From 15feb8e6f0e5c8f331a0fc81e99755d7d71666a2 Mon Sep 17 00:00:00 2001
From: "codeflash-ai[bot]"
 <148906541+codeflash-ai[bot]@users.noreply.github.com>
Date: Fri, 20 Feb 2026 09:12:29 +0000
Subject: [PATCH] Optimize _is_inside_lambda
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The optimization achieves a **17% runtime improvement** (from 1.05ms to 894μs) by caching the `current.type` attribute access in a local variable (`t` or `current_type`) inside the loop. This seemingly small change reduces repeated attribute lookups on the same object during each iteration.

**What Changed:**
Instead of accessing `current.type` twice per iteration (once for each conditional check), the optimized version stores it in a local variable and reuses that value. This transforms two attribute lookups into one per iteration.

**Why This Improves Performance:**
In Python, attribute access involves dictionary lookups in the object's `__dict__`, which carries overhead. By caching the attribute value in a local variable, the code performs this lookup once per iteration instead of twice. Local variable access in Python is significantly faster than attribute access because it's a simple array index operation at the bytecode level (LOAD_FAST) versus a dictionary lookup (LOAD_ATTR).

**Key Performance Characteristics:**
The line profiler shows the optimization is particularly effective for the common case where both conditions need to be checked. The time spent on the two conditional checks decreased from 28% + 23.4% = 51.4% of total time to 22.4% + 15.3% = 37.7%, demonstrating measurable savings from the reduced attribute access overhead.

**Test Case Performance:**
- The optimization shows the most significant gains in **large-scale traversal scenarios** (1000-node chains), with 4-5% speedups in `test_long_chain_with_lambda_at_top_large_scale` and `test_long_chain_with_method_declaration_earlier_large_scale`
- Shorter chains show slight regressions (1-6% slower) in individual test cases, likely due to measurement noise and the overhead of the additional variable assignment being more noticeable in very short executions
- The overall **17% improvement** across the full workload confirms the optimization is beneficial when amortized across realistic usage patterns with varying tree depths

This optimization is particularly valuable when traversing deep AST structures, where the function may iterate many times before finding a lambda or method declaration, making the cumulative savings from reduced attribute access substantial.
---
 codeflash/languages/java/instrumentation.py | 5 +++--
 1 file changed, 3 insertions(+), 2 deletions(-)

diff --git a/codeflash/languages/java/instrumentation.py b/codeflash/languages/java/instrumentation.py
index 01ea24661..644300dd6 100644
--- a/codeflash/languages/java/instrumentation.py
+++ b/codeflash/languages/java/instrumentation.py
@@ -84,9 +84,10 @@ def _is_inside_lambda(node: Any) -> bool:
     """Check if a tree-sitter node is inside a lambda_expression."""
     current = node.parent
     while current is not None:
-        if current.type == "lambda_expression":
+        t = current.type
+        if t == "lambda_expression":
             return True
-        if current.type == "method_declaration":
+        if t == "method_declaration":
             return False
         current = current.parent
     return False