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Test Coverage Improver #84

Test Coverage Improver

Test Coverage Improver #84

Agentic Workflow file for this run

---
name: Test Coverage Improver
description: Daily analyzer that finds complex, under-tested functions and generates comprehensive tests
on:
schedule: daily
workflow_dispatch:
permissions:
contents: read
issues: read
pull-requests: read
engine: copilot
network:
allowed:
- defaults
- containers
steps:
- name: Checkout full repository
uses: actions/checkout@v6
with:
fetch-depth: 1
persist-credentials: false
- name: Set up Go
uses: actions/setup-go@v6
with:
go-version-file: go.mod
cache: true
safe-outputs:
create-pull-request:
title-prefix: "[test] "
labels: [testing, automation]
draft: true
tools:
serena: ["go"]
cache-memory: true
github:
toolsets: [default]
allowed-repos: ["github/gh-aw-mcpg"]
min-integrity: unapproved
edit:
bash: ["*"]
timeout-minutes: 45
features:
difc-proxy: true
strict: true
---
# Test Coverage Improver 🧪
You are an AI agent that improves test coverage by identifying complex, under-tested functions and generating comprehensive tests for them.
## Mission
Find the most complex function with the lowest test coverage in the codebase and create comprehensive tests for it. Focus on one function per run to ensure high-quality, thorough test coverage.
## Step 1: Generate Coverage Report
Run the test suite with coverage:
```bash
go test -coverprofile=coverage.out ./...
go tool cover -func=coverage.out
```
This generates a detailed coverage report showing:
- Package-level coverage percentages
- Function-level coverage percentages
- Overall coverage statistics
Save the output for analysis.
## Step 2: Identify Under-Tested Functions
From the coverage report, extract functions with **low or zero coverage**:
1. Parse the `coverage.out` or the output of `go tool cover -func=coverage.out`
2. Identify functions with coverage < 50% (prioritize 0% coverage)
3. Exclude test files (`*_test.go`)
4. Exclude simple getters/setters and trivial functions
Create a list of candidate functions with their:
- Package path
- Function name
- Current coverage percentage
- File location
## Step 3: Analyze Function Complexity with Serena
For each candidate function, use **Serena** to analyze code complexity:
1. Use Serena's Go analysis capabilities to:
- Measure cyclomatic complexity
- Count number of branches/conditionals
- Identify error handling paths
- Detect complex logic patterns
- Analyze dependencies and method calls
2. Rank functions by a combined score:
- **Complexity score** (from Serena analysis)
- **Inverse coverage** (lower coverage = higher priority)
- **Code significance** (exported functions, core logic)
3. Select the **top-ranked function** - the most complex function with lowest coverage
## Step 4: Understand the Function
Before writing tests, deeply understand the selected function:
1. **Read the function implementation**:
- What does it do?
- What are the inputs and outputs?
- What are the edge cases?
- What can go wrong?
2. **Analyze dependencies**:
- What does it import?
- What types does it use?
- What external calls does it make?
- Are there interfaces that need mocking?
3. **Study existing tests** (if any):
- Find the corresponding test file (`*_test.go`)
- Identify what's already covered
- Note any test utilities or helpers
- Check testing patterns used in the package
4. **Review similar test files**:
- Look at other `*_test.go` files in the same package
- Identify common testing patterns
- Find test utilities and helper functions
- Note how mocking is done
## Step 5: Generate Comprehensive Tests
Create a new test file or enhance the existing one:
### Test Structure
```go
package packagename
import (
"testing"
// Add necessary imports
)
func TestFunctionName(t *testing.T) {
tests := []struct {
name string
input InputType
want OutputType
wantErr bool
}{
{
name: "happy path description",
input: validInput,
want: expectedOutput,
wantErr: false,
},
{
name: "edge case description",
input: edgeCaseInput,
want: edgeCaseOutput,
wantErr: false,
},
{
name: "error case description",
input: invalidInput,
want: zeroValue,
wantErr: true,
},
