The Garbage Collection Handbook The Art Of Automatic Memory Management Pdf Downloadl !!TOP!!
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The nearly universal adoption of garbage collection by modern programming languages makes a thorough understanding of this topic essential for any programmer. This authoritative handbook gives expert insight on how different collectors work as well as the various issues currently facing garbage collectors. Armed with this knowledge, programmers can confidently select and configure the many choices of garbage collectors.
V8 and Blink use mark-sweep-compact garbage collectors where a single garbage-collection cycle consists of three phases: (1) marking, where live objects are identified; (2) sweeping, where dead objects are released; and (3) compaction, where live objects are relocated to reduce memory fragmentation. During marking, the garbage collector finds all objects reachable from a defined set of root references, conceptually traversing an object graph, where the nodes of the graph are objects and the edges are fields of objects.
Assuming that the components cannot be unified, the cross-component reference cycles can lead to either (a) memory leaks when graphs involving cycles cannot be reclaimed by the components' garbage collectors, heavily impacting browser performance, or (b) premature collection of objects resulting in use-after-free security vulnerabilities and program crashes that put users at risk.
In computer science, garbage collection (GC) is a form of automatic memory management. The garbage collector attempts to reclaim memory which was allocated by the program, but is no longer referenced; such memory is called garbage. Garbage collection was invented by American computer scientist John McCarthy around 1959 to simplify manual memory management in Lisp.
Garbage collection relieves the programmer from doing manual memory management, where the programmer specifies what objects to de-allocate and return to the memory system and when to do so. Other, similar techniques include stack allocation, region inference, and memory ownership, and combinations thereof. Garbage collection may take a significant proportion of a program's total processing time, and affect performance as a result.
Resources other than memory, such as network sockets, database handles, windows, file descriptors, and device descriptors, are not typically handled by garbage collection, but rather by other methods (e.g. destructors). Some such methods de-allocate memory as well.
Many programming languages require garbage collection, either as part of the language specification (e.g., RPL, Java, C#, D, Go, and most scripting languages) or effectively for practical implementation (e.g., formal languages like lambda calculus). These are said to be garbage-collected languages. Other languages, such as C and C++, were designed for use with manual memory management, but have garbage-collected implementations available. Some languages, like Ada, Modula-3, and C++/CLI, allow both garbage collection and manual memory management to co-exist in the same application by using separate heaps for collected and manually managed objects. Still others, like D, are garbage-collected but allow the user to manually delete objects or even disable garbage collection entirely when speed is required.
GC uses computing resources to decide which memory to free. Therefore, the penalty for the convenience of not annotating object lifetime manually in the source code is overhead, which can impair program performance. A peer-reviewed paper from 2005 concluded that GC needs five times the memory to compensate for this overhead and to perform as fast as the same program using idealised explicit memory management. The comparison however is made to a program generated by inserting deallocation calls using an oracle, implemented by collecting traces from programs run under a profiler, and the program is only correct for one particular execution of the program. Interaction with memory hierarchy effects can make this overhead intolerable in circumstances that are hard to predict or to detect in routine testing. The impact on performance was given by Apple as a reason for not adopting garbage collection in iOS, despite it being the most desired feature.
Reference counting garbage collection is where each object has a count of the number of references to it. Garbage is identified by having a reference count of zero. An object's reference count is incremented when a reference to it is created, and decremented when a reference is destroyed. When the count reaches zero, the object's memory is reclaimed.
As with manual memory management, and unlike tracing garbage collection, reference counting guarantees that objects are destroyed as soon as their last reference is destroyed, and usually only accesses memory which is either in CPU caches, in objects to be freed, or directly pointed to by those, and thus tends to not have significant negative side effects on CPU cache and virtual memory operation. 2b1af7f3a8