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  • Why is insertion into my tree faster on sorted input than random input?

    - by Juliet
    Now I've always heard binary search trees are faster to build from randomly selected data than ordered data, simply because ordered data requires explicit rebalancing to keep the tree height at a minimum. Recently I implemented an immutable treap, a special kind of binary search tree which uses randomization to keep itself relatively balanced. In contrast to what I expected, I found I can consistently build a treap about 2x faster and generally better balanced from ordered data than unordered data -- and I have no idea why. Here's my treap implementation: http://pastebin.com/VAfSJRwZ And here's a test program: using System; using System.Collections.Generic; using System.Linq; using System.Diagnostics; namespace ConsoleApplication1 { class Program { static Random rnd = new Random(); const int ITERATION_COUNT = 20; static void Main(string[] args) { List<double> rndTimes = new List<double>(); List<double> orderedTimes = new List<double>(); rndTimes.Add(TimeIt(50, RandomInsert)); rndTimes.Add(TimeIt(100, RandomInsert)); rndTimes.Add(TimeIt(200, RandomInsert)); rndTimes.Add(TimeIt(400, RandomInsert)); rndTimes.Add(TimeIt(800, RandomInsert)); rndTimes.Add(TimeIt(1000, RandomInsert)); rndTimes.Add(TimeIt(2000, RandomInsert)); rndTimes.Add(TimeIt(4000, RandomInsert)); rndTimes.Add(TimeIt(8000, RandomInsert)); rndTimes.Add(TimeIt(16000, RandomInsert)); rndTimes.Add(TimeIt(32000, RandomInsert)); rndTimes.Add(TimeIt(64000, RandomInsert)); rndTimes.Add(TimeIt(128000, RandomInsert)); string rndTimesAsString = string.Join("\n", rndTimes.Select(x => x.ToString()).ToArray()); orderedTimes.Add(TimeIt(50, OrderedInsert)); orderedTimes.Add(TimeIt(100, OrderedInsert)); orderedTimes.Add(TimeIt(200, OrderedInsert)); orderedTimes.Add(TimeIt(400, OrderedInsert)); orderedTimes.Add(TimeIt(800, OrderedInsert)); orderedTimes.Add(TimeIt(1000, OrderedInsert)); orderedTimes.Add(TimeIt(2000, OrderedInsert)); orderedTimes.Add(TimeIt(4000, OrderedInsert)); orderedTimes.Add(TimeIt(8000, OrderedInsert)); orderedTimes.Add(TimeIt(16000, OrderedInsert)); orderedTimes.Add(TimeIt(32000, OrderedInsert)); orderedTimes.Add(TimeIt(64000, OrderedInsert)); orderedTimes.Add(TimeIt(128000, OrderedInsert)); string orderedTimesAsString = string.Join("\n", orderedTimes.Select(x => x.ToString()).ToArray()); Console.WriteLine("Done"); } static double TimeIt(int insertCount, Action<int> f) { Console.WriteLine("TimeIt({0}, {1})", insertCount, f.Method.Name); List<double> times = new List<double>(); for (int i = 0; i < ITERATION_COUNT; i++) { Stopwatch sw = Stopwatch.StartNew(); f(insertCount); sw.Stop(); times.Add(sw.Elapsed.TotalMilliseconds); } return times.Average(); } static void RandomInsert(int insertCount) { Treap<double> tree = new Treap<double>((x, y) => x.CompareTo(y)); for (int i = 0; i < insertCount; i++) { tree = tree.Insert(rnd.NextDouble()); } } static void OrderedInsert(int insertCount) { Treap<double> tree = new Treap<double>((x, y) => x.CompareTo(y)); for(int i = 0; i < insertCount; i++) { tree = tree.Insert(i + rnd.NextDouble()); } } } } And here's a chart comparing random and ordered insertion times in milliseconds: Insertions Random Ordered RandomTime / OrderedTime 50 1.031665 0.261585 3.94 100 0.544345 1.377155 0.4 200 1.268320 0.734570 1.73 400 2.765555 1.639150 1.69 800 6.089700 3.558350 1.71 1000 7.855150 4.704190 1.67 2000 17.852000 12.554065 1.42 4000 40.157340 22.474445 1.79 8000 88.375430 48.364265 1.83 16000 197.524000 109.082200 1.81 32000 459.277050 238.154405 1.93 64000 1055.508875 512.020310 2.06 128000 2481.694230 1107.980425 2.24 I don't see anything in the code which makes ordered input asymptotically faster than unordered input, so I'm at a loss to explain the difference. Why is it so much faster to build a treap from ordered input than random input?

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  • Deciphering a queer compiler warning about unsigned decimal constant

    - by Artagnon
    This large application has a memory pool library which uses a treap internally to store nodes of memory. The treap is implemented using cpp macros, and the complete file trp.h can be found here. I get the following compiler warning when I attempt to compile the application: warning: this decimal constant is unsigned only in ISO C90 By deleting portions of the macro code and using trial-and-error, I finally found the culprit: #define trp_prio_get(a_type, a_field, a_node) \ (2654435761*(uint32_t)(uintptr_t)(a_node)) I'm not sure what that strange number is doing there, but I assume it's there for a good reason, so I just want to leave it alone. I do want to fix the warning though- any idea why the compiler's saying that it's unsigned only in ISO C90? EDIT: I'm using gcc-4.1

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  • A balanced binary search tree which is also a heap

    - by saeedn
    I'm looking for a data structure where each element in it has two keys. With one of them the structure is a BST and looking at the other one, data structure is a heap. With a little search, I found a structure called Treap. It uses the heap property with a random distribution on heap keys to make the BST balanced! What I want is a Balanced BST, which can be also a heap. The BST in Treap could be unbalanced if I insert elements with heap Key in the order of my choice. Is there such a data structure?

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  • CodePlex Daily Summary for Sunday, July 14, 2013

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Add a few more known global names for improved ES6 compatibility update Nuget package to version 2.5 and automatically add the AjaxMin.targets to your project when you update the package...JSLint.NET: JSLint.NET 0.9.1 Beta: Version 0.9.1 Beta includes: JSLint.NET Console: Console help available using the /? switch (or no arguments). See the Console Options page for more. JSLint.NET for Visual Studio: Support linked JSLintNet.json file. More about this file on the JSLint.NET Settings page. Hide un-implemented menu items. Prefix JSLint errors in the task list. JSLint.NET Core: Allow ignoring of individual files in JSLintNet.json.TypePipe: 1.15.2.0 (.NET 4.5): This is build 1.15.2.0 of the TypePipe for .NET 4.5. Find the complete release notes for the build here: Release Notes.re-linq: 1.15.2.0 (.NET 4.5): This is build 1.15.2.0 of re-linq for .NET 4.5. 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