Software Quality Metrics

Introduction

One of the biggest challenges that developers face is ensuring that the software they develop meets the needs of their users and performs as expected. 

Measuring software quality is a crucial step towards addressing these challenges and delivering high-quality software applications. 

Let’s explore which aspects have an impact on software quality and investigate which metrics you need to track to really improve your product and process.

Why are software quality metrics important?

Software quality metrics help developers and stakeholders to make sure that the software they are producing is of high quality and meets the needs of its users. By measuring software quality using metrics such as defect density, code coverage, and maintainability, developers identify areas of the code that need improvement and prioritize their efforts accordingly.

Software quality metrics also help teams to track progress over time and evaluate the effectiveness of their development processes. By setting goals and monitoring progress with metrics such as cycle time and code review coverage, developers can identify areas where they can improve their efficiency and make adjustments to their processes as needed.

Software quality metrics can be used to communicate with stakeholders and customers about the quality of the software. By presenting data on metrics such as defect density and escaped defects, developers can demonstrate the effectiveness of their testing and quality assurance processes and build trust with their users.

Risks connected to focusing on software quality metrics

There is a risk of overemphasizing metrics at the expense of other important factors, such as user experience or business outcomes. While metrics can provide valuable insights into the software performance, they should be used in conjunction with other sources of information. That way you can make sure that development efforts are aligned with business goals and user needs.

Teams can also start tracking too many metrics and become overwhelmed by the amount of data. And, after all, the goal of measuring isn’t to track a ton of metrics, but to track the ones that correspond with your goals and make changes based on data they deliver. In terms of software quality metrics, we’re talking about actually improving the quality of our product. To mitigate the risk of tracking too many metrics, focus on a few ones that are directly tied to business outcomes and user needs, and to regularly reassess the metrics to ensure that they remain relevant and useful.

There’s also a risk of misinterpreting metrics or drawing incorrect conclusions from the data. To prevent that, make sure that the metrics are being tracked correctly and that the data is being analyzed and interpreted correctly. This may require specialized expertise or additional training to ensure that the metrics are being used correctly.

Risks connected to measuring software quality can be mitigated by using the right set of metrics, cross-referencing them with other sources of information, focusing on a few key chosen ones that are directly tied to business outcomes and user needs, and ensuring that the metrics are being tracked and analyzed correctly. 

Software Quality metrics - groups

There are many different metrics that can be used to measure software quality, and the ones you choose will depend on your specific goals and objectives.

Let’s take a look at a few groups of indicators that help to keep track of the product’s quality.

Code quality metrics

Code quality metrics such as code complexity, code coverage, and code smells can give us insights into the maintainability and reliability of the code. Code complexity indicators such as cyclomatic complexity and nesting depth can help you identify areas of the code that are difficult to maintain. On the other hand, code coverage metrics like statement coverage and branch coverage allow your team to determine how much of the codebase is covered by automated tests. Code smells such as duplicated code, long methods, and complex conditionals indicate areas of the code that need improvement.

Performance metrics

Performance metrics such as response time, throughput, and scalability can help us understand how well the software performs under various conditions. Load testing and stress testing can be used to simulate high volumes of traffic and identify bottlenecks and areas where the software needs optimization.

Security metrics

Security metrics such as vulnerability density and penetration testing can help you identify potential security risks and vulnerabilities. Regular security testing and code analysis helps to identify and address potential security issues before they become major problems. Security metrics include indicators such as the number of vulnerabilities, the severity of vulnerabilities, and the time taken to patch vulnerabilities.

Process metrics

Process metrics such as defect density, cycle time, and code review coverage help you to understand how efficiently and effectively your development team is working. These metrics allow you to identify areas for improvement and optimize the development process to ensure that you’re delivering high-quality software as quickly and efficiently as possible.

Usability metrics

Usability metrics are used to measure how easy it is to use a software application. They look at things like how long it takes to finish tasks, how many mistakes are made while doing tasks, and how happy users are with the software. These indicators are important because they show which parts of the software need to be changed to make it easier to use.

Selecting the right metrics to measure software quality is a critical part of the software development process. By choosing metrics that align with your goals and objectives, you can gain a comprehensive understanding of how well the software is performing and where improvements can be made.

Specific software quality metrics

Now let's take a closer look at a narrower set of specific metrics. It may be useful if you are just starting your journey with measuring software quality.

Halstead Metrics

Halstead metrics were developed by Maurice Halstead in 1977. These metrics are used to calculate the complexity of a program based on the number of operators and operands used in it. The metrics include program length, vocabulary size, volume, difficulty, and effort.

Testability

Testability is a metric used to evaluate how easily a software application can be tested. It’s important because it helps in identifying the testing needs of a software application. Testability can be improved by designing software that is modular, well-structured, and easy to maintain.

Code Coverage

Code coverage is used to evaluate the amount of code that has been tested. It is calculated by dividing the number of lines of code that have been executed during testing by the total number of lines of code in the software application. Code coverage helps in identifying areas of the software application that have not been tested and need further testing.

Cyclomatic Complexity

Cyclomatic complexity is a metric used to evaluate the complexity of a software application. It is calculated by counting the number of decision points in the software application. The higher the cyclomatic complexity, the more complex the software application is.

Response Time

Response time is used to evaluate the performance of a software application. It is the time taken by the software application to respond to a user request. A lower response time indicates better performance.

Defect Density

Defect density helps to evaluate the quality of a software application. It’s calculated by dividing the number of defects in the software application by the size of the app. The higher the defect density, the lower the quality of the software application.

Escaped Defects

Escaped defects are defects that aren’t detected during testing and are discovered by users after the software application has been released. It’s a measure of the quality of the software development process. A high number of escaped defects indicates that the software development process needs improvement.

Maintainability Index

Maintainability Index allows you to evaluate how easy it is to maintain a software application. It’s calculated by taking into account various factors such as code complexity, code size, and code documentation. The higher the maintainability index, the easier it is to maintain the software application.

Mean Time Between Failures (MTBF)

MTBF is a metric used to evaluate the reliability of a software application. It is the average time between failures of a software application. A higher MTBF indicates higher reliability of the software application.

Mean Time to Repair (MTTR)

MTTR is a metric used to evaluate how quickly a software application can be repaired after a failure. It is the average time taken to repair a software application after a failure. A lower MTTR indicates that the software application can be repaired quickly, which is important for maintaining high availability

Summary

You’ve learned a list of potential metrics for tracking software quality. Now it's time to choose the metrics that will work for you and be tailored to the goals you want to achieve in the development of your product. To make an informed choice, go to the next chapters of this handbook where we explain each metric, show when and how it is worth tracking it, and in what improvements it can help you.