Challenge: Improve detection and resolution of errors in code building to enable faster, more effective software delivery

Solutions: A first-of-its-kind, cutting-edge, code fixing agent that leverages generative AI models to identify and resolve errors automatically, ensuring smooth integration and deployment

Benefits:

• Improved software quality
• Greater speed of delivery
• Heightened communication among teams
• Reduced downtime and bottlenecks
• Increased reliability
• Scalability

ALTEN’s teams set out to develop a code fixing agent to address these issues, drawing on their extensive expertise in AI technologies and models. They came up with a pioneering approach that represents a first in the industry, leveraging generative AI models capable of identifying and resolving errors automatically to ensure smooth integration and deployment. The automatic code fixing agent reduces the need for human intervention and the frequency of errors. Aside from saving time, it ensures that everyone is working on the same – and the latest – version of the project.

As in any area, fixing software build failures involves first identifying the problem, then investigating its origin, making corrections, and testing to see that it is resolved. The faster the issue is detected and resolved, the less disruption it can cause. CI/CD automated code fixing minimizes build failures caused by human error or system misconfigurations. When failures do occur, it helps to catch them early, before they escalate, making it possible to deliver software faster and more reliably to users. In addition, it contributes to improved teamwork and communication among the various actors in the development process while reducing stress and downtime. Finally, it ensures reliable and consistent error resolution across pipelines. And because the architecture is cloud-based, it allows easy scaling to accommodate large and complex CI/CD environments.

This solution comprises a blend of advanced AI models and an automatic code fixing approaches, tailored to address complex CI/CD processes. The team employed Agentic workflows, which turn large language models (LLMs) into proactive problem-solving agents, rather than just reactive content generators; generative AI fine-tuning (CodeLlama, Mistral, DeepSeek, Falcon) provided for the adaptation of pre-trained large language models to specific domains or tasks.

The automated code fixing agent enables ALTEN’s client to offer the advantages of expert CI/CD pipelines to its clients, enabling them to deploy a fully functional application programming interface (API) in a few easy steps.