top of page

Metrics Every Software Engineer Should Track

Updated: Jul 26

Metrics Every Software Engineer Should Track Introduction: As a software engineer, tracking metrics is crucial for measuring the success and efficiency of your work. By monitoring these key indicators, you can identify areas for improvement, make data-driven decisions, and ultimately deliver higher-quality software. Remember, metrics may not provide all the answers, but will point you in the right direction to look for opportunities to improve. 1. Code Coverage: Code coverage measures the percentage of your codebase that is covered by manual or automated tests. Most Code Coverage is done with automated Unit Tests. Code Coverage metrics helps ensure that your tests are comprehensive and that potential bugs are caught early. Aim for a "reasonable" code coverage percentage to increase the reliability and maintainability of your code. There are many opinions on the value of code coverage and unit testing, however, if each engineer understands that for certain types of defects, unit tests will be the only mechanism that can discover them. We discuss in detail in our "Test Engineering as a Discipline" training what these types of issues are, and why it is important to understand that using different types of testing help discover the broad spectrum of issues that may exist in your code. 2. Defect Trending over Time (DTT): Tracking the trending of the number of bugs in your software is essential for identifying patterns and improving overall quality. By monitoring bug trends and counts over time, you can assess your ability to create quality code, and the ability to resolve the appropriate volume and priority of defects, and prioritize areas that require attention. 3. Test Case Coverage and Effectiveness:

Understanding what functionality needs to be covered in your product, and how to measure that coverage is imperative to any software development effort large or small. Teams need to assure quality before software goes into production, not just monitor it after the fact and fix issues quickly. If you have adequate coverage and release a defect into production, you then have a feed back loop to evaluate the miss. Test case effectiveness measures the percentage of test cases that detect defects in your software. It helps evaluate the quality and thoroughness of your testing efforts. Regularly review and update your test cases to ensure they cover critical functionality and edge cases effectively.


4. Performance and Load: Response time measures how quickly your software responds to user requests. It directly impacts user experience and satisfaction. By monitoring response time, you can identify performance bottlenecks and optimize your code to deliver a faster and more responsive application. Load measurements help you understand where your software "breaks down", before users see the slowness in their environments. 5. Customer Satisfaction (NPS): Customer satisfaction is a vital metric that reflects how well your software meets user expectations. Regularly gather feedback from users through surveys or ratings to gauge their satisfaction levels. This metric can guide you in making improvements that align with user needs and preferences. The Net promoter Score is commonly accepted way to get data on your performance. Customer feedback will be the most critical assessment of your team and whether you are building the right capabilities in your product and producing the right level of quality and performance. 6. Incident Volume and Outage Time: Measuring the volume of customer incidents and associated outage time is key to understanding whether your software can stand up to the rigors of the usage models and environments they are operating in. This measurement is a large component of how customers view the quality of your application. Ultimately, if they cannot use the application when they need to due to downtime or issues, the continual adding of capabilities and features does not improve their opinion of your software or company.

7. Mean Time to Resolve (MTTR): MTTR measures the average time it takes to resolve a problem or bug once it has been detected. By reducing MTTR, you can minimize downtime and improve user satisfaction. Implement efficient debugging and troubleshooting processes to resolve issues promptly. 8. Technical Debt: Technical debt refers to the accumulated cost of shortcuts or suboptimal solutions in your codebase. Tracking technical debt helps you prioritize refactoring efforts and maintain a clean and maintainable codebase. Regularly assess and address technical debt to prevent it from becoming a burden in the long run. 9. Team Velocity: Team velocity measures the amount of work your development team can complete within a given time frame. It helps with capacity planning and setting realistic project timelines. By tracking team velocity, you can identify bottlenecks, optimize workflows, and improve overall productivity. It is equally important to understand that frequent releases do not equal customer satisfaction. We talk about why this occurs in the training on Process Models and Agile Optimization. Conclusion: Tracking these metrics can provide valuable insights into the performance and quality of your software engineering efforts. By regularly monitoring and analyzing these indicators, you can make informed decisions, drive continuous improvement, and deliver exceptional software that meets user expectations. Remember, metrics are not just numbers; they represent opportunities for growth and success in your software engineering journey.


Comments


bottom of page