Enhance Software Performance Testing using Artificial Intelligence
With advances in data collection, processing, and computation, AI has become the latest buzzword in every industry. Performance testing is a type of testing in which the speed, responsiveness, and stability of a software, product, or network is evaluated under peak workload. Performance testing has evolved a lot over time. The focus has shifted from mere testing to performance engineering aspects in which the testing teams identify bottlenecks, perform error analysis, and provide performance tuning recommendations.
To keep up with the agile mode of development, the traditional testing process is no longer adequate, and teams need to bring in automation. Artificial Intelligence can play an important factor in test automation to reduce the time consumption and manual intervention involved in various test phases. Generative Artificial Intelligence, a subset of AI can aid in these activities. This paper discusses how performance testing and engineering can benefit from Artificial Intelligence and provides some use cases.
- Software Performance Testing
- Machine Learning concepts [high-level]
- Generative AI
- Usage of Machine Learning and Generative AI in Performance Testing process
Rini Susan V S
Rini Susan V S is a senior quality engineer focusing on Software Performance Testing and Engineering. She has an extensive working knowledge of Performance Testing, Application monitoring, DevOps, Cloud, and CI/CD tools. Rini regularly contributes to technical blogs and articles and has published articles on Developer.com and Software Testing Magazine. Currently, she is pursuing a technical program in Artificial Intelligence and Machine Learning.