TY - GEN
T1 - Enhancing Software Engineering with AI
T2 - 2024 International Conference on Decision Aid Sciences and Applications (DASA)
AU - Al-Ahmad, Ahmad
AU - Kahtan, Hasan
AU - Tahat, Luay
AU - Tahat, Tarek
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2025/1/17
Y1 - 2025/1/17
N2 - Artificial intelligence (AI) is currently a prominent topic in the field of software engineering. AI has greatly transformed software engineering by providing advanced tools that may boost the effectiveness and efficiency of various stages of the system development life cycle. In this paper, we examine the role of AI by focusing primarily on ChatGPT, an OpenAI language model. The research explores how ChatGPT can assist in software engineering tasks such as code generation, bug fixing, and documentation development. Through an analysis of real-world scenarios, the case study highlights the benefits and challenges of using AI tools in these three areas. The findings show that although AI can accelerate the output and simplify processes, its application must be carefully considered because it has issues in terms of lack of context awareness regarding performance considerations, project-specific requirements, its inability to access real-time logs or inspect environments, and its tendency to produce documentation that doesn't capture the necessary details for complex systems.
AB - Artificial intelligence (AI) is currently a prominent topic in the field of software engineering. AI has greatly transformed software engineering by providing advanced tools that may boost the effectiveness and efficiency of various stages of the system development life cycle. In this paper, we examine the role of AI by focusing primarily on ChatGPT, an OpenAI language model. The research explores how ChatGPT can assist in software engineering tasks such as code generation, bug fixing, and documentation development. Through an analysis of real-world scenarios, the case study highlights the benefits and challenges of using AI tools in these three areas. The findings show that although AI can accelerate the output and simplify processes, its application must be carefully considered because it has issues in terms of lack of context awareness regarding performance considerations, project-specific requirements, its inability to access real-time logs or inspect environments, and its tendency to produce documentation that doesn't capture the necessary details for complex systems.
KW - Artificial Intelligence
KW - ChatGPT
KW - Code Generation
KW - Documentation Generation
KW - Software Engineering
UR - http://www.scopus.com/inward/record.url?scp=85217238178&partnerID=8YFLogxK
U2 - 10.1109/dasa63652.2024.10836262
DO - 10.1109/dasa63652.2024.10836262
M3 - Conference contribution
SN - 979-8-3503-6911-3
T3 - 2024 International Conference on Decision Aid Sciences and Applications (DASA)
SP - 1
EP - 5
BT - 2024 International Conference on Decision Aid Sciences and Applications (DASA)
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2024 through 12 December 2024
ER -