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  • How to determine item at a index in pattern

    - by el.gringogrande
    I have the following elements in a list/array a1,a2,a3 and these elements are used to build another list in a predictable pattern example a1,a1,a2,a2,a3,a3,a1,a1,a2,a2,a3,a3... The pattern may change but I will always know how many times each element repeats and all elements repeats the same number of times. And the elements always show up in the same order. so another pattern might be a1,a1,a1,a2,a2,a2,a3,a3,a3,a1,a1,a1,a2,a2,a2,a3,a3,a3... or a1,a2,a3,a1,a2,a3 it will never be a2,a2,a1,a1,a3,a3... or a1,a2,a3,a2,a3,a1 etc How I determine what element is at any index in the list?

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  • How do LL(*) parsers work?

    - by freezer878
    I cannot find any complete description about LL(*) parser, such as ANTLR, on Internet. I'm wondering what is the difference between an LL(k) parser and an LL(*) one and why they can't support left-recusrive grammars despite their flexibility.

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  • Given a word, how do I get the list of all words, that differ by one letter?

    - by user187809
    Let's say I have the word "CAT". These words differ from "CAT" by one letter (not the full list) CUT CAP PAT FAT COT etc. Is there an elegant way to generate this? Obviously, one way to do it is through brute force. pseduo code: while (0 to length of word) while (A to Z) replace one letter at a time, and check if the resulting word is a valid word If I had a 10 letter word, the loop would run 26 * 10 = 260 times. Is there a better, elegant way to do this?

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  • Finding patterns in Puzzle games.

    - by José Joel.
    I was wondering, which are the most commonly used algorithms applied to finding patterns in puzzle games conformed by grids of cells. I know that depends of many factors, like the kind of patterns You want to detect, or the rules of the game...but I wanted to know which are the most commonly used algorithms in that kind of problems... For example, games like columns, bejeweled, even tetris. I also want to know if detecting patterns by "brute force" ( like , scanning all the grid trying to find three adyacent cells of the same color ) is significantly worst that using particular algorithms in very small grids, like 4 X 4 for example ( and again, I know that depends of the kind of game and rules ...) Which structures are commonly used in this kind of games ?

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  • How do I recursively define a Hash in Ruby from supplied arguments?

    - by Sarah Beckham
    This snippet of code populates an @options hash. values is an Array which contains zero or more heterogeneous items. If you invoke populate with arguments that are Hash entries, it uses the value you specify for each entry to assume a default value. def populate(*args) args.each do |a| values = nil if (a.kind_of? Hash) # Converts {:k => "v"} to `a = :k, values = "v"` a, values = a.to_a.first end @options[:"#{a}"] ||= values ||= {} end end What I'd like to do is change populate such that it recursively populates @options. There is a special case: if the values it's about to populate a key with are an Array consisting entirely of (1) Symbols or (2) Hashes whose keys are Symbols (or some combination of the two), then they should be treated as subkeys rather than the values associated with that key, and the same logic used to evaluate the original populate arguments should be recursively re-applied. That was a little hard to put into words, so I've written some test cases. Here are some test cases and the expected value of @options afterwards: populate :a => @options is {:a => {}} populate :a => 42 => @options is {:a => 42} populate :a, :b, :c => @options is {:a => {}, :b => {}, :c => {}} populate :a, :b => "apples", :c => @options is {:a => {}, :b => "apples", :c => {}} populate :a => :b => @options is {:a => :b} # Because [:b] is an Array consisting entirely of Symbols or # Hashes whose keys are Symbols, we assume that :b is a subkey # of @options[:a], rather than the value for @options[:a]. populate :a => [:b] => @options is {:a => {:b => {}}} populate :a => [:b, :c => :d] => @options is {:a => {:b => {}, :c => :d}} populate :a => [:a, :b, :c] => @options is {:a => {:a => {}, :b => {}, :c => {}}} populate :a => [:a, :b, "c"] => @options is {:a => [:a, :b, "c"]} populate :a => [:one], :b => [:two, :three => "four"] => @options is {:a => :one, :b => {:two => {}, :three => "four"}} populate :a => [:one], :b => [:two => {:four => :five}, :three => "four"] => @options is {:a => :one, :b => { :two => { :four => :five } }, :three => "four" } } It is acceptable if the signature of populate needs to change to accommodate some kind of recursive version. There is no limit to the amount of nesting that could theoretically happen. Any thoughts on how I might pull this off?

