğan, “SageMaker nedir?,” Linkedin. Accessed: Aug. 29, 2024. [Online]. Available: https://www.linkedin.com/pulse/sagemaker-nedir-tunahan-%C3%B6zdo%C4%9Fan/
• [38] D. Nigenda et al., “Amazon SageMaker Model Monitor: A System for Real-Time Insights into Deployed Machine Learning Models,” in Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Association for Computing Machinery, Aug. 2022, pp.3671–3681. doi: 10.1145/3534678.3539145.
• [39] “Levity AI Web Site.” Accessed: Aug. 29, 2024. [Online]. Available: https://levity.ai/
• [40] K. Sukhanova, “Create No-Code Models with Levity,” TechAcute, Oct. 25, 2022. Accessed: Dec. 29, 2024. [Online]. Available: https://techacute.com/no-code-models-levity/
• [41] “Causaly AI Web Site,” Causaly. Accessed: Aug. 28, 2024. [Online]. Available: https://www.causaly.com/
• [42] “AI Squared Web Site,” AI Squared. Accessed: Aug. 28, 2024. [Online]. Available: https://squared.ai/
• [43] “CallFluent AI Web Site,” CallFluent AI. Accessed: Aug. 28, 2024. [Online]. Available: https://callfluent.com/
• [44] B. Yalçıner et al., “Yazılım Kalite Maliyetlerinin Kontrol Altında Tutulması Yoluyla Proje Geliştirme Maliyetlerinin Düşürülmesi: Literatüre bir bakış.”
• [45] S. Martínez-Fernández et al., “Software Engineering for AI-Based Systems: A Survey,” ACM Transactions on Software Engineering and Methodology, vol. 31, no. 2, Apr. 2022, doi: 10.1145/3487043.
• [46] A. N. Duc, I. Sundbø, E. Nascimento, A. Nguyen-Duc, and T. Conte, “Software engineering for artificial intelligence and machine learning software: A systematic literature review”, doi: 10.48550/arXiv.2011.03751.
• [47] V. U. Rajput, “Research on Know Your Customer (KYC),” 2013. [Online]. Available: www.ijsrp.org
• [48] D. Kecerdasan Buatan, M. Hidayat, S. Yulia Defitri, H. Hilman STIE Persada Bunda, and U. Mahaputra Muhammad Yamin, “The Impact of Artificial Intelligence (AI) on Financial Management,” 2024. [Online]. Available: https://journal.ppipbr.com/index.php/productivity/index
• [49] N. Goksel and A. Bozkurt, “Artificial Intelligence in Education,” 2019, pp. 224–236. doi: 10.4018/978-1-5225-8431-5.ch014.