Execution efficiency measures how well code performs its required work while limiting execution time, CPU usage, memory pressure, and other computing resources. Faster, less wasteful execution can reduce operational cost, energy consumption, and strain on user devices. section 8.0 section 8.4.5
Improve execution efficiency by reducing unnecessary work at several layers:
- Optimize database operations with indexes, connection pools, and by avoiding N+1 query patterns. section 8.4.5
- Choose suitable data structures and implementations, then use microbenchmarks to identify more efficient algorithms. section 8.4.5
- Reduce runtime overhead with native compilation; GraalVM Native Image can compile Java applications ahead of time into platform-specific executables. section 8.4.5
- Adjust computational precision when the task permits it, since lower precision can cost fewer resources. section 8.4.5
- Smooth processing loads, such as by partitioning customer IDs into batches before generating invoices. section 8.4.5
Batching invoice generation
Partitioning customer IDs into groups of 200 and processing each group in turn makes workload smoothing explicit: load the IDs, create batches, and generate invoices batch by batch. section 8.4.5
Efficiency is not an invitation to optimize blindly. Prefer the smallest safe improvement, and reject changes whose minor resource savings make code harder to understand or conflict with operational constraints. section 8.5.2
