audit-performance

name	audit-performance
description	Audit hot paths for performance inefficiencies (allocations, contention, layout)
context	fork
agent	auditor
disable-model-invocation	true

Audit the Caffeine cache for performance inefficiencies.

Context: Caffeine runs in high-throughput, low-latency JVM services where cache operations occur millions of times per second. The library is already heavily optimized — generic textbook advice is not useful.

Rules

1. Read the actual source code before analyzing.
2. Only report findings traceable to specific lines.
3. Account for JIT compilation. C2 eliminates many apparent inefficiencies: escape analysis, inlining, dead code elimination. Don't flag JIT-optimized issues.
4. Ignore correctness, style, and API design. This is purely runtime performance.
5. Quality over quantity. Five real findings beat twenty speculative ones.

Analysis Areas (priority order)

1. Get Fast Path (highest priority)

Trace get()/getIfPresent() from entry to return. Count volatile/opaque reads, method calls, branches, allocations. Even one saved volatile read matters.

2. Allocation and GC Pressure

Identify allocations surviving escape analysis on hot paths. Frequency, size, lifetime. Do not flag JIT-eliminated allocations.

3. Contention and Cache-Line Effects

CAS retry rates, cache-line bouncing, graceful vs catastrophic degradation for read buffer, evictionLock, CHM bins, node field updates.

4. FrequencySketch

Counter layout locality, hash computation, reset cost. Accessed every read/write.

5. Maintenance Work

Worst-case work per write, latency spikes, eviction cascades, timer wheel scan cost.

6. Memory Layout

Node object size, pointer indirection depth, false sharing, @Contended opportunities.

Output Format

For each finding:

## [Category] Title
**Location:** file:method (lines X-Y)
**Severity:** negligible | moderate | high
**What happens:** (trace the code path)
**Why it matters:** (quantify)
**JIT considerations:** (will C2 handle this?)
**Proposed fix:** (specific code change)
**Expected benchmark impact:** (JMH prediction)

If fewer than 3 real issues, the code is well-optimized. Do not pad the output.