Affiliation:
1. Pune Vidyarthi Griha’s College of Engineering & Shrikrushna S. Dhamankar Institute of Management, Nashik
Abstract
This paper presents the analysis of software testing quality assurance using agile development environment and artificial intelligence with research travelogue. It explores the integration of Agile development methodologies with Artificial Intelligence (AI) to elevate the quality assurance (QA) processes in software testing. By leveraging Agile practices, such as iterative development and continuous feedback, alongside AI-driven tools for automation, predictive analytics, and anomaly detection, the approach aims to significantly enhance the accuracy and efficiency of QA processes. The research travelogue documents the journey through various Agile environments, detailing how AI technologies are applied to streamline testing workflows, identify potential issues earlier in the development cycle, and adapt to changing requirements. The findings reveal that this hybrid approach not only accelerates the testing process but also improves defect detection rates and overall software reliability, offering valuable insights for future advancements in software QA practices
Reference17 articles.
1. [1] Garousi, V., Felderer, M., Hacaloğlu, T., “Software test maturity assessment and test process improvement: A multivocal literature review”, Information and Software Technology, 85, 16-42, (2017).
2. [2] Mushtaq, Muhammad Salman, Muhammad Yousaf Mushtaq,and Muhammad Waseem. "Creating an Authentic LearningEnvironment Using e-Learning Application." EuropeanConference on e-Learning. Academic Conferences InternationalLimited, 2020.
3. [3] Corradini, Davide, et al. "Automated black‐box testing ofnominal and error scenarios in RESTful APIs." Software
4. Testing, Verification and Reliability 32.5 (2022): e1808.
5. [4] Chan, K., et al. "ReduNet: A white-box deep network from theprinciple of maximizing rate reduction." Journal of machinelearning research 23.114 (2022).