Seven Common GC Algorithms: Principles, Comparisons, and Optimizations

This article provides a comprehensive overview of seven common Garbage Collection (GC) algorithms, serving as a learning framework for understanding GC fundamentals. The content covers: (1) The necessity of GC - explaining memory leaks, dangling pointers, and incorrect memory release issues that arise without automatic garbage collection; (2) Basic GC terminology including objects, pointers, live objects, dead objects, heap, and root; (3) Four evaluation criteria for GC algorithms: throughput, maximum pause time, heap usage efficiency, and cache locality.

The seven algorithms detailed include: GC Mark-Sweep (with marking and sweeping phases, advantages of simplicity but缺点 of fragmentation); Reference Counting (immediate garbage reclamation but suffers from circular reference issues); GC Copying (excellent throughput but only uses half the heap); GC Mark-Compact (combines mark-sweep with compaction, using three-pass heap scanning); Conservative GC (cannot move objects, works with languages that don't support precise GC); Generational GC (exploits the observation that most objects die young, using minor and major GC); and Incremental GC/Tri-color Marking (alternates between application and GC to reduce maximum pause time, using write barriers).

Each algorithm is analyzed with its working principles, execution processes, advantages, disadvantages, and optimization approaches. The article emphasizes that there is no perfect algorithm in engineering—only the most suitable solution for specific business scenarios.