Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
AI in software engineering |
| Συγγραφείς: |
Pleșu, D., Nedelea, D., Dulgheru, I. |
| Πηγή: |
Conferinţa tehnico-ştiinţifică a studenţilor, masteranzilor şi doctoranzilor (Vol.1) |
| Έτος έκδοσης: |
2025 |
| Θεματικοί όροι: |
adaptive learning, automation tools, debugging techniques, machine learning, test optimization, quality assurance |
| Περιγραφή: |
Artificial Intelligence AI is transforming software testing, development, and education by enhancing automation, optimizing debugging, and enabling adaptive learning. In software testing, AI-driven tools improve test case selection and streamline debugging by identifying patterns in code and suggesting precise fixes. Machine learning models enhance vulnerability detection, improving security in enterprise environments. In development, AIpowered assistants such as GitHub Copilot automate coding tasks, accelerating software production and reducing errors. AI-driven refactoring tools optimize legacy code, increasing maintainability and scalability. Additionally, AI is revolutionizing software engineering education through personalized learning environments, real-time feedback, and automated tutoring systems, making programming more accessible and efficient. By integrating AI into these domains, the software industry achieves higher accuracy, reduced costs, and improved learning outcomes. This paper explores the impact of AI on software engineering, highlighting its role in reshaping testing methodologies, development practices, and educational approaches. |
| Τύπος εγγράφου: |
article in journal/newspaper |
| Περιγραφή αρχείου: |
application/pdf |
| Γλώσσα: |
English |
| Relation: |
https://ibn.idsi.md/vizualizare_articol/248292 |
| Διαθεσιμότητα: |
https://ibn.idsi.md/vizualizare_articol/248292 |
| Rights: |
info:eu-repo/semantics/openAccess |
| Αριθμός Καταχώρησης: |
edsbas.AEA92250 |
| Βάση Δεδομένων: |
BASE |