Test-Related Measures

Test-Related Measures

Testing techniques are often confused with testing objectives. The degree of test coverage is not the same as the high quality of the system under test. However, these issues are interrelated. The higher the degree of coverage, the greater the probability that hidden defects will be detected. When we talk about the test execution results, we should analyze them in the same way as we do the system being tested. It is the quantitative evaluation of the test results (but not the tests themselves, for example, the degree to which they cover possible scenarios of the system’s operation) are discussed below. In turn, the metrics of the tests themselves or of the testing process, as such, are the issues considered in the fields of expertise “Software Engineering Processes” and “Software Engineering Management”.


Measurement instruments are designed as a tool for quality analysis. Test results are measured to evaluate the quality of the product which is a software system. The history of measurements demonstrates the progress in terms of achieving an acceptable quality. This history has to do with a quality management tool.


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Evaluation of the program under test, IEEE 982.1-98


Program measurements as part of planning and design testing


The measurements can be based on the size of the programs (for example, in terms of the number of lines of program code or function points) or their structure (for example, in terms of assessing its complexity in certain architectural terms). Structural measurements can also include the frequency of calls made by some program modules to others.


Types of defects in software testing, their classification and statistics


The testing literature classifies a large amount of different defects. The effectiveness of testing can be achieved if we understand what types of defects can be found in the testing of the software system and how their frequency varies with time (implying a historical perspective of the system’s development, and not its operation failures). This information allows you to predict the quality of the system and helps to improve the overall development process.

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