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Software Testing Using Ai

  • Unique Paper ID: 178236
  • Volume: 11
  • Issue: 12
  • PageNo: 3186-3194
  • Abstract:
  • Summary software testing is a critical stage in the software development lifecycle and ensures the reliability and quality of your software system. With modern software becoming more and more complex, we can see that traditional manual testing rates are inefficient and not scalable. In recent years, artificial intelligence (AI) has been proven to be powerful in automation and improve many aspects of software testing. This systematic review aims to analyze current trends and cutting edge trends in AI control software te sting. This study examines a variety of approaches, techniques an d tools to assess their effectiveness in a variety of test contexts. Initially, 90 articles were retrieved from the main research database using precisely defined search queries. The multiphase filter process selected 20 high quality articles for incoming analyses and abo ut 50 related studies were checked to gain a comprehensive under standing of the domain. The results show that AI is effectively use d to automate several test tasks, including test cases, defect prediction, test case prioritization, transformation test, android application testing, test case validation, test case validation, white customer testing, among others, particularly through machine learning ( ML) and deep learning (DL). This review concludes that AI integration in software testing not only optimizes the testing process, but also improves accuracy, efficiency and coverage. This work provides a general overview of how AI technology can change traditional software testing practices.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 12
  • PageNo: 3186-3194

Software Testing Using Ai

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Impact Factor
8.01 (Year 2024)
UGC Approved
Journal no 47859

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