Generative AI in Software Engineering: Revolutionizing Test Case Generation and Validation Techniques

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@article{1705175,
      author = {Dheerender Thakur, Aditya Mehra, Rohit Choudhary, Mithun Sarker},
      title = {Generative AI in Software Engineering: Revolutionizing Test Case Generation and Validation Techniques},
      journal = {Iconic Research And Engineering Journals},
      year = {2023},
      volume = {7},
      number = {5},
      pages = {281-293},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/17051751.pdf},
      abstract = {The ever-changing dynamics of software systems and the rising pressure in the software industry to deliver product updates more frequently have posed severe testing challenges. Artificial Intelligence (AI) is now considered a disruptive technology that can provide solutions in quality assurance about test case generation, validation, and overall quality management. In this article, we discuss how Artificial Intelligence enables the creation of efficient software tests, predicting possible defects before they appear and increasing the product's reliability. In this article, which discusses case studies within diverse fields, including banking, e-commerce, automobile, healthcare, and telecommunications, AI's functional roles and values are explained concerning their actual utilization. It also identifies fundamental concerns in implementing artificial intelligence solutions, such as data quality, interpretability, and ethical issues. It gives an insight into how these hurdles could be overcome. As AI grows, the technology will shape the software testing field to help organizations develop even higher-quality software within less time.},
      keywords = {Artificial Intelligence (AI), Software Testing, Quality Assurance, Test Case Generation, Test Case Validation, Predictive Analytics, Automation, Machine Learning},
      month = {November},
  }