Efficient substring searching There are many times when programmers need to search for a substring, for example when parsing text. This is commonly referred to as searching for a needle (substring) in a haystack (the string to search in). The most straightforward way to do this is by using search functions that your language provides: C: strchr()/memchr(), strstr()/memmem()C++: string::find()Ruby: String#index or regular expressionsPython: string.find() or regular expressions However those functions are usually implemented in a naive way. They usually go through every index in the haystack and try to compare the substring at that index with the given needle. In this article we’ll examine smarter algorithms, in particular Boyer-Moore and its variants. Before we move on, it should be noted that Python’s string.find(), Ruby regular expressions and glibc’s implementation of memmem() actually can use smarter algorithms when conditions are right, but that is besides the main point of this article. Smarter algorithms The code
Damn Cool Algorithms: Levenshtein Automata Posted by Nick Johnson | Filed under python, coding, tech, damn-cool-algorithms In a previous Damn Cool Algorithms post, I talked about BK-trees, a clever indexing structure that makes it possible to search for fuzzy matches on a text string based on Levenshtein distance - or any other metric that obeys the triangle inequality. Today, I'm going to describe an alternative approach, which makes it possible to do fuzzy text search in a regular index: Levenshtein automata. Introduction The basic insight behind Levenshtein automata is that it's possible to construct a Finite state automaton that recognizes exactly the set of strings within a given Levenshtein distance of a target word. We can then feed in any word, and the automaton will accept or reject it based on whether the Levenshtein distance to the target word is at most the distance specified when we constructed the automaton. Of course, if that were the only benefit of Levenshtein automata, this would be a short article. Indexing
PLIB: A Portable Games Library. OLAP cubes, outdated BI technology? As businesses demand that more employees have access to the benefits of expansive, real-time data analysis, it seems that the latency and complexity associated with OLAP cubes will soon see them rendered to the pages of technological history by a new breed of operational Business Intelligence (BI) tools. – Tools that cater for pervasive and virtually instantaneous data analysis and reporting through in-memory analytics. But they’ll survive; for now. What do OLAP cubes offer? The ability of OLAP cubes to facilitate multifaceted data analysis in response to complex business queries, will see them maintain some degree of usefulness, as businesses accumulate increasingly large data volumes of increasing complexity. Because OLAP cubes can be made up of more than three dimensions (hypercube), in-depth analysis is enabled, allowing users to gain comprehensive and valuable business insights. OLAP cubes can also perform data analysis without internet connectivity. In-memory analytics
ArsDigita University Curriculum About the Curriculum The curriculum was modeled on the undergraduate CS program at MIT. Several of the courses were straightforward adoptions of MIT courses. A few were specifically designed for the program, which was roughly in line with the ACM's 2001 Model Curricula for Computing. The process of accreditation (ACM or CSAB/ABET) would have been pursued if the program had continued. Courses Math for Computer Science - Tara Holm Structure and Interpretation of Computer Programs - Holly Yanco Discrete Math - Shai Simonson How Computers Work - Gill Pratt Object-oriented Program Design - David Goddeau Algorithms - Shai Simonson Systems - Luis Rodriguez Web Applications - Philip Greenspun Theory of Computation - Shai Simonson Artificial Intelligence - Patrick Winston Unix Workshop Database Management Systems - Ravi Jasuja Applied Probability - Tina Kapur Course of study
Create UML diagrams online in seconds, no special tools needed. Actor Actor and Use Case Notes Many Use Cases Actor Inheritance Multiple Actors And Inheritance <<Extends>> <<Includes>> <img src=" Registration)" > Meaty Example Create Your Own >> Damn Cool Algorithms, Part 1: BK-Trees - Nick's Blog - Vimperator Posted by Nick Johnson | Filed under coding, tech, damn-cool-algorithms This is the first post in (hopefully) a series of posts on Damn Cool Algorithms - essentially, any algorithm I think is really Damn Cool, particularly if it's simple but non-obvious. BK-Trees, or Burkhard-Keller Trees are a tree-based data structure engineered for quickly finding near-matches to a string, for example, as used by a spelling checker, or when doing a 'fuzzy' search for a term. The aim is to return, for example, "seek" and "peek" if I search for "aeek". BK-Trees were first proposed by Burkhard and Keller in 1973, in their paper "Some approaches to best match file searching". Before we can define BK-Trees, we need to define a couple of preliminaries. Now we can make a particularly useful observation about the Levenshtein Distance: It forms a Metric Space. These three criteria, basic as they are, are all that's required for something such as the Levenshtein Distance to qualify as a Metric Space.
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Visualising sorting algorithms This is another one of my rare technical posts, as opposed to news of which countries I've been visiting. If you're in computer science, you've probably seen an animation of sorting algorithms, maybe heard a rendition, or seen a visual representation. I have, somewhat by accident, discovered a different way to visualise a sorting algorithm: plot points for memory accesses, with address on the X axis and time (counted by accesses) on the Y axis, and different colours for reads and writes. It produces some rather pretty pictures. Ye olde bubblesort. Insertion sort - the version optimized for mostly sorted content. Shellsort, clearly showing the phases. Selection sort: Heapsort: the solid lines at the top are the heap-building phase, while the rest shows the extraction. Divide-and-conquer algorithms have a pretty fractal nature. Mergesort: this diagram is twice as wide as the others because it uses temporary storage on the right.
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Software Development AntiPatterns Good software structure is essential for system extension and maintenance. Software development is a chaotic activity, therefore the implemented structure of systems tends to stray from the planned structure as determined by architecture, analysis, and design. Software refactoring is an effective approach for improving software structure. The resulting structure does not have to resemble the original planned structure. The structure changes because programmers learn constraints and approaches that alter the context of the coded solutions. For example, the solution for the Spaghetti Code AntiPattern defines a software development process that incorporates refactoring. Development AntiPatterns utilize various formal and informal refactoring approaches. The BlobProcedural-style design leads to one object with a lion’s share of the responsibilities, while most other objects only hold data or execute simple processes. Read next All of the AntiPatterns are compiled there. Learn more
Swiftless' Game Programming Site Google Code Jam - Rotate It’s time for some basic finger exercise. The Google Code Jam Rotate is very trivial, so relax and fire up your IDE. I was a bit lazy, so there is no reading of the input sets, just a two-dimensional array and two functions Rotating As the Google solution pointed out, there is actually no need to really rotate the 2dim array. Just push everything to the right, as if gravity would be to the right. So here is the “gravity from the right” code public static void fakeRotate ( char [][] board ) { for ( int i = 0 ; i < N ; i ++) { for ( int j = N - 1 ; j >= 0 ; j --) { if ( board [ i ][ j ] ! // push to right int m = 1 ; while (( j + m ) < N && board [ i ][ j + m ] == '.' ) { board [ i ][ j + m ] = board [ i ][ j + ( m - 1 )]; board [ i ][ j + ( m - 1 )] = ' m ++; Checking for a winner Now we have everything ready to look for a winner. Progressing this way, I