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  • Big-O for Eight Year Olds?

    - by Jason Baker
    I'm asking more about what this means to my code. I understand the concepts mathematically, I just have a hard time wrapping my head around what they mean conceptually. For example, if one were to perform an O(1) operation on a data structure, I understand that the amount of operations it has to perform won't grow because there are more items. And an O(n) operation would mean that you would perform a set of operations on each element. Could somebody fill in the blanks here? Like what exactly would an O(n^2) operation do? And what the heck does it mean if an operation is O(n log(n))? And does somebody have to smoke crack to write an O(x!)?

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  • O(log N) == O(1) - Why not?

    - by phoku
    Whenever I consider algorithms/data structures I tend to replace the log(N) parts by constants. Oh, I know log(N) diverges - but does it matter in real world applications? log(infinity) < 100 for all practical purposes. I am really curious for real world examples where this doesn't hold. To clarify: I understand O(f(N)) I am curious about real world examples where the asymptotic behaviour matters more than the constants of the actual performance. If log(N) can be replaced by a constant it still can be replaced by a constant in O( N log N). This question is for the sake of (a) entertainment and (b) to gather arguments to use if I run (again) into a controversy about the performance of a design.

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  • Faster way to compare two sets of points in N-dimensional space?

    - by Amit
    List1 contains a high number (~7^10) of N-dimensional points (N <=10), List2 contains the same or fewer number of N-dimensional points (N <=10). My task is this: I want to check which point in List2 is closest (euclidean distance) to a point in List1 for every point in List1 and subsequently perform some operation on it. I have been doing it the simple- the nested loop way when I didn't have more than 50 points in List1, but with 7^10 points, this obviously takes up a lot of time. What is the fastest way to do this? Any concepts from Computational Geometry might help?

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  • Find recipes that can be cooked from provided ingridients

    - by skaurus
    Sorry for bad English :( Suppose i can preliminary organize recipes and ingredients data in any way. How can i effectively conduct search of recipes by user-provided ingredients, preferably sorted by max match - so, first going recipes that use maximum of provided ingridients and do not contain any other ingrs, after them recipes that uses less of provided set and still not any other ingrs, after them recipes with minimum additional requirements and so on? All i can think about is represent recipe ingridients like bitmasks, and compare required bitmask with all recipes, but it is obviously a bad way to go. And related things like Levenstein distance i don't see how to use here. I believe it should be quite common task...

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  • Effective way to calculate a similarity percentage between data sets

    - by UltraVi01
    I am currently working with User objects -- each of which have many Goal objects. The Goal objects are not User specific, that is, Users can share the same Goal. I am attempting to fashion a way to calculate a "similarity percentage" between two Users... (i.e., taking into account how many Goals they share as well as how many Goals they do not share) Does anyone have experience with this type of situation? I am using Grails with Mysql if that is helpful. Thanks

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  • Space requirements of a merge-sort

    - by Arkaitz Jimenez
    I'm trying to understand the space requirements for a Mergesort, O(n). I see that time requirements are basically, amount of levels(logn) * merge(n) so that makes (n log n). Now, we are still allocating n per level, in 2 different arrays, left and right. I do understand that the key here is that when the recursive functions return the space gets deallocated, but I'm not seeing it too obvious. Besides, all the info I find, just states space required is O(n) but don't explain it. Any hint? function merge_sort(m) if length(m) = 1 return m var list left, right, result var integer middle = length(m) / 2 for each x in m up to middle add x to left for each x in m after middle add x to right left = merge_sort(left) right = merge_sort(right) result = merge(left, right) return result

