Before starting what is Software Test Metrics and types, I would like to start with the famous quotes in terms of metrics. Software test metrics is to monitor and control process and product. It helps to drive the project towards our planned goals without deviation. It is used to calculate the number of Test Cases prepared and the effort spent for the preparation of Test Cases.
It allows us to compare the overall defects found pre and post-delivery defect removal efficiency. If you have any more questions, feel free to ask via comments. We'll look at an example of a percentage test case executed to see how the test metrics are calculated.
Similarly, you can compute for other parameters such as test cases that were not executed, test cases that were passed, test cases that failed, test cases that were blocked, and so on. Vineet Nanda. Previous Page Print Page. It helps you to quickly find the areas that are most dense the reason for most defects. When creating a histogram, be sure to organize your data values from High to low or low to high for most impact. You can stop here, but to get more out of your metrics, continue with the next step.
Combine the histogram with the distribution of Severity of defects in each cause. This will give you the areas that you should focus on more accurately. So this chart will refine our data and give us a much deeper understanding of where to channel further development and fixing effort.
Defect Distribution Pareto Chart:. You could also create a Pareto chart to find which causes will fix most defects. In many cases, a Pareto chart may not be necessary. 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. Defect distribution at the end of test cycles or at a certain point in test cycles is a snapshot of defect data at that point in time. It cannot be used to derive conclusions if things are getting better or worse.
For example: At a point of time, you will know that are X number of severe bugs. We can see if defects have been increasing, decreasing or are stable over time or over releases. Defect Distribution over time by Cause. Defect Distribution over time by Module. Defect Distribution over time by Severity. Defect Distribution over time by Platform.
Plot a multiline chart for the 3 causes over 5 cycles, as below:. Bug found vs. To start creating Fixed vs. Found chart, you will have to first collect the no. This is one of the charts that need cumulative numbers to make sense.
Consider the following defect data over a 10 day long test cycle:. A defect created vs. This chart is great but there are too many lines that distract us. The raw numbers of bugs created and resolved is meaningless, you can remove them from the chart for a cleaner created vs.
If the green line grew steeper and steeper it means the rate of finding the bugs has not dropped even towards the end of testing. Towards the end of the curve, the created and resolved lines are converging more or less.
This is also a good sign because it shows that the defect management process is working and is fixing the problems effectively. If the blue line is way below the green line, it means the defects are not addressed in a timely way and we might need a process improvement.
Limitations: While this chart answers a lot of important questions, it does have its limitations. 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. While calculated metrics are derived from the data collected in base metrics.
To understand how to calculate the test metrics, we will see an example of a percentage test case executed. Likewise, you can calculate for other parameters like test cases not executed, test cases passed, test cases failed, test cases blocked, etc.
Skip to content. Software Testing Metrics. Project Metrics: It can be used to measure the efficiency of a project team or any testing tools being used by the team members.
Different stages of Metrics life cycle Steps during each stage Analysis Identification of the Metrics Define the identified QA Metrics Communicate Explain the need for metric to stakeholder and testing team Educate the testing team about the data points to need to be captured for processing the metric Evaluation Capture and verify the data Calculating the metrics value using the data captured Report Develop the report with an effective conclusion Distribute the report to the stakeholder and respective representative Take feedback from stakeholder.
Sr Steps to test metrics Example 1 Identify the key software testing processes to be measured Testing progress tracking process 2 In this Step, the tester uses the data as a baseline to define the metrics The number of test cases planned to be executed per day 3 Determination of the information to be followed, a frequency of tracking and the person responsible The actual test execution per day will be captured by the test manager at the end of the day 4 Effective calculation, management, and interpretation of the defined metrics The actual test cases executed per day 5 Identify the areas of improvement depending on the interpretation of defined metrics The Test Case execution falls below the goal set, we need to investigate the reason and suggest the improvement measures.
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