I knew the basics but fumbled when they pushed on specific algorithms like mark-and-sweep vs reference counting.
Start by defining garbage collection as automatic memory reclamation, then explain the core algorithms (reference counting, mark-and-sweep, generational) and how they trade off throughput, pause times, and memory overhead. Finally, connect it to real-world impact in languages like Java or Python, and discuss how you'd tune or choose a GC strategy for a system.
Pro tip: Mention that understanding GC is crucial for diagnosing production issues like memory leaks and latency spikes, and that you've used tools like GC logs or profilers to optimize performance. This shows hands-on experience beyond textbook knowledge.
Explain that GC automatically reclaims memory occupied by objects no longer in use, preventing manual memory management errors like leaks and dangling pointers.
Outline key techniques: reference counting (simple but cycle-prone), mark-and-sweep (traces reachable objects), and generational (exploits object lifetimes) with brief pros and cons.
Highlight trade-offs: throughput vs. pause times, memory overhead vs. collection frequency, and how different collectors (e.g., G1, CMS) target specific goals.
Give examples: Java's JVM GC, Python's reference counting + cycle detector, Go's concurrent collector, and how each affects application design.
Summarize that GC choice impacts performance, scalability, and reliability, and mention tools (GC logs, profilers) for monitoring and tuning.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.