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Whereas Queue<T> operates a FIFO order, Stack<T> operates a last in, first out (LIFO) order. Looking at this from a queuing perspective, it seems like the height of unfairness latecomers get priority over those who arrived early. However, there are some situations in which this topsy-turvy ordering can make sense. A performance characteristic of most computers is that they tend to be able to work faster with data they ve processed recently than with data they ve not touched lately. CPUs have caches that provide faster access to data than a computer s main memory can support, and these caches typically operate a policy where recently used data is more likely to stay in the cache than data that has not been touched recently. If you re writing a server-side application, you may consider throughput to be more important than fairness the total rate at which you process work may matter more than how long any individual work item takes to complete. In this case, a LIFO order may make the most sense work items that were only just put into a queue are much more likely to still live in the CPU s cache than those that were queued up ages ago,
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and so you ll get better throughput during high loads if you process newly arrived items first. Items that have sat in the queue for longer will just have to wait for a lull. Like Queue<T>, Stack<T> offers a method to add an item, and one to remove it. It calls these Push and Pop, respectively. They are very similar to the queue s Enqueue and Dequeue, except they both work off the same end of the list. (You could get the same effect using a LinkedList, and always calling AddFirst and RemoveFirst.) A stack could also be useful for managing navigation history. The Back button in a browser works in LIFO order the first page it shows you is the last one you visited. (And if you want a Forward button, you could define a second stack each time the user goes Back, Push the current page onto the Forward stack. Then if the user clicks Forward, Pop a page from the Forward stack, and Push the current page onto the Back stack.)
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The .NET Framework class library provides various useful collection classes. We saw List<T> in an earlier chapter, which provides a simple resizable linear list of items. Dictionaries store entries by associating them with keys, providing fast key-based lookup. HashSet<T> and SortedSet<T> manage sets of unique items, with optional ordering. Queues, linked lists, and stacks each manage a queue of items, offering various strategies for how the order of addition relates to the order in which items come out of the queue.
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10 is all about strings. A bit late, you might think: we ve had about nine chapters of string-based action already! Well, yes, you d be right. That s not terribly surprising, though: text is probably the single most important means an application has of communicating with its users. That is especially true as we haven t introduced any graphical frameworks yet. I suppose we could have beeped the system speaker in Morse, although even that can be considered a text-based operation. Even with a graphical UI framework where we have pictures and buttons and graphs and sounds, they almost always have textual labels, descriptions, comments, or tool tips. Users who have difficulty reading (perhaps because they have a low-vision condition) may have that text transformed into sound by accessibility tools, but the application is still processing text strings under the covers. Even when we are dealing with integers or doubles internally within an algorithm, there comes a time when we need to represent them to humans, and preferably in a way that is meaningful to us. We usually do that (at least in part) by converting them into strings of one form or another. Strings are surprisingly complex and sophisticated entities, so we re going to take some time to explore their properties in this chapter. First, we ll look at what we re really doing when we initialize a literal string. Then, we ll see a couple of techniques which let us convert from other types to a string representation and how we can control the formatting of that conversion. Next, we ll look at various different techniques we can use to process a string. This will include composition, splitting, searching and replacing content, and what it means to compare strings of various kinds. Finally, we will look at how .NET represents strings internally, how that differs from other representations in popular use in the world, and how we can convert between those representations by using an Encoding.
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