Prompt file imported from SEM-Lab/FAAdditionalFunctionalities (.github/prompts/al-performance.prompt.md). Fill in {{PerformanceIssue}} before use. Copyright stays with the author.

AL Performance Analysis

Your goal is to analyze and optimize performance for {{PerformanceIssue}}.

Performance Analysis Process

1. Generate Performance Profile

Generate CPU profile:

al_generate_cpu_profile_file

2. Analyze Profile Results

• Identify hotspots (functions with high execution time)
• Find frequently called procedures
• Detect inefficient loops
• Locate expensive database operations

3. Common Performance Issues

FlowField Recursive Dependencies (AL0896)

Problem: Circular FlowField references causing infinite evaluation

Solution:

• Break circular dependencies
• Use regular fields with triggers
• Implement alternative calculation methods

Inefficient Queries

Problem: Missing keys, poor filtering

Solution:

• Add appropriate keys
• Use SetLoadFields for partial records
• Optimize filter sequences

Loop Optimization

Problem: Nested loops with database calls

Solution:

// Bad
repeat
    OtherTable.SetRange(Field, MainTable.Field);
    if OtherTable.FindSet() then
        repeat
            // Process
        until OtherTable.Next() = 0;
until MainTable.Next() = 0;

// Good
if OtherTable.FindSet() then
    repeat
        TempTable.Init();
        TempTable.TransferFields(OtherTable);
        TempTable.Insert();
    until OtherTable.Next() = 0;

4. Performance Best Practices

Database Access

• Use partial records with SetLoadFields
• Minimize round trips
• Use temporary tables for complex calculations
• Implement appropriate keys

Code Structure

• Avoid recursive procedures
• Cache calculated values
• Use lazy evaluation
• Minimize event subscriber overhead

FlowFields

• Avoid complex CalcFormula
• Check for circular dependencies
• Consider alternative implementations
• Use SumIndexFields when possible

5. Clean Up

Human Gate: Profile Data Removal Confirmation

Clearing codelenses will remove performance analysis data

Before clearing:

1. Confirm analysis is complete - All data captured?
2. Save important findings - Document bottlenecks identified
3. Obtain approval - Wait for confirmation to proceed

Clear profiling code lenses after analysis (only after approval):

al_clear_profile_codelenses

Optimization Workflow

1. Measure: Generate baseline profile with al_generate_cpu_profile_file
2. Analyze: Identify bottlenecks
3. Optimize: Apply targeted fixes
4. Verify: Re-profile to confirm improvements
5. Clean: Use al_clear_profile_codelenses to clean workspace
6. Document: Record optimization decisions

Performance Targets

• Page load: < 2 seconds
• Report generation: < 10 seconds for standard data
• API calls: < 500ms response time
• Batch processing: > 1000 records/minute