Implement Block Cache for Filesystem Performance

Caching Below the Filesystem

Block caches keep recently used disk blocks in RAM, keyed by (device, block number). Reads hit RAM; misses fetch from media and insert with eviction policy (LRU or clock).

Cache Structure

Fields per entry:

• block_id and dirty flag
• data[BLOCK_SIZE]
• refcount or LRU timestamp

For example, scanning a 1 MB file with 4 KB blocks touches 256 distinct block IDs; a 64-entry cache captures hot sequential reuse on second pass.

Why This Matters in Production

The hash-table-plus-LRU-list design here is exactly how Linux's unified page cache accelerates every file read, and the clock algorithm mentioned is what the kernel actually uses instead of strict LRU to keep overhead low at scale. Mixing up write-through and write-back semantics is a real source of data-loss bugs: one is safe but slow, the other is fast but loses dirty data on a crash.

Debugging Checklist

Before you call the implementation done, walk failure modes on purpose. Test empty structures, single-element edge cases, maximum concurrency, and errno paths that must not crash the program. OS code usually fails in production when happy-path tests pass but invariants break under contention or memory pressure.

Implementation Notes

Keep structures small and name fields after kernel counterparts when possible. That lets you read man pages and kernel source side by side while you work. Print observable events during development; remove noisy logs once tests pass reliably.

For This Exercise

You will implement get/put with clock eviction and write-back on flush. The task asks you to count cache hits vs misses on repeated reads of the same file.