memscope 0.1.2

Analyze and simulate dynamic memory usage in C/C++ code

memscope

🔍 Analyze and visualize memory allocation and release operations in C/C++ code.

🚀 Features

• Detects malloc, calloc, realloc, new, delete, free
• Counts allocation vs. deallocation operations
• Detects potential memory leaks
• Visualizes heap behavior over time using Matplotlib

📦 Installation

bash pip install memscope

Or from source: git clone https://github.com/MiriKanner/memscope cd memscope pip install -e

🧠 Quick Start

Analyze C/C++ Source Code

from memscope import analyze_source

result = analyze_source("examples/sample.c") print(result)

example output:

{ "allocs": 2, "frees": 1, "unfreed_allocations": 1, "lines": { "alloc": [4, 7], "free": [9] } }

Visualize Memory Operations

from memscope.visualizer import plot_memory_timeline, plot_memory_bars

events = [ {"step": 1, "allocated": 128, "freed": 0}, {"step": 2, "allocated": 256, "freed": 64}, {"step": 3, "allocated": 0, "freed": 320}, ]

plot_memory_timeline(events) plot_memory_bars(events)

🧩 API Reference

analyze_source(filepath: str) -> dict

Analyze a C/C++ source file and detect allocation/deallocation operations.

Parameters

---filepath: path to .c or .cpp file.

Returns: { "allocs": int, "frees": int, "unfreed_allocations": int, "lines": {"alloc": list[int], "free": list[int]} }

plot_memory_timeline(events: list[dict])

Plots total heap size over time.

plot_memory_timeline([ {"step": 1, "allocated": 128, "freed": 0}, {"step": 2, "allocated": 0, "freed": 128}, ])

plot_memory_bars(events: list[dict])

Plots allocation (green) and free (red) deltas.

plot_memory_bars([ {"step": 1, "allocated": 200, "freed": 0}, {"step": 2, "allocated": 0, "freed": 100}, ])