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AI-Based Software Testing

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Proceedings of World Conference on Information Systems for Business Management (ISBM 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 833))

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Abstract

As the complexity of software applications continues to increase, software testing becomes more challenging and time-consuming. The use of artificial intelligence (AI) in software testing has emerged as a promising approach to address these challenges. AI-based software testing techniques leverage machine learning, natural language processing, and other AI technologies to automate the testing process, improve test coverage, and enhance the accuracy of test results. This paper provides an overview of AI-based software testing, including its benefits and limitations, and discusses various techniques and tools used in this field.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Independent University, Dhaka, Bangladesh

    Saquib Ali Khan, Nabilah Tabassum Oshin, Mahmuda Nizam, Ishtiaque Ahmed, Md Masum Musfique & Mahady Hasan

Authors
  1. Saquib Ali Khan
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  2. Nabilah Tabassum Oshin
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  3. Mahmuda Nizam
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  4. Ishtiaque Ahmed
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  5. Md Masum Musfique
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  6. Mahady Hasan
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Corresponding author

Correspondence to Saquib Ali Khan .

Editor information

Editors and Affiliations

  1. University of Cantabria, Santander, Spain

    Andres Iglesias

  2. University of Aizu, Fukushima, Japan

    Jungpil Shin

  3. Knowledge Chamber of Commerce and Industry, Ahmedabad, Gujarat, India

    Bharat Patel

  4. Global Knowledge Research Foundation, Ahmedabad, Gujarat, India

    Amit Joshi

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© 2024 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Khan, S.A., Oshin, N.T., Nizam, M., Ahmed, I., Musfique, M.M., Hasan, M. (2024). AI-Based Software Testing. In: Iglesias, A., Shin, J., Patel, B., Joshi, A. (eds) Proceedings of World Conference on Information Systems for Business Management. ISBM 2023. Lecture Notes in Networks and Systems, vol 833. Springer, Singapore. https://doi.org/10.1007/978-981-99-8346-9_28

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