Memory Settings

Optimize BrowserStack Code Quality memory allocation for efficient analysis based on codebase size.

Memory Configuration Requirements

For repositories with 2+ million lines of code, proper memory configuration is essential for successful analysis.

Key Memory Settings:

Container Memory (-m): Total memory allocated to Docker container
Analyzer Heap (ANALYSER_XMX): Memory specifically for analysis engine
Risk Engine (RISK_XMX): Memory for risk calculation operations

Memory Recommendations by Codebase Size

Lines of Code	`ANALYSER_XMX`	Container Memory (`-m`)	Recommended Host RAM
Up to 1 Million	`-Xmx6g`	`12GB`	16 GB
2-10 Million	`-Xmx15g`	`30GB`	32 GB
10+ Million	`-Xmx30g`	`60GB`	64 GB
20+ Million	`-Xmx45g`	`90GB`	128 GB

Memory Allocation Rules

Keep ANALYSER_XMX ≤ 70% of container memory
ANALYSER_XMX scales proportionally with lines of code (LOC)
ANALYSER_XMX and RISK_XMX are independent, non-overlapping settings
Reserve 20-30% container memory for system operations and UI processes

Memory Percentage Guidelines

Analyzer Memory as Percentage of Total Container Memory:

< 1M LOC: 35-40% (allows overhead for UI and system processes)
1-3M LOC: 40-45% (balanced allocation for medium repositories)
3-5M LOC: 50-55% (increased analyzer priority for large codebases)
> 5M LOC: 60-70% (maximum allocation for very large repositories)

WARNING

Never exceed 70% allocation for ANALYSER_XMX as this can cause container instability and OOM errors in system processes.

Code Duplication Impact

High Duplication Scenarios:

Generated code or auto-generated files in repository
Framework dependencies with similar patterns
Copy-paste code across multiple modules

Memory Adjustment for Duplication:

bash

# Base recommendation for 1M LOC
ANALYSER_XMX=-Xmx6g

# High duplication adjustment (+20-30%)
ANALYSER_XMX=-Xmx8g

# Repository with significant code duplication (+40-50%)  
ANALYSER_XMX=-Xmx9g

Docker Compose Configuration

yaml

version: '3.8'
services:
  app:
    image: "browserstack/code-quality:1.9.36.0"
    environment:
      - ANALYSER_XMX=-Xmx15g
      - RISK_XMX=-Xmx1024m
    deploy:
      resources:
        limits:
          memory: 30G
        reservations:
          memory: 20G

Docker Run Configuration

bash

docker run -m 30GB -d \
  --name BrowserStackCodeQuality \
  -e ANALYSER_XMX=-Xmx15g \
  -e RISK_XMX=-Xmx1024m \
  -e EMB_ANALYSER_THREADS=8 \
  -p 3000:3000 \
  browserstack/code-quality:1.9.36.0

Memory Distribution Guidelines

Analyzer Memory as Percentage of Container Memory

Repository Size	Analyzer Memory %	System Reserve %
< 1M LOC	35-40%	25-30%
1-5M LOC	40-50%	20-25%
5-10M LOC	50-60%	15-20%
> 10M LOC	60-70%	10-15%

Memory Monitoring and Optimization

Monitor Container Memory Usage

bash

# Real-time memory monitoring
docker stats BrowserStackCodeQuality

# Memory usage during analysis
docker exec BrowserStackCodeQuality top -p $(pgrep java)

Check Java Heap Usage

bash

# JVM memory information
docker exec BrowserStackCodeQuality jstat -gc $(pgrep java)

# Heap dump for analysis (if needed)
docker exec BrowserStackCodeQuality jmap -dump:format=b,file=/tmp/heapdump.hprof $(pgrep java)

Performance Optimization Strategies

For High Code Duplication

Characteristics:

Multiple similar files or libraries
Generated code or auto-generated files
Large framework dependencies

Adjustments:

Increase ANALYSER_XMX by 20-30%
Monitor memory usage patterns during analysis
Consider excluding auto-generated files from analysis

For Multi-Language Repositories

Memory Impact:

Each language parser requires additional memory
Complex language interactions increase memory usage
Cross-language dependency analysis needs more resources

Recommendations:

Add 2-4GB to base ANALYSER_XMX recommendation for multi-language projects
Increase EMB_PARSER_THREADS for parallel processing efficiency
Monitor per-language analysis performance and adjust accordingly

For C/C++ Projects - Strict Mode Analysis

NOTE

C++ Repositories: For improved analysis accuracy, especially with build integration, consider Remote Scan with Strict Mode. This significantly enhances code quality detection but requires additional memory allocation.

