C/C++ Memory Optimization Expert - 31/07/2026 11:36 EDT
Budget: ₹600 – ₹1,500 INR
My current C/C++ codebase is functionally solid but far too heavy on RAM. I want it slimmed down without sacrificing stability, so your primary mission is to diagnose and trim memory consumption across the project.
Here’s the picture:
• The focus is squarely on C and C++ sources.
• I need concrete, measurable memory savings—ideally demonstrated through before-and-after profiling runs.
• Speed and readability improvements are welcome side-effects, but memory is the KPI that matters.
How we’ll work:
1. You begin with a deep dive using the tools you trust—Valgrind, AddressSanitizer, massif-visualizer, perf, or similar—to chart current heap/stack behaviour.
2. From those findings you’ll redesign data structures, apply smarter algorithms where they pay off, and refactor any OOP patterns that are needlessly bloating the footprint.
3. A lightweight Python script to automate regression benchmarks and leak checks should accompany the changes so I can replicate your results in one command.
Acceptance criteria:
• At least a 30 % reduction in peak memory usage in my standard test suite.
• Clean runs on Valgrind/ASan with zero leaks or invalid accesses.
• A short markdown report summarising every change, the rationale, and the profiling evidence.
Send over two or three lines about a project where you cut memory this dramatically before, and we’ll get started.
Here’s the picture:
• The focus is squarely on C and C++ sources.
• I need concrete, measurable memory savings—ideally demonstrated through before-and-after profiling runs.
• Speed and readability improvements are welcome side-effects, but memory is the KPI that matters.
How we’ll work:
1. You begin with a deep dive using the tools you trust—Valgrind, AddressSanitizer, massif-visualizer, perf, or similar—to chart current heap/stack behaviour.
2. From those findings you’ll redesign data structures, apply smarter algorithms where they pay off, and refactor any OOP patterns that are needlessly bloating the footprint.
3. A lightweight Python script to automate regression benchmarks and leak checks should accompany the changes so I can replicate your results in one command.
Acceptance criteria:
• At least a 30 % reduction in peak memory usage in my standard test suite.
• Clean runs on Valgrind/ASan with zero leaks or invalid accesses.
• A short markdown report summarising every change, the rationale, and the profiling evidence.
Send over two or three lines about a project where you cut memory this dramatically before, and we’ll get started.