AI-Augmented Software Engineering
What is AI-augmented software engineering?
AI-augmented software engineering integrates AI technologies as tools for the software development process to eliminate repetitive work and improve quality of human-only output. For instance, AI developers leverage AI tools to:
- Generate code
- Fix bugs
- Create documentation
How is it different from traditional software engineering?
Traditional software engineering depends on manual coding and the expertise of developers and testers for reliable and efficient results.
AI-augmented software engineering, however, uses AI tools to boost productivity, quality, and efficiency throughout the development lifecycle—from planning to deployment. For example, while traditional code reviews are done solely by humans, AI-powered tools can now assist by analyzing code against vast online repositories and offering improvement suggestions.
How AI is used in AI-augmented software engineering
Creating code
AI-powered tools like ChatGPT are widely used in software engineering to generate code based on user requirements, supporting any programming language. By leveraging databases, code repositories, and other resources, these tools can produce efficient and reliable code, sometimes even creating entire applications. However, they may struggle with issues such as recognizing deprecated code.
Bug fixing and improving code
Traditional software engineering requires developers to manually debug code, research solutions, and consult experts to find and fix bugs.
AI-augmented software engineering lets developers submit code to AI tools, which automatically analyze execution traces and errors, identify root causes, and suggest improvements.
Understanding code and generating documentation
Developers often struggle to understand complex or unfamiliar code. AI tools can simplify this by explaining code and automatically generating documentation, freeing developers to focus on more important tasks. By automating repetitive and labor-intensive documentation—like user manuals and help articles—AI-augmented software engineering boosts productivity.
Language translation
Engineering teams sometimes need to migrate their codebase to a different programming language. In these cases, they can leverage AI tools to efficiently convert syntax and code structures into the desired language.
Testing
Today automation testing is evolving into autonomous testing, where AI tools handle quality engineering tasks from test case generation to execution. This reduces human intervention and errors. Developers also use AI to generate unit tests, with AI models improving over time by learning from failed cases.
Other task automations
AI-augmented software engineering can automate routine tasks beyond coding and testing, such as generating email responses, prioritizing messages, and scheduling meetings—freeing developers to focus on more critical work.
Even Project management
AI-augmented software engineering uses AI tools to streamline project management by analyzing risks and resources, enabling smarter task assignments and timeline planning for all stakeholders.