C++ Strict Mode Requirements:

Additional Memory: Increase ANALYSER_XMX by 30-50% above base recommendation
Build Integration: Requires embold-trace tool for comprehensive analysis
Remote Scan Setup: See Integration Guide for detailed configuration

C++ Memory Scaling:

bash

# Standard C++ project (1M LOC)
ANALYSER_XMX=-Xmx6g

# C++ with Strict Mode (1M LOC) 
ANALYSER_XMX=-Xmx8g

# Large C++ project with Strict Mode (5M LOC)
ANALYSER_XMX=-Xmx40g

Troubleshooting Memory Issues

Out of Memory Errors

Symptoms:

OutOfMemoryError: Java heap space
Analysis terminated unexpectedly
Container restart during analysis

Solutions:

Increase ANALYSER_XMX (ensure < 70% of container memory)
Increase container memory limit (-m parameter)
Reduce concurrent analysis threads
Enable garbage collection logging for detailed analysis

Performance Degradation

Indicators:

Analysis takes significantly longer than expected
High CPU usage with low progress
Frequent garbage collection events

Optimizations:

Monitor memory allocation patterns
Adjust thread counts based on available memory
Consider incremental or remote scanning approaches
Use SSD storage to reduce memory pressure from I/O operations

Memory Configuration Testing

bash

# Test memory configuration before major analysis
docker exec BrowserStackCodeQuality java -XX:+PrintFlagsFinal -version | grep HeapSize

# Verify container memory limits
docker inspect BrowserStackCodeQuality | grep -A 3 "Memory"

# Check system memory availability
free -h && echo "Docker Host Memory Available"

# Monitor memory allocation during analysis
docker stats --format "table {{.Container}}\t{{.CPUPerc}}\t{{.MemUsage}}\t{{.MemPerc}}" BrowserStackCodeQuality

# Real-time Java process monitoring
docker exec BrowserStackCodeQuality sh -c 'while true; do ps aux | grep java | grep -v grep; sleep 5; done'

Advanced Memory Tuning

Garbage Collection Optimization:

bash

# Enable GC logging for analysis optimization
docker run -m 30GB -d \
  --name BrowserStackCodeQuality \
  -e ANALYSER_XMX="-Xmx15g -XX:+UseG1GC -XX:+PrintGC -XX:+PrintGCDetails" \
  -e RISK_XMX=-Xmx1024m \
  browserstack/code-quality:1.9.36.0

Heap Dump Collection (for troubleshooting):

bash

# Generate heap dump during OOM issues
docker exec BrowserStackCodeQuality jmap -dump:format=b,file=/opt/gamma_data/logs/heapdump_$(date +%Y%m%d_%H%M).hprof $(pgrep -f "java.*gamma")

# Analyze heap usage patterns
docker exec BrowserStackCodeQuality jstat -gc $(pgrep -f "java.*gamma") 5s

Best Practices

Start Conservative: Begin with recommended settings and incrementally adjust based on actual performance data
Monitor First Scan: Watch memory usage closely during initial repository analysis to identify bottlenecks
Document Optimal Settings: Record successful memory configurations for each major repository or project type
Regular Performance Review: Reassess memory needs quarterly as codebases grow or change significantly
Test Changes Safely: Validate memory adjustments in non-production environments before applying to production
Keep Historical Data: Track memory usage trends over time to predict future scaling needs

Memory Configuration Checklist

Before Analysis:

[ ] Verify container memory allocation matches recommendations
[ ] Confirm ANALYSER_XMX is ≤ 70% of container memory
[ ] Check available host system memory
[ ] Review repository characteristics (size, languages, duplication level)

During Analysis:

[ ] Monitor container memory usage with docker stats
[ ] Watch for OOM errors in application logs
[ ] Track analysis performance and completion time
[ ] Monitor system resource availability

After Analysis:

[ ] Document successful memory settings for this repository type
[ ] Record any performance issues or optimization opportunities
[ ] Update memory recommendations based on actual usage patterns

Environment Variables – Complete configuration reference including memory variables
Database Backup – Data protection procedures that may impact memory usage
Updates Guide – Version management and memory requirement changes

Was this page helpful?

Memory Settings ​

Memory Configuration Requirements ​

Memory Recommendations by Codebase Size ​

Memory Allocation Rules ​

Memory Percentage Guidelines ​

Code Duplication Impact ​

Docker Compose Configuration ​

Docker Run Configuration ​

Memory Distribution Guidelines ​

Analyzer Memory as Percentage of Container Memory ​

Memory Monitoring and Optimization ​

Monitor Container Memory Usage ​

Check Java Heap Usage ​

Performance Optimization Strategies ​

For High Code Duplication ​

For Multi-Language Repositories ​

For C/C++ Projects - Strict Mode Analysis ​

Troubleshooting Memory Issues ​

Out of Memory Errors ​

Performance Degradation ​

Memory Configuration Testing ​

Advanced Memory Tuning ​

Best Practices ​

Memory Configuration Checklist ​

Related Documentation ​

Memory Settings

Memory Configuration Requirements

Memory Recommendations by Codebase Size

Memory Allocation Rules

Memory Percentage Guidelines

Code Duplication Impact

Docker Compose Configuration

Docker Run Configuration

Memory Distribution Guidelines

Analyzer Memory as Percentage of Container Memory

Memory Monitoring and Optimization

Monitor Container Memory Usage

Check Java Heap Usage

Performance Optimization Strategies

For High Code Duplication

For Multi-Language Repositories

For C/C++ Projects - Strict Mode Analysis

Troubleshooting Memory Issues

Out of Memory Errors

Performance Degradation

Memory Configuration Testing

Advanced Memory Tuning

Best Practices

Memory Configuration Checklist

Related Documentation