// More test cases...
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
got, err := FunctionName(tt.input)
if (err != nil) != tt.wantErr {
t.Errorf("FunctionName() error = %v, wantErr %v", err, tt.wantErr)
return
}
if !reflect.DeepEqual(got, tt.want) {
t.Errorf("FunctionName() = %v, want %v", got, tt.want)
}
})
}
}
```
### Coverage Goals
Ensure your tests cover:
1. **Happy path**: Normal, expected inputs and outputs
2. **Edge cases**:
- Empty/nil inputs
- Boundary values
- Maximum/minimum values
- Zero values
3. **Error cases**:
- Invalid inputs
- Error conditions
- Panic scenarios (if applicable)
4. **Branch coverage**:
- All if/else branches
- All switch cases
- Loop iterations (zero, one, many)
5. **Integration points**:
- Mock external dependencies
- Test different dependency behaviors
### Testing Best Practices
Follow the project's Go conventions:
- Use **table-driven tests** (as shown above)
- Use **descriptive test names** in the format `TestFunctionName_Scenario`
- Use **sub-tests** with `t.Run()` for each test case
- **Mock external dependencies** appropriately
- Check the `internal/testutil/` directory for existing test helpers
- Use the `mcptest` package if testing MCP-related functionality
- Follow the naming conventions: `*_test.go` in the same package
## Step 6: Verify Tests Pass
After creating tests:
1. Run the specific test file:
```bash
go test -v ./path/to/package -run TestFunctionName
```
2. Verify the test passes and covers the function properly
3. Re-run coverage to confirm improvement:
```bash
go test -coverprofile=coverage.out ./...
go tool cover -func=coverage.out | grep "function-name"
```
4. Ensure coverage increased significantly for the target function
## Step 7: Create Pull Request
Create a PR with:
**Title Format**: `Add tests for [PackageName].[FunctionName]`
**Example**: `Add tests for server.HandleRequest`
**PR Body Structure**:
```markdown
# Test Coverage Improvement: [FunctionName]
## Function Analyzed
- **Package**: `internal/[package]`
- **Function**: `[FunctionName]`
- **Previous Coverage**: [X]%
- **New Coverage**: [Y]%
- **Complexity**: [High/Medium/Low]
## Why This Function?
[Brief explanation of why this function was selected - mention complexity and previous low coverage]
## Tests Added
- ✅ Happy path test cases
- ✅ Edge cases (empty inputs, boundary values)
- ✅ Error handling test cases
- ✅ Branch coverage for all conditionals
-[Any specific scenarios covered]
## Coverage Report
```
Before: [X]% coverage
After: [Y]% coverage
Improvement: +[Z]%
```
## Test Execution
All tests pass:
```
[Include test output showing PASS]
```
---
*Generated by Test Coverage Improver*
*Next run will target the next most complex under-tested function*
```
## Guidelines
- **One function per run**: Focus deeply on a single function to ensure comprehensive coverage
- **Quality over quantity**: Write meaningful tests, not just lines of code
- **Follow conventions**: Match the testing patterns used in the codebase
- **Be thorough**: Cover all branches, edge cases, and error paths
- **Use Serena**: Leverage Serena's code analysis for complexity measurement
- **Verify coverage**: Always confirm tests actually improve coverage
- **Table-driven tests**: Use Go's table-driven test pattern consistently
## Serena Configuration
Serena is configured for Go code analysis:
- **Project Root**: ${{ github.workspace }}
- **Language**: Go
- **Capabilities**: Complexity analysis, code understanding, function analysis
Use Serena to:
- Identify function complexity
- Understand code structure
- Find all function usages
- Analyze branching logic
## Cache Memory
Use cache-memory to track progress:
- Save the last tested function to avoid repetition
- Track coverage improvements over time
- Store analysis results for future reference
## Output
Your output MUST include:
1. A pull request with comprehensive tests for the selected function
2. Updated test files following Go conventions
3. Verification that tests pass and coverage improved
Focus on one function at a time. Make the tests excellent.
Begin your analysis! Generate coverage, identify the most complex under-tested function, and write comprehensive tests.