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Coverage in integration tests

Coverage in integration tests
  1. What is integration test coverage?
  2. Should code coverage include integration tests?
  3. What is test coverage in testing?
  4. How do you measure test coverage?
  5. How does SonarQube integrate code coverage?
  6. Is jest only for unit testing?
  7. What is the difference between code coverage and test coverage?
  8. Is a code coverage tool in continuous integration?
  9. Does 100% code coverage during testing ensure a quality product?
  10. Can you reach 100% test coverage?
  11. What are KPIs in testing?
  12. How important is test coverage?

What is integration test coverage?

Integration tests on the other hand are much slower, but they can test the application under real conditions, test HTTP protocol interaction, etc. Going back to code coverage, code coverage is nothing more but checking which lines of code were executed during a test run.

Should code coverage include integration tests?

No. Coverage metrics simply tell you which code was executed. Period. It doesn't you what that code was executed for (integration tests, unit tests, performance tests, etc.).

What is test coverage in testing?

Test coverage is defined as a metric in Software Testing that measures the amount of testing performed by a set of test. ... In simple terms, it is a technique to ensure that your tests are testing your code or how much of your code you exercised by running the test.

How do you measure test coverage?

You simply take:

  1. (A) the total lines of code in the piece of software you are testing, and.
  2. (B) the number of lines of code all test cases currently execute, and.
  3. Find (B divided by A) multiplied by 100 – this will be your test coverage %.

How does SonarQube integrate code coverage?

To scan a specific codebase you run the SonarQube scanner. This is a local process that analyses your code then sends reports to the SonarQube server.
...
SonarQube is a tool which aims to improve the quality of your code using static analysis techniques to report:

  1. code coverage.
  2. bugs.
  3. code smells.
  4. security vulnerabilities.

Is jest only for unit testing?

In this Jest tutorial we'll cover only unit testing, but at the end of the article you'll find resources for the other types of tests.

What is the difference between code coverage and test coverage?

For those who aren't familiar with these terms, code coverage is a measure of code that is executed throughout testing, while test coverage is a measure of how much of the feature being tested is actually covered by tests*.

Is a code coverage tool in continuous integration?

Code coverage tools are available for many programming languages and as part of many popular QA tools. They are integrated with build tools like Ant, Maven, and Gradle, with CI tools like Jenkins, project management tools like Jira, and a host of other tools that make up the software development toolset.

Does 100% code coverage during testing ensure a quality product?

In short no, a Code Coverage metric does not improve the quality of a project at all. There's also a common belief that Code Coverage reflects the quality of the unit tests but it doesn't. It doesn't give you an information what parts of your system are properly tested either.

Can you reach 100% test coverage?

“You can have 100 percent coverage with completely worthless tests,” they'll point out. And they'll be completely right. To someone casually consuming this metric, the percentage can easily mislead. After all, 100 percent coverage sounds an awful lot like 100 percent certainty.

What are KPIs in testing?

KPIs or Key Performance Indicators in the software testing industry are some measurable values that are computed to gauge the efficiency and effectiveness of the testing process as a whole.

How important is test coverage?

Test Coverage is an important indicator of software quality and an essential part of software maintenance. It helps in evaluating the effectiveness of testing by providing data on different coverage items. It is a useful tool for finding untested parts of a code base.

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