We'd all like to write "better" code. But how do you know what "better" means? And how do you know how well your current code scores on whatever scale you choose?
In this talk, we'll look at some possible measures for the quality of your code and come up with some ways to incorporate this measurement into your development process seamlessly.
Taking action to improve those numbers is left as an exercise for the audience.
This summary has been generated using AI
Outline of Dave Cross’s Talk
Title: Measuring the Quality of Perl Code
Speaker: Dave Cross
Introduction
- Greetings and appreciation for attendance.
- Brief introduction to his current role and the purpose of the
talk.
Section 1: Why Measure Code
Quality?
- Importance of measurement for management and improvement.
- Quotation from Peter Drucker: “You can’t manage what you can’t
measure.”
- Explanation of setting baselines and measuring improvements.
Section 2: What to Measure?
- Challenge of finding direct measures for code quality.
- Introduction to using proxy measures.
- Detailed discussion on proxies:
- Test passes
- Test coverage
- Perl critic scores
- Cyclomatic complexity
Section 3: How to Measure?
- Importance of regular, automated measurements.
- Overview of continuous integration tools:
- Jenkins
- Travis CI
- Circle CI
- Setup and integration of Travis CI with GitHub.
Section 4: Summary and
Displaying Success
- Ways to showcase improvements:
- Using badges from Travis CI and Coveralls.
- Presentation of test results and code quality metrics.
- Example of setting up and integrating various tools to automate the
measurement process.
Conclusion
- Recap of the importance and methodology of measuring Perl code
quality.
- Invitation to use his dashboard for tracking code quality
metrics.
Question & Answer Session
- Discussion on the feasibility of historical data analysis.
- Clarifications on the use of Perl Critic configurations.
My Thoughts
Dave Cross provides a comprehensive guide to measuring and improving
the quality of Perl code. His approach involves a blend of
theory—emphasizing the need for measurable metrics in management—and
practical guidance on using tools like Travis CI, Coveralls, and Perl
Critic. The talk is structured to walk through the rationale,
methodology, and tools necessary to implement a continuous quality
improvement process, making it highly valuable for Perl developers
looking to enhance their codebase systematically. The inclusion of
real-world tools and examples of their setup makes the talk particularly
actionable. Overall, it’s a well-rounded discussion that balances
conceptual knowledge with actionable steps.