Agile Testing Metrics to Measure the Performance of Software Testing Process

Not all metrics in scrum are easy to measure, and software quality is one of the hardest. The definition is subjective; the closest measurable metric is the escaped defects metric. That’s perhaps why not everyone considers this, but at the end of the day, a software engineering team’s goal is to build high-quality software. In Scrum projects, ROI can be calculated by assessing the revenue generated by a developed product vs. the costs of each sprint required to develop a product. The fact of the matter is that the Scrum framework can help products generate revenue much faster than the traditional methods (it does not guarantee this).

This in comparison with the actual values will trigger an early red flag that test processes need to change if the targets are to be reached. Typically, pie charts or histograms are used to get a quick snapshot of work assignment. The chart below immediately brings to our attention that Bob is overbooked and David is underutilized. This gives the test lead/manager an opportunity to look into why that is the case and take corrective measures if needed. Before you do so, it is important to tell your team to be unbiased and define what a good test set means.

Defects created vs. defects resolved chart

No metrics will improve product quality, only observing a satisfactory Definition of Done will achieve that. The best measurements are usually taken as closely as possible to the time and place of work being carried out. As a user, I want my software product to work and behave as intended. Accumulate and ignore enough defects and sooner or later your customer(s) will stop using your product and use someone else’s instead.

A defect management dashboard helps the Agile team responsible for fixing defects to identify each reporter’s issue based on priority to determine how quickly each needs to be addressed. Security and safety issues, as well as other critical defects, will stand out, as well as patterns in how often and where defects are most commonly occurring. Scrum Masters can plan time and personnel for fixing defects into their future sprints with more accuracy and work the currently most important fixes into this or the next sprint.

What is Defect Density in software testing

There’s been one thing missing in all the scrum metrics we covered—software quality. The escaped defects metrics alone provides a view of quality, and it is an imperfect metric which identifies quality issues only after they are released to production. Of course, defect density is a powerful measure of the effectiveness of a software development process. When bugs consistently escape to production it tells us the something is seriously wrong in our software development process. Teams who adopt test-driven development and the other Extreme Programming practices often see a huge drop in defect density. Defects are expensive so dropping in defect density also drops costs.

You can access pre-formatted, pre-grouped, and segregated logs and traces that indicate defects. A centralized view of these logs simplifies data sharing and coordination within the team, fostering problem-solving through quick communication and teamwork. With observability, you do not need agile defect density to comb through individual logs and traces — you can track your applications and view real-time data in a centralized dashboard. This Scrum metric measures whether it’s worthwhile to continue a project or not. When the costs of development exceed the value, it’s time for the project to end.

Customer Satisfaction

Developers have access to a lot of tools that can help them find bugs while they are writing and testing their own code. It is hard to imagine the days when developers fed a stack of punch cards into a mainframe and waited to figure out if it worked or not. Obviously, we don’t want to break things in production environments.

Work moves like a virtual assembly line from one person to the next; one environment to the next. For many organizations, the journey from development to Production (left to right) looks similar to the diagram below. However, this metric can be misleading if the complexity of the code is not considered, as different parts of the code have a different degree of complexity. As a general practice, your set of metrics should also have a cost related test metrics. Total time a feature exists from initial creation to customer delivery — similar to lead time in kanban. Queue length provides a view of how many items are sitting in each column over time.

Defect Detection Percentage (DDP)

This helps developers trace the affected areas properly, allowing them to achieve highly accurate results. Software is tested based on its quality, scalability, features, security, and performance, including other essential elements. It’s common to detect defects and errors in a software testing process. However, developers must ensure they are taken care of before launching it to the end-users. This is because fixing an error at an early stage will cost significantly less than rectifying it at a later stage.

• It’s common to detect defects and errors in a software testing process.
• However, if there too many causes and the histogram or pie chart is insufficient to show the trends clearly, a Pareto chart can come in handy.
• Cumulative flow diagrams use color-coding to represent different statuses (e.g., in progress, done, in backlog).
• Queue length provides a view of how many items are sitting in each column over time.
• It enables one to decide if a piece of software is ready to be released.
• The growing and shrinking bars capture attention and communicate progress and speed much more effectively.

The balance of software development is figuring out how fast we can move, while taking an appropriate amount of risk. If the total number of defects at the end of a test cycle is 30 and they all originated from 6 modules, the defect density is 5. Defect removal efficiency is the extent to which the development team is able to handle and remove the valid defects reported by the test team. With the distribution over time, you will know what’s been going with the defects in each category. We can see if defects have been increasing, decreasing or are stable over time or over releases.

Methodology-specific agile metrics

Knowing this number will help predict the amount of defects that could be expected per new change. This allows test teams to strategically use retrospective meetings to understand their capacity to help identify and fix defects coming from new changes. These charts help in understanding how the rate of testing and the rate of defect finding compare with desired values. Test Execution snapshot chart shows the total executions organized as passed, failed, blocked, incomplete, and unexecuted for easy absorption of the test run status.

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Defect Density: Context is King.

I will rarely look at the severity of the defect and treat all defects as equal. Defect ratio is a metric that indicates just how many bugs users have experienced during the development process. As you may already know, nothing can be 100% bug-free but Agile emphasizes that the number of bugs within software gets reduced to a minimum. A Scrum team tests each story to avoid defect but it sometimes happens that a few defects manage to escape.