Continuous Integration

Continuous Integration (CI) automates the integration of code changes, aiming to improve software development speed and reliability. Current research heavily emphasizes using machine learning, particularly deep reinforcement learning and various classification models, to optimize CI processes, such as predicting build failures, prioritizing test cases, and intelligently skipping unnecessary CI runs. This focus on automated decision-making within CI pipelines is driven by the need to address challenges like increasing build times and resource consumption, especially in large and complex projects, including those involving machine learning itself. The resulting improvements in efficiency and reduced error rates have significant implications for software development productivity and product quality.