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  • Recursion - Ship Battle

    - by rgorrosini
    I'm trying to write a little ship battle game in java. It is 100% academic, I made it to practice recursion, so... I want to use it instead of iteration, even if it's simpler and more efficient in most some cases. Let's get down to business. These are the rules: Ships are 1, 2 or 3 cells wide and are placed horizontally only. Water is represented with 0, non-hit ship cells are 1, hit ship cells are 2 and sunken ships have all it's cells in 3. With those rules set, I'm using the following array for testing: int[][] board = new int[][] { {0, 1, 2, 0, 1, 0}, {0, 0, 1, 1, 1, 0}, {0, 3, 0, 0, 0, 0}, {0, 0, 2, 1, 2, 0}, {0, 0, 0, 1, 1, 1}, }; It works pretty good so far, and to make it more user-friendly I would like to add a couple of reports. these are the methods I need for them: Given the matrix, return the amount of ships in it. Same as a), but separating them by state (amount of non-hit ships, hit and sunken ones). I will need a hand with those reports, and I would like to get some ideas. Remember it must be done using recursion, I want to understand this, and the only way to go is practice! Thanks a lot for your time and patience :).

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  • Unit Testing - Algorithm or Sample based ?

    - by ohadsc
    Say I'm trying to test a simple Set class public IntSet : IEnumerable<int> { Add(int i) {...} //IEnumerable implementation... } And suppose I'm trying to test that no duplicate values can exist in the set. My first option is to insert some sample data into the set, and test for duplicates using my knowledge of the data I used, for example: //OPTION 1 void InsertDuplicateValues_OnlyOneInstancePerValueShouldBeInTheSet() { var set = new IntSet(); //3 will be added 3 times var values = new List<int> {1, 2, 3, 3, 3, 4, 5}; foreach (int i in values) set.Add(i); //I know 3 is the only candidate to appear multiple times int counter = 0; foreach (int i in set) if (i == 3) counter++; Assert.AreEqual(1, counter); } My second option is to test for my condition generically: //OPTION 2 void InsertDuplicateValues_OnlyOneInstancePerValueShouldBeInTheSet() { var set = new IntSet(); //The following could even be a list of random numbers with a duplicate var values = new List<int> { 1, 2, 3, 3, 3, 4, 5}; foreach (int i in values) set.Add(i); //I am not using my prior knowledge of the sample data //the following line would work for any data CollectionAssert.AreEquivalent(new HashSet<int>(values), set); } Of course, in this example, I conveniently have a set implementation to check against, as well as code to compare collections (CollectionAssert). But what if I didn't have either ? This is the situation when you are testing your real life custom business logic. Granted, testing for expected conditions generically covers more cases - but it becomes very similar to implementing the logic again (which is both tedious and useless - you can't use the same code to check itself!). Basically I'm asking whether my tests should look like "insert 1, 2, 3 then check something about 3" or "insert 1, 2, 3 and check for something in general" EDIT - To help me understand, please state in your answer if you prefer OPTION 1 or OPTION 2 (or neither, or that it depends on the case, etc )

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  • Purpose of IF, ELSE, FOR macros ?

    - by psihodelia
    I have a source code of a library which has a lot of strange IF, ELSE, FOR, etc. macros for all common C-keywords instead of using just usual if,else,for,while keywords. These macros are defined like this: #define IF( a) if( increment_if(), a) where increment_if() function is defined so: static __inline void increment_if( void) { // If the "IF" operator comes just after an "ELSE", its counter // must not be incremented. ... //implementation } I don't really understand, what is the purpose of such macros? This library is for a real-time application and I suppose that using such macros must slow-down an application.

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  • arbitrary vire connection / search and replace

    - by fatai
    input :["vire_connection",[1, 2, [ 3, [ 4, "connect"]]], ["connect", [3 , 5] ] ] output:["vire_connection",[ 1, 2, [ 3, [ 4, [ 3, 5 ] ] ] ] ], [ [ 3 , 5] ] ] after connection ( simply copying [3,5] to other wanted position ) , remove connect word input :["vire_connection", [ [ [ ["connect", [ 3, 4 ] ] ] ] ], [ 2, "connect"]] output :["vire_connection",[[[[[3,4]]]]], [ 2, [ 3 , 4 ]]] after connection ( simply copying [3,4] to other wanted position ) , remove connect word how can I do ?

