Code Coverage for Golang

Testing code coverage for golang is one of the crucial aspects of writing a bugless code. While the Go team has been offering tools around this platform, there’s a need for better code coverage tools.

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RKTracer tool will instrument the code at the source code level with zero modification to your application features, then build will compile the instrumented source and places the statistics in a final output file.

RKTracer code coverage report shows whether a line, statement, and condition has been executed or not, along with the number of times it has been executed.

RKTracer Tool Benefits

  • An alternative to the existing hard-to-use open source tools
  • An alternative to tools that don’t provide enough information about coverage
  • Comprehensive code coverage reports. RKTracer supports Line, statement, Branch, Condition, and Multiple Condition coverage levels.
  • Support and backup for bugs.
  • Flexibility. You can use RKTracer for Python, Kotlin, GoLang, and Swift languages’ code coverage.
  • Golang code coverage integration tests: RKTracer has ready-to-use plugins for Jenkins, SonarQube. It easily integrates with in-house CI.
  • Reliable support from a team with over 20 years of experience.

In this article, you’ll learn:

  • How the RKTracer works on Golang Code coverage
  • How to instrument a project
  • Generate code coverage without unit test cases
  • How to add test cases for uncovered code to increase coverage
  • How to interpret the code coverage report generated by the RKTracer tool. 

We will use a prime example as it is easy to understand. 

A Little Background of Golang Programming Language and Version

Golang is one of the most booming programming languages. This open-source language is freely available and is backed by Google.

Over the past decade, it has evolved to being a critical cloud-centered project. Version 1.13 was released in September 2019.  

Google employees developed Golang as a community-led open-source project. It is easy to learn and work with Golang, and it can be read easily by other developers.

Go has quite some similarities with Java. One of these is that it builds and maintains cross-platform applications of all types.

One of the most remarkable wins of Golang is its applicability in cross-platform CLI tools. RKTracer works seamlessly with Golang in windows, Apple macOS, and Linux.

The Need for Code Coverage in Golang Programming 

Below are some reasons why you should care about Golang code coverage analysis:

  • Easy codebase maintenance. Writing a scalable code is vital if you want to enhance your software with crucial functionalities. A code coverage report will help you ensure that the code quality is well maintained. This way, it gets easier to add new features.
  • You are identifying harmful code in time. The consistent analysis will help you spot code that’s bad, dead, and unused. With this, you’ll be able to improve your code writing practices and end up with a better overall product.
  • Better ROI. A higher return on investment can only be achieved if you reduce production defects before releasing your software to the market. 

RKTracer supports the following Code Coverage levels.

RKTracer has all levels of Golang code coverage. This is unlike many code coverage tools in the market.

The Golang test coverage all packages has criteria comprised of:

  • Function Coverage. The tool checks whether functions in the code have been executed at least once.
  • Line Coverage. This tests the paths that contain a sequence of conditions and controls that have worked well at least once.
  • Statement Coverage. This test checks the number of statements that have been validated in the source code successfully.
  • Branch/Decision Coverage. This Checks if the decision control structures like loops have executed
  • Condition Coverage. For “True” and “False“ conditions, the Boolean expressions are tested at least once.
  • Multiple condition coverage. This covers all the possible outcomes in the source code at least once.

All this is run in a 4-step command process.

  • Instrumentation Project using the RKTracer tool.
  • Testing the application with or without unit test cases.
  • Collect coverage data.
  • Html Report Generation.
RKTracer-working-principle

Example 1-How to generate and increase Code Coverage Golang using RKTracer tool (And Generate an HTML Report)

  • First, Instrument your project using the RKTracer tool.
  • Once your project is instrumented, go ahead and build the project by running a “go build” command. Ensure you’re on the RKTracer tool cover mode. 
  • In this case, we’ll test for primality by entering a few number options – the first test case being 5.
  • Since 5 is a prime number, the result will be one in one test that resulted in a prime number.
  • After this, all we have to do is run the command rkresults to generate the report.
  • The above is the file that got generated and has made a backup of the previous file.
  • As you can see below, the results are clearly and graphically tabulated.
  • Here are the results we got: 
increased-code-coverage-png
  • RKTracer’s color-coding makes it very easy for you to find unreachable code in the HTML reports you get after testing.
  • The clear illustration with the line coverage, statement, and multiple condition coverages come in handy for any developer who intends to understand their code.

After You’ve Generated HTML Report, What’s Next?

The code coverage process using RKTracer can be automated if you choose to test it in Jenkins. You’ll also be able to check reports that have been uploaded by the RKTracer tool to Jenkins.

Want Golang to merge coverage files or test coverage multiple packages? You can merge the code from unit test cases and system testing.

Besides, you may choose to publish the HTML report generated by the RKTracer tool in SonarQube.

For more details on this, see how to publish RKTracer’s Code Coverage reports to Jenkins and Snarqube.

So, this way, RKTracer will help you check and increase the code coverage of your project.

Example 2- Integration Test with Django Framework

This example will give you an idea of how to generate code coverage using the RKTracer tool while performing integration tests with other frameworks. We have already created the built environment and a demo file for the test.

  • Let us instrument the source files, we can instrument the file with the same command, but we have to give the folder’s path with source files that need to be instrumented. So the command will be “rktracer -on ‘The Path’ py -v.”
  • As we press enter, it will instrument all the source files within a few seconds, and it also depends upon the resources available in the build system.
  • As we can see, it has processed 830 (some of them instrumented and some left out because of exclusion of source files from instrumentation) files within 9 seconds.
  • You can also exclude individual files or do selected instrumentation with this configuration file.
  • Now run the test and launch the Django framework server.
  • Keep the application running and open another terminal and send signal “pkill -USR1 -f “python.*manage.py” to dump coverage data without killing the application. Now generate the code coverage report using RKTracer in the new terminal.
  • As you open the report, you can see the overall code coverage.
  • You can search for a particular file and check the code coverage of that particular file.
  • You can open any particular file to see the code coverage, and if you right-click, it will show you the Function Summary, File Summary, and the Project Summary.

So, this way, you can generate code coverage reports by integrating them with any other framework.

Advantages of RKTracer Code Coverage tool:

  • RKTracer is a very ‘easy to use’ tool.
  • Speedy analysis. It instruments hundreds of python source files within seconds.
  • It can generate coverage reports for all testing types, for example, with or without unit test cases.
  • Generates HTML reports with the Line, statement, branch, condition, and multiple conditions levels of code coverage.
  • Generates easy to understand coverage reports.
  • Ready to use plug-ins like Jenkins, SonarQube, and integrates with in-house CI.
  • Support team with over 20 years of experience.

Conclusion:

Code coverage and test coverage are essential to maintain the efficiency of the tests. Different programming languages use different code coverage tools, but RKTracer can make things easy to use with any programming language.

Python is a straightforward yet compelling programming language, and so is the RKTracer tool for code coverage. RKTracer can work on any operating system and any build environment, just like Python.

Using the reports of different code coverage levels generated by The RKTracer tool, the tester can quickly improve the code coverage results. It can also integrate with different frameworks and generate code coverage very effectively.

Other code coverage tools have many problems. They are not easy to use and have no back-up features. They don’t cover all the code coverage levels (Line coverage, Statement coverage, Branch coverage, Condition coverage, and Multi-condition coverage).

RKTracer provides the solution to all these problems and generates more effective and faster results. Yes, code coverage is essential for your project. But that does not mean that it should be a complicated and time-taking process. Make the code coverage an easy and effective process with RKTracer.

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