Enhancing Software Development Efficiency: CI/CD Pipelines with Real-Time Defect Detection

EasyChair Preprint 13182

Abstract

Continuous Integration/Continuous Delivery (CI/CD) pipelines have revolutionized the software development process by automating build, test, and deployment stages, ensuring rapid and reliable delivery of code changes. However, despite the benefits, defects can still slip through the cracks, leading to costly fixes and delays. Real-time defect detection aims to address this challenge by integrating automated testing and analysis directly into the CI/CD pipeline.

This abstract explores the integration of real-time defect detection techniques into CI/CD pipelines to enhance software development efficiency. We examine various approaches, including static code analysis, dynamic testing, and machine learning-based anomaly detection, that enable early identification of defects as code changes progress through the pipeline. By detecting issues at the earliest possible stage, developers can address them promptly, reducing the likelihood of defects propagating to production.

Furthermore, we discuss the benefits of incorporating real-time defect detection into CI/CD pipelines, such as improved code quality, faster time-to-market, and reduced operational risks. We also highlight challenges, such as false positives, scalability issues, and the need for continuous refinement of detection algorithms.

Keyphrases: Continous Delivery, Continous Integration, Technology

@booklet{EasyChair:13182,
  author    = {Louis Frank and Saleh Mohamed},
  title     = {Enhancing Software Development Efficiency: CI/CD Pipelines with Real-Time Defect Detection},
  howpublished = {EasyChair Preprint 13182},
  year      = {EasyChair, 2024}}