Jaeger lib (https://github.com/jaegertracing/jaeger-lib/) is an open-source distributed tracing system developed by Uber. Testing and coverage are essential to maintain high code quality in Jaeger lib. This explanation will cover the possible options and provide examples for each option using the provided tools and workflows in Jaeger lib.
Testing in Jaeger lib
Jaeger lib uses different testing tools and workflows to ensure high code quality. The following are some of the testing tools and workflows used in Jaeger lib:
Go Kit
Go Kit is a collection of libraries for building microservices in Go. Jaeger lib uses Go Kit to provide a set of gRPC servers and clients, metrics, and more. Go Kit provides a testing framework that allows writing tests for gRPC servers and clients.
Example:
The following is an example of a Go Kit test for a gRPC server:
func TestGRPCServer(t *testing.T) {
var svc structs.TracerService
var server *grpc.Server
var client tracer.TracerServiceClient
// Initialize the gRPC server and client
server = grpcServer(svc)
conn, err := grpc.Dial("localhost:50051", grpc.WithInsecure())
require.NoError(t, err)
client = tracer.NewTracerServiceClient(conn)
// Test the gRPC server
response, err := client.Trace(context.Background(), &tracer.TraceRequest{})
require.NoError(t, err)
require.NotNil(t, response)
}
pytest-cov
Jaeger lib uses pytest-cov to collect test coverage data for Python code. Pytest-cov is a plugin for pytest that provides test coverage reports.
Example:
The following is an example of a pytest-cov test for Python code:
def test_example():
assert True
# Run the test with pytest-cov
pytest --cov=example_module
Linkerd jaeger
Linkerd jaeger is a command-line tool for checking the Jaeger extension in Linkerd. It allows checking if the Jaeger extension is up and running and opening the Jaeger extension dashboard in a web browser.
Example:
The following is an example of using Linkerd jaeger to check the Jaeger extension:
linkerd jaeger check
Coverage in Jaeger lib
Jaeger lib uses different tools and workflows to measure code coverage. The following are some of the coverage tools and workflows used in Jaeger lib:
JaCoCo
Jaeger lib uses JaCoCo to measure Java code coverage. JaCoCo is a code coverage library for Java that provides code coverage reports.
Example:
The following is an example of using JaCoCo to measure Java code coverage:
# Build the project with JaCoCo
./gradlew jacocoTestReport
# Open the JaCoCo code coverage report
open build/reports/jacoco/test/html/index.html
Cobertura
Jaeger lib uses Cobertura to measure Java code coverage. Cobertura is a code coverage tool for Java that provides code coverage reports.
Example:
The following is an example of using Cobertura to measure Java code coverage:
# Build the project with Cobertura
./gradlew cobertura
# Open the Cobertura code coverage report
open build/reports/cobertura/index.html
Tackle-test
Jaeger lib uses Tackle-test to generate test cases for CTD-guided test generation. Tackle-test is an open-source tool for automated unit testing.
Example:
The following is an example of using Tackle-test to generate test cases:
# Initialize Tackle-test
tackle-test init
# Generate test cases
tackle-test generate
Open Policy Agent
Jaeger lib uses Open Policy Agent to report coverage. Open Policy Agent is a policy engine that provides a unified way to enforce policies across different platforms.
Example:
The following is an example of using Open Policy Agent to report coverage:
opa test --coverage
In conclusion, Jaeger lib uses different tools and workflows to ensure high code quality through testing and coverage. The tools and workflows used in Jaeger lib include Go Kit, pytest-cov, Linkerd jaeger, JaCoCo, Cobertura, Tackle-test, and Open Policy Agent. These tools and workflows help measure code coverage, generate test cases, and ensure high code quality.
