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Conference Paper
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Year 2024, Volume: 28, 326 - 341, 01.08.2024

Huseyin Karacali Efecan Cebel , Nevzat Donum

https://doi.org/10.55549/epstem.1521963

Abstract

References

  • Karacali, H., Cebel, E., & Donum, N. (2024). Performance comparison of AI platforms in solving computer science problems. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 28, 326-341.

Performance Comparison of AI Platforms in Solving Computer Science Problems

Year 2024, Volume: 28, 326 - 341, 01.08.2024

Huseyin Karacali Efecan Cebel , Nevzat Donum

https://doi.org/10.55549/epstem.1521963

Abstract

In the rapidly evolving landscape of artificial intelligence (AI), its significance and accelerated development are undeniable. AI has emerged as a cornerstone technology with profound implications across various domains, driving innovation and reshaping the way we approach complex problems. Particularly, the utilization of AI in coding tasks has garnered substantial attention, given its potential to streamline development processes and enhance the efficiency of software engineering practices. Against this backdrop, this paper presents a detailed comparative analysis of four different AI platforms, namely ChatGPT, Gemini, Blackbox, and Microsoft Copilot, in addressing key challenges within the realm of computer science, spanning natural language processing, image processing, and cybersecurity. The study focuses on leveraging the C++ programming language to develop solutions for these multifaceted problems across the aforementioned platforms. Each platform's outputs are meticulously evaluated on various parameters including accuracy, execution time, code size, and time complexity to provide a comprehensive understanding of their performance. Furthermore, an iterative optimization methodology is employed, entailing three rounds of refinement for the code produced by each platform, with the resultant outputs subjected to comparative analysis in each iteration. Through this rigorous approach, the paper not only elucidates the efficacy of different AI platforms in addressing diverse computational challenges but also underscores the iterative enhancement process on AI platforms for refining code quality and performance across multiple domains within computer science.

Keywords

AI-driven development AI-driven chatbot AI Platforms Computer science

References

  • Karacali, H., Cebel, E., & Donum, N. (2024). Performance comparison of AI platforms in solving computer science problems. The Eurasia Proceedings of Science, Technology, Engineering & Mathematics (EPSTEM), 28, 326-341.
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Details

Primary Language English
Subjects Software Engineering (Other)
Journal Section Articles
Authors

Huseyin Karacali

Efecan Cebel

Nevzat Donum

Early Pub Date July 24, 2024
Publication Date August 1, 2024
Submission Date February 5, 2024
Acceptance Date April 9, 2024
Published in Issue Year 2024 Volume: 28

Cite

APA Karacali, H., Cebel, E., & Donum, N. (2024). Performance Comparison of AI Platforms in Solving Computer Science Problems. The Eurasia Proceedings of Science Technology Engineering and Mathematics, 28, 326-341. https://doi.org/10.55549/epstem.1521963
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