Performance Analysis and Profiling

• Understanding performance metrics and benchmarks
• Profiling tools and techniques for identifying bottlenecks in Java
• Analyzing CPU, memory, and I/O usage in Java

JVM Internals and Garbage Collection

• JVM architecture and memory management
• Garbage collection algorithms and tuning in Java
• Analyzing and optimizing GC behavior in Java

Java Memory Model

• Memory visibility and ordering guarantees
• Volatile and synchronized keywords
• Atomic classes and non-blocking algorithms

Java Concurrency and Multithreading

• Thread synchronization and coordination
• Concurrent data structures and utilities
• Fine-grained locking and lock-free programming

Low-Level Optimizations

• Microbenchmarking and performance testing
• Techniques for reducing method call overhead
• Optimizing loop performance and data structures

HotSpot JVM Performance Tuning

• JVM flags and runtime options
• JIT compiler and bytecode optimization
• Escape analysis and object allocation optimization

Efficient Data Structures and Algorithms

• Choosing the right data structures for specific use cases
• Designing and implementing high-performance algorithms
• Using specialized collections and libraries

I/O and Networking Performance

• Efficient file I/O and stream processing
• NIO and asynchronous I/O for scalability
• Tuning network performance and latency

Caching and Memory Optimization

• Understanding caching principles and techniques
• Exploiting CPU caches and cache-conscious programming
• Memory layout and data alignment optimizations

Performance Testing and Benchmarking

• Building reliable performance tests
• Profiling and analyzing benchmark results
• Comparing and optimizing algorithms and implementations

High-Performance Frameworks and Libraries

• Using high-performance libraries (e.g., Apache Commons, Guava)
• Leveraging efficient frameworks (e.g., Netty, Akka)
• Performance considerations for popular frameworks (e.g., Spring, Hibernate)

Performance Monitoring and Production Optimization

• Monitoring tools and techniques for production systems
• Profiling in live environments
• Strategies for diagnosing and resolving performance issues