SonarQube measures code quality based on different metrics. The most important metric is the code coverage metric. In this case, no tests have been written, which means you have no code coverage. The cool thing about SonarQube is that it indicates the number of lines that aren’t covered by tests.

What is SonarQube coverage?

Test coverage reports and test execution reports are important code quality metrics that you can import into SonarQube. Test coverage reports tell you the percentage of your code that is covered by your test cases. Test execution reports tell you which tests have been run and their results.

What is difference between JaCoCo and SonarQube?

JaCoCo vs SonarQube: What are the differences? JaCoCo: A code coverage library for Java. It is a free code coverage library for Java, which has been created based on the lessons learned from using and integration existing libraries for many years; SonarQube: Continuous Code Quality.

How does SonarQube calculate test coverage?

How does Sonarqube calculate the ‘Coverage’

  1. CT = conditions that have been evaluated to ‘true’ at least once.
  2. CF = conditions that have been evaluated to ‘false’ at least once.
  3. LC = covered lines = lines_to_cover – uncovered_lines.
  4. B = total number of conditions.
  5. EL = total number of executable lines (lines_to_cover)

Which tool is used for code coverage?

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.

What is the use of SonarQube in Jenkins?

SonarQube is an open-source platform, which is used for continuous analysis of source code quality by performing analysis on your code to detect duplications, bugs, security vulnerabilities and code smells on programming languages.

How do you measure code coverage using SonarQube and JaCoCo?

We’ll set up:

  1. an instance of SonarQube running in Docker.
  2. a Java project with a class and some unit tests.
  3. a Gradle build which generates a Jacoco code coverage report then runs the SonarQube scanner against the Java project.

Which is the special feature of SonarQube?

SonarQube is a mainly known for Code analysis tool which analyzes source code as per industry standards, and provides standard and advance reports for the improve quality. It combines static and dynamic analysis tools and easy to read is also a lot easier with SonarQube.

How do you generate reports in SonarQube?

How to generate PDF form SonarQube™? With bitegarden Report for SonarQube™ these reports can be generated in the simplest way possible. Browsing the project space in the “More …“ option you will find a section that provides all the reports that you need, from an executive summary to a report with all the issues found.

Is Jenkins a code coverage tool?

java class in Figure 2.31, “Jenkins lets you display code coverage metrics for packages and classes”). Code coverage metrics are a great way to isolate code that has not been tested, in order to add extra tests for corner cases that were not properly tested during the initial development, for example.

Does SonarQube use JaCoCo?

SonarQube is used in integration with JaCoCo, a free code coverage library for Java.

Is Clover a code coverage tool?

Clover is an extremely useful code coverage tool for organizations that embrace a ‘shift left’ approach to testing or Agile methodologies. Clover supports Windows, Linux and Mac OS X operating systems and Java and Groovy for code coverage. Redundant and superfluous tests are noted through a per-test coverage feature.

What is the difference between code coverage and test coverage?

Code Coverage vs Test Coverage. So, now we know that code coverage is a measure of how much code is executed during testing, while test coverage is a measure of how much of the feature set is covered with tests.

What is GCOV code coverage?

Gcov is a source code coverage analysis and statement-by-statement profiling tool. Gcov generates exact counts of the number of times each statement in a program is executed and annotates source code to add instrumentation. Gcov comes as a standard utility with the GNU Compiler Collection (GCC) suite.

How is code coverage calculated?

To calculate the code coverage percentage, simply use the following formula: Code Coverage Percentage = (Number of lines of code executed by a testing algorithm/Total number of lines of code in a system component) * 100.

What is coverage criteria in software testing?

A coverage criterion is a rule or collection of rules that impose test requirements on a test set [Ammann, Offutt]. The coverage criterion describes test requirements completely and unambiguously. In our sanitizer example, we have a sanitizer type criterion.

Which testing has better code coverage?

Why You Should Perform Code Coverage? Unit tests are primarily used to test the code at an individual unit level. Since unit tests are written by the developer himself, he has better visibility of the tests that should be included as a part of unit testing.

What are types of code coverage?

Following are the types of code coverage Analysis:

  • Statement coverage and Block coverage.
  • Function coverage.
  • Function call coverage.
  • Branch coverage.
  • Modified condition/decision coverage.

Why do we need code coverage?

Higher code coverage increases your chances of finding bugs. And while code coverage doesn’t guarantee perfection, you’ll be significantly less effective without it. Put simply, code coverage tells you how much of your code your tests are reaching. 80% code coverage means 80% of your code is executed during test runs.

Is code coverage testing black box?

Code coverage is often the applied methodology in white-box testing. In model-based testing, as a testing heuristic, one often also uses various coverage metrics to measure the quality of generated test suite with respect to the model from which the test suite was derived.

Is code coverage a good metric?

Code coverage is a metric that can help you understand how much of your source is tested. It’s a very useful metric that can help you assess the quality of your test suite, and we will see here how you can get started with your projects.

How does JaCoCo code coverage work?

JaCoCo mainly provides three important metrics: Lines coverage reflects the amount of code that has been exercised based on the number of Java byte code instructions called by the tests. Branches coverage shows the percent of exercised branches in the code, typically related to if/else and switch statements.

Which of the following is not black-box testing?

Exploratory testing, model based testing and requirement testing is black box testing techniques that are used to test the system or program. Therefore, fault injection is not a black box testing.

Which testing is performed first?

Testing which performed first is –

Static testing is performed first.

What is difference between retesting and regression testing?

In other words, regression testing is about searching for defects, whereas retesting is about fixing specific defects that you’ve already found. They can therefore occur in one and the same testing process, where: You update your software with a new feature. You test the existing functionality (regression testing)

Who performs beta testing?

real users

Beta Testing is performed by real users of the software application in a real environment. Beta testing is one of the type of User Acceptance Testing.

What is the difference between UAT and beta testing?

Key Differences Between UAT and Beta Testing

Beta testing is done by the end user. UAT is done by one or two users. Beta testing can be done by hundreds or thousands. UAT often involves working alongside the testing and/or development team.

What is difference between alpha testing and beta testing?

Alpha testing is predominantly about ensuring bug-free functionality. Beta testing involves releasing the software to a limited number of real users. They are free to use it as they want. In other words, this testing is unstructured.