Let’s face it. So many aspects of software development can aptly be described as tedious. Chief among those is automated testing.

Testing has long been relegated to the dusty, windowless back offices of our ship-features-or-else world. We do it under duress from pointy-haired managers, with a begrudging sense of responsibility, and a vague sense of unease about what we’re actually accomplishing by satisfying coverage goals.

We can do better.

It is high time we offered first-class citizenship to our software tests. We envision new tooling that illuminates the path for engineering teams to significantly improve the state of their automated testing. One that encompasses deep observability techniques so we know what is and isn’t being tested (and whether or not it matters). One that captures and surfaces more context about the test itself, and the application under test, so we can make more intelligent decisions about the issue we’re trying to resolve. One that understands what we’re trying to accomplish with a given test, and becomes a useful assistant in modifying, updating, extending, rewriting or sunsetting it. This is the next generation of test automation tooling.

With the emergence of modern technologies like distributed tracing and powerful large language models, we are finally able to turn our vision of a new testing toolkit into reality. CodeComet is our first step towards this vision. Our goal is to reignite interest, and dare we say enjoyment, in the process of automated testing. If you catch yourself smiling the first time you launch our tools, we’ll pretend to be mildly surprised (while internally jumping for joy). 🙂

We envision a foundational set of features and functionality that we deem essential to the next generation of test tooling:

• Advanced Testing Analytics: Understand exactly what's happening within each test, with clear and granular data into test performance and behavior.

  
  

• Intelligent Test Coverage Maps: Visualize exactly which portions of your application are covered by tests, and how well.

  
  

• Cross-Application Test Tracing: Follow the thread of your tests across applications and services.

  
  

• Dynamic Test Selection: Save time by only running the tests that matter.

  
  

• Real-World Usage Correlation: Align your tests (and testing efforts) with how your application is actually being used.

  
  

• Automated Test Development: Speed up creating and updating tests by offloading tedious steps to our system.

  
  

• Proactive Test Suggestions: Get insights into where to focus your next testing efforts.

  
  

• Efficient Test Pre-Execution: Use smart pre-execution and caching strategies for quicker testing results.

  
  

• Scalable Test Execution: Ramp up test execution capabilities as demands scale with your project.

  
  

• Distributed Testing Framework: Run your tests wherever you'd like, from the cloud to your local machine.

  
  

We’re sure there’s even more just around the corner. While we have grander ambitions in the long run, we’ve reined them in for our first pass. We won’t launch with everything listed above. As a specific example, we will only support Go and Python to begin with. We want to make sure we know how to walk before we run. So we are building something compact and compelling, that works as advertised, and doesn’t skip those easy-to-neglect edge cases.

Though we are early in this journey, we are committed to building developer-focused tools that bring us closer to the future of software testing that we’ve dreamed about. A future where testing is observable, effective, comprehensive…and enjoyable. 🙂

If our vision of CodeComet resonates with you, we would love to hear from you.