Olivier Gaudin
The Clean as You Code Imperative
#1about 2 minutes
Understanding code as the foundational asset of software
Software is built on code, which acts like the roots of a tree, dictating its behavior, performance, and long-term health.
#2about 4 minutes
Exploring the four essential pillars of clean code
Clean code is defined by four key attributes: consistency for team collaboration, intentionality to avoid bugs, adaptability for future changes, and responsibility to prevent bad practices.
#3about 3 minutes
How clean code increases development velocity and ownership
Unclean code leads to rework and disposable code, while clean code increases team throughput, enables innovation, and fosters a sense of ownership.
#4about 3 minutes
Why knowing your code quality metrics is not enough
Simply measuring code quality metrics like code coverage often fails to drive improvement because it focuses on the entire existing codebase, which is an overwhelming problem to solve.
#5about 5 minutes
Adopting the "Clean as You Code" methodology
The "Clean as You Code" approach fixes the "water leak" by focusing on ensuring that all new and changed code meets a high-quality standard via a quality gate.
#6about 1 minute
How "Clean as You Code" organically improves legacy code
By focusing on new and modified code, this methodology naturally cleans up the legacy codebase over time as developers touch about 20% of the code annually.
#7about 2 minutes
Integrating code quality checks into the development lifecycle
The "Clean as You Code" practice is integrated throughout the development process, starting in the IDE and continuing through pull requests and CI/CD pipelines.
#8about 2 minutes
A summary of the clean code imperative
The presentation concludes that clean code creates a better work environment and that the "Clean as You Code" approach is the simplest way to achieve it without adding extra steps.
#9about 7 minutes
Q&A on Sonar, AI in code analysis, and pricing
The Q&A session addresses questions about architectural concepts like DDD, the use of AI in analysis, Sonar's pricing model, and strategies for shifting quality checks earlier in the development cycle.
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