Before implementing or modifying algorithms, carefully evaluate data structure properties and operation costs. Always: 1. **Understand data structure guarantees**: Choose structures that provide the necessary ordering and performance characteristics. For instance, when replacing one structure with another, be aware of their different behaviors: ```java // Problematic: PriorityBlockingQueue doesn't guarantee ordering for equal priorities private final PriorityBlockingQueue shutdownTasks = new PriorityBlockingQueue<>(); // Better: If order matters for equal priorities, use a secondary comparison key private final PriorityBlockingQueue shutdownTasks = new PriorityBlockingQueue<>(11, Comparator .comparing(ShutdownTask::getPriority) .thenComparing(ShutdownTask::getCreationOrder)); ``` 2. **Avoid unnecessary computations**: Eliminate redundant operations by: - Deriving one data structure from another when they contain inverse or related data - Leveraging existing ordering instead of re-sorting collections - Using the most efficient implementation for your specific case (e.g., specific `List.of()` implementations) 3. **Choose appropriate algorithms**: Select the right algorithm for specific operations like version comparison, ensuring it handles edge cases correctly: ```java // Better performance and correctness for version comparisons new ComparableVersion("2.10.0.CR1").compareTo(new ComparableVersion(version)) ``` These optimizations improve both performance and correctness of your code while keeping it maintainable.