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  • What Software Engineering Areas should be stressed upon while Interviewing Candidate for Fulltime So

    - by Rachel
    Hi, This question is somewhat related to other posts which I found on Stackoverflow but not exactly and so am prompted to ask about it. I know we must ask for Data-Structures and Algorithms but what specific data-structures or Algorithms or other CS Concepts should be asked while interviewing Sr. Software Engineering Fulltime Position as compared with Software Engineering Position. Thanks.

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  • How can I represent a line of music notes in a way that allows fast insertion at any index?

    - by chairbender
    For "fun", and to learn functional programming, I'm developing a program in Clojure that does algorithmic composition using ideas from this theory of music called "Westergaardian Theory". It generates lines of music (where a line is just a single staff consisting of a sequence of notes, each with pitches and durations). It basically works like this: Start with a line consisting of three notes (the specifics of how these are chosen are not important). Randomly perform one of several "operations" on this line. The operation picks randomly from all pairs of adjacent notes that meet a certain criteria (for each pair, the criteria only depends on the pair and is independent of the other notes in the line). It inserts 1 or several notes (depending on the operation) between the chosen pair. Each operation has its own unique criteria. Continue randomly performing these operations on the line until the line is the desired length. The issue I've run into is that my implementation of this is quite slow, and I suspect it could be made faster. I'm new to Clojure and functional programming in general (though I'm experienced with OO), so I'm hoping someone with more experience can point out if I'm not thinking in a functional paradigm or missing out on some FP technique. My current implementation is that each line is a vector containing maps. Each map has a :note and a :dur. :note's value is a keyword representing a musical note like :A4 or :C#3. :dur's value is a fraction, representing the duration of the note (1 is a whole note, 1/4 is a quarter note, etc...). So, for example, a line representing the C major scale starting on C3 would look like this: [ {:note :C3 :dur 1} {:note :D3 :dur 1} {:note :E3 :dur 1} {:note :F3 :dur 1} {:note :G3 :dur 1} {:note :A4 :dur 1} {:note :B4 :dur 1} ] This is a problematic representation because there's not really a quick way to insert into an arbitrary index of a vector. But insertion is the most frequently performed operation on these lines. My current terrible function for inserting notes into a line basically splits the vector using subvec at the point of insertion, uses conj to join the first part + notes + last part, then uses flatten and vec to make them all be in a one-dimensional vector. For example if I want to insert C3 and D3 into the the C major scale at index 3 (where the F3 is), it would do this (I'll use the note name in place of the :note and :dur maps): (conj [C3 D3 E3] [C3 D3] [F3 G3 A4 B4]), which creates [C3 D3 E3 [C3 D3] [F3 G3 A4 B4]] (vec (flatten previous-vector)) which gives [C3 D3 E3 C3 D3 F3 G3 A4 B4] The run time of that is O(n), AFAIK. I'm looking for a way to make this insertion faster. I've searched for information on Clojure data structures that have fast insertion but haven't found anything that would work. I found "finger trees" but they only allow fast insertion at the start or end of the list. Edit: I split this into two questions. The other part is here.

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  • help implementing algorithm

    - by davit-datuashvili
    http://en.wikipedia.org/wiki/All_nearest_smaller_values this is site of the problem and here is my code but i have some trouble to implement it import java.util.*; public class stack{ public static void main(String[]args){ int x[]=new int[]{ 0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15 }; Stack<Integer> st=new Stack<Integer>(); for (int a:x){ while (!st.empty() && st.pop()>=a){ System.out.println( st.pop()); if (st.empty()){ break; } else{ st.push(a); } } } } } and here is pseudo code from site S = new empty stack data structure for x in the input sequence: while S is nonempty and the top element of S is greater than or equal to x: pop S if S is empty: x has no preceding smaller value else: the nearest smaller value to x is the top element of S push x onto S

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  • help implementing All Nearest Smaller Values algorithm

    - by davit-datuashvili
    http://en.wikipedia.org/wiki/All_nearest_smaller_values this is site of the problem and here is my code but i have some trouble to implement it import java.util.*; public class stack{ public static void main(String[]args){ int x[]=new int[]{ 0, 8, 4, 12, 2, 10, 6, 14, 1, 9, 5, 13, 3, 11, 7, 15 }; Stack<Integer> st=new Stack<Integer>(); for (int a:x){ while (!st.empty() && st.pop()>=a){ System.out.println( st.pop()); if (st.empty()){ break; } else{ st.push(a); } } } } } and here is pseudo code from site S = new empty stack data structure for x in the input sequence: while S is nonempty and the top element of S is greater than or equal to x: pop S if S is empty: x has no preceding smaller value else: the nearest smaller value to x is the top element of S push x onto S

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  • Time complexity of a powerset generating function

    - by Lirik
    I'm trying to figure out the time complexity of a function that I wrote (it generates a power set for a given string): public static HashSet<string> GeneratePowerSet(string input) { HashSet<string> powerSet = new HashSet<string>(); if (string.IsNullOrEmpty(input)) return powerSet; int powSetSize = (int)Math.Pow(2.0, (double)input.Length); // Start at 1 to skip the empty string case for (int i = 1; i < powSetSize; i++) { string str = Convert.ToString(i, 2); string pset = str; for (int k = str.Length; k < input.Length; k++) { pset = "0" + pset; } string set = string.Empty; for (int j = 0; j < pset.Length; j++) { if (pset[j] == '1') { set = string.Concat(set, input[j].ToString()); } } powerSet.Add(set); } return powerSet; } So my attempt is this: let the size of the input string be n in the outer for loop, must iterate 2^n times (because the set size is 2^n). in the inner for loop, we must iterate 2*n times (at worst). 1. So Big-O would be O((2^n)*n) (since we drop the constant 2)... is that correct? And n*(2^n) is worse than n^2. if n = 4 then (4*(2^4)) = 64 (4^2) = 16 if n = 100 then (10*(2^10)) = 10240 (10^2) = 100 2. Is there a faster way to generate a power set, or is this about optimal?

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  • Generating different randoms valid for a day on different independent devices?

    - by Pentium10
    Let me describe the system. There are several mobile devices, each independent from each other, and they are generating content for the same record id. I want to avoid generating the same content for the same record on different devices, for this I though I would use a random and make it so too cluster the content pool based on these randoms. Suppose you have choices from 1 to 100. Day 1 Device#1 will choose for the record#33 between 1-10 Device#2 will choose for the record#33 between 40-50 Device#3 will choose for the record#33 between 50-60 Device#1 will choose for the record#55 between 40-50 Device#2 will choose for the record#55 between 1-10 Device#3 will choose for the record#55 between 10-20 Device#1 will choose for the record#11 between 1-10 Device#2 will choose for the record#22 between 1-10 Device#3 will choose for the record#99 between 1-10 Day 2 Device#1 will choose for the record#33 between 90-100 Device#2 will choose for the record#33 between 1-10 Device#3 will choose for the record#33 between 50-60 They don't have access to a central server. Data available for each of them: IMEI (unique per mobile) Date of today (same on all devices) Record id (same on all devices) What do you think, how is it possible? ps. tags can be edited

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  • Creating an adjacency List for DFS

    - by user200081
    I'm having trouble creating a Depth First Search for my program. So far I have a class of edges and a class of regions. I want to store all the connected edges inside one node of my region. I can tell if something is connected by the getKey() function I have already implemented. If two edges have the same key, then they are connected. For the next region, I want to store another set of connected edges inside that region, etc etc. However, I am not fully understanding DFS and I'm having some trouble implementing it. I'm not sure when/where to call DFS again. Any help would be appreciated! class edge { private: int source, destination, length; int key; edge *next; public: getKey(){ return key; } } class region { edge *data; edge *next; region() { data = new edge(); next = NULL; } }; void runDFS(int i, edge **edge, int a) { region *head = new region(); aa[i]->visited == true;//mark the first vertex as true for(int v = 0; v < a; v++) { if(tem->edge[i].getKey() == tem->edge[v].getKey()) //if the edges of the vertex have the same root { if(head->data == NULL) { head->data = aa[i]; head->data->next == NULL; } //create an edge if(head->data) { head->data->next = aa[i]; head->data->next->next == NULL; }//if there is already a node connected to ti } if(aa[v]->visited == false) runDFS(v, edge, a); //call the DFS again } //for loop }

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