AI-ASSISTED & QUALITY-ASSURED CODE
Clean Code in the Age of Generative AI
Creating maintainable, reliable, and secure software requires high-quality code, regardless of the origin, whether human-written or machine-generated.
AI coding assistants like GitHub Copilot, OpenAI ChatGPT, and Amazon CodeWhisperer are becoming increasingly essential in software development. AI coding assistants offer significant benefits by automating code generation, accelerating development timelines, and boosting developer productivity.
To maximize the advantages of generative AI in coding, developer teams need robust DevOps processes, reporting, and metrics that focus on code quality, security, and reliability. Generative AI produces human-like output based on its training data. Since generative AI is trained using human code, its output includes all the same issues as human-created code. With AI-generated code, a higher volume of code will be produced at a faster speed, and it is important to be aware of the following considerations.
Code contains errors, bugs, or inefficiencies because GenAI does not test or validate its results.
Code contains flaws that, when exploited, result in malicious software attacks.
Code that is difficult to read, understand, and change prevents ease of enhancement.
AI prioritizes syntax correctness over efficiency leading to complexity that is costly to repair.
Sonar’s solutions consisting of SonarQube and SonarCloud integrated into the Continuous Integration (CI) pipeline alongside SonarLint in the IDE, unlock the full potential of AI-generated code that is consistent, intentional, adaptable, and responsible. Using Sonar, development teams can minimize risk, ensure code quality, and derive more value from code created by both AI and humans in a predictable and sustainable way. Sonar’s solutions offer the best path toward adopting AI code generation.
By integrating Sonar's 'Clean as You Code' methodology into your development pipeline, you maintain a gold standard of Clean Code across both AI-generated and human-written code.
Accelerate development cycles by resolving AI coding issues in the DevOps pipeline, delivering faster time-to-market.
Ensure AI-generated code meets high standards before building and testing, reducing time to debug and rework.
Build confidence in your generative AI codebase by performing code reviews using Sonar to eliminate issues.
With tools that streamline the verification of AI code and provide guided learning, Sonar leads to greater job satisfaction.
Tango provides a powerful solution to thousands of clients, growing alongside a network of service centers. However, with growth and acquisition comes the challenge of integrating new technologies into their ecosystem without hindering the quality and performance of their software.
Sonar helps our development team confidently make both AI-assisted and human-developed code fit for production by reviewing and establishing rules of good programming practices to achieve better code and avoid typical errors. It also assists us in gauging the code coverage for each project, allowing us to identify areas that still require testing.
Dario Flores, Technical Quality Specialist @ Axoft
In this webinar, join Manish Kapur, Sr. Director, Product & Solutions for Sonar, to discover how using AI code generation responsibly can help you innovate faster.
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