A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023)
The synergy between software engineering (SE) and artificial intelligence (AI) catalyzes software development, as numerous recent studies illustrate an intensified intersection between these domains. This systematic literature review examines the integration of AI techniques or methodologies across...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10740293/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846141904592306176 |
|---|---|
| author | Usman Khan Durrani Mustafa Akpinar Muhammed Fatih Adak Abdullah Talha Kabakus Muhammed Maruf Ozturk Mohammed Saleh |
| author_facet | Usman Khan Durrani Mustafa Akpinar Muhammed Fatih Adak Abdullah Talha Kabakus Muhammed Maruf Ozturk Mohammed Saleh |
| author_sort | Usman Khan Durrani |
| collection | DOAJ |
| description | The synergy between software engineering (SE) and artificial intelligence (AI) catalyzes software development, as numerous recent studies illustrate an intensified intersection between these domains. This systematic literature review examines the integration of AI techniques or methodologies across SE phases and related activities spanning from 2013 to 2023, resulting in the selection of 110 research papers. Investigating the profound influence of AI techniques, including machine learning, deep learning, natural language processing, optimization algorithms, and expert systems, across various SE phases—such as planning, requirement engineering, design, development, testing, deployment, and maintenance—is the focal point of this study. Notably, the extensive adoption of machine learning and deep learning algorithms in the development and testing phases has enhanced software quality through defect prediction, code recommendation, and vulnerability detection initiatives. Furthermore, natural language processing’s role in automating requirements classification and sentiment analysis has streamlined SE practices. Optimization algorithms have also demonstrated efficacy in refining SE activities such as feature location and software repair action predictions, augmenting precision and efficiency in maintenance endeavors. Prospective research emphasizes the imperative of interpretable AI models and the exploration of novel AI paradigms, including explainable AI and reinforcement learning, to promote ethical and efficient software development practices. This paper fills the gap identified in AI techniques dedicated to improving SE phases. The review concludes that AI in SE is revolutionizing the discipline, enhancing software quality, efficiency, and innovation, with ongoing efforts targeting the mitigation of identified limitations and the augmentation of AI capabilities for intelligent and dependable SE. |
| format | Article |
| id | doaj-art-81a834cae0c0445abaa8daafcb7dacf2 |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-81a834cae0c0445abaa8daafcb7dacf22024-12-04T00:02:14ZengIEEEIEEE Access2169-35362024-01-011217118517120410.1109/ACCESS.2024.348890410740293A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023)Usman Khan Durrani0https://orcid.org/0000-0003-4255-6253Mustafa Akpinar1https://orcid.org/0000-0003-4926-3779Muhammed Fatih Adak2https://orcid.org/0000-0003-4279-0648Abdullah Talha Kabakus3https://orcid.org/0000-0003-2181-4292Muhammed Maruf Ozturk4https://orcid.org/0000-0001-6446-9754Mohammed Saleh5https://orcid.org/0000-0002-8142-6323Department of Computer and Information Sciences, Higher Colleges of Technology, Dubai, United Arab EmiratesDepartment of Computer and Information Sciences, Higher Colleges of Technology, Dubai, United Arab EmiratesDepartment of Computer Engineering, Sakarya University, Sakarya, TürkiyeDepartment of Computer Engineering, Duzce University, Düzce, TürkiyeDepartment of Computer Engineering, Suleyman Demirel University, Isparta, TürkiyeDepartment of Computer and Information Sciences, Higher Colleges of Technology, Dubai, United Arab EmiratesThe synergy between software engineering (SE) and artificial intelligence (AI) catalyzes software development, as numerous recent studies illustrate an intensified intersection between these domains. This systematic literature review examines the integration of AI techniques or methodologies across SE phases and related activities spanning from 2013 to 2023, resulting in the selection of 110 research papers. Investigating the profound influence of AI techniques, including machine learning, deep learning, natural language processing, optimization algorithms, and expert systems, across various SE phases—such as planning, requirement engineering, design, development, testing, deployment, and maintenance—is the focal point of this study. Notably, the extensive adoption of machine learning and deep learning algorithms in the development and testing phases has enhanced software quality through defect prediction, code recommendation, and vulnerability detection initiatives. Furthermore, natural language processing’s role in automating requirements classification and sentiment analysis has streamlined SE practices. Optimization algorithms have also demonstrated efficacy in refining SE activities such as feature location and software repair action predictions, augmenting precision and efficiency in maintenance endeavors. Prospective research emphasizes the imperative of interpretable AI models and the exploration of novel AI paradigms, including explainable AI and reinforcement learning, to promote ethical and efficient software development practices. This paper fills the gap identified in AI techniques dedicated to improving SE phases. The review concludes that AI in SE is revolutionizing the discipline, enhancing software quality, efficiency, and innovation, with ongoing efforts targeting the mitigation of identified limitations and the augmentation of AI capabilities for intelligent and dependable SE.https://ieeexplore.ieee.org/document/10740293/AIartificial intelligencedeep learningexpert systemsintegrationmachine learning |
| spellingShingle | Usman Khan Durrani Mustafa Akpinar Muhammed Fatih Adak Abdullah Talha Kabakus Muhammed Maruf Ozturk Mohammed Saleh A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) IEEE Access AI artificial intelligence deep learning expert systems integration machine learning |
| title | A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) |
| title_full | A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) |
| title_fullStr | A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) |
| title_full_unstemmed | A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) |
| title_short | A Decade of Progress: A Systematic Literature Review on the Integration of AI in Software Engineering Phases and Activities (2013-2023) |
| title_sort | decade of progress a systematic literature review on the integration of ai in software engineering phases and activities 2013 2023 |
| topic | AI artificial intelligence deep learning expert systems integration machine learning |
| url | https://ieeexplore.ieee.org/document/10740293/ |
| work_keys_str_mv | AT usmankhandurrani adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT mustafaakpinar adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT muhammedfatihadak adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT abdullahtalhakabakus adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT muhammedmarufozturk adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT mohammedsaleh adecadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT usmankhandurrani decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT mustafaakpinar decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT muhammedfatihadak decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT abdullahtalhakabakus decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT muhammedmarufozturk decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 AT mohammedsaleh decadeofprogressasystematicliteraturereviewontheintegrationofaiinsoftwareengineeringphasesandactivities20132023 |