I have used Uplevel to enhance code quality, which in turn reduced defects for a telecom client. Uplevel analyzed the client codebase and identified the technical debt, code smells, and areas with high complexity. It helped reduce defects through defect prediction and improved code quality. Uplevel's machine learning algorithm analyzes historical data and predicts that specific modules in a client application have a high likelihood of defects due to complexity and recent changes. Due to this capability, the development team focuses on high-risk modules, conducting thorough code reviews and testing to mitigate potential defects. With this approach, the team identified and addressed more than five critical defects, which likely reduced production issues and improved overall application reliability.
Find out in this report how the two Engineering Process solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
I have used Uplevel to enhance code quality, which in turn reduced defects for a telecom client. Uplevel analyzed the client codebase and identified the technical debt, code smells, and areas with high complexity. It helped reduce defects through defect prediction and improved code quality. Uplevel's machine learning algorithm analyzes historical data and predicts that specific modules in a client application have a high likelihood of defects due to complexity and recent changes. Due to this capability, the development team focuses on high-risk modules, conducting thorough code reviews and testing to mitigate potential defects. With this approach, the team identified and addressed more than five critical defects, which likely reduced production issues and improved overall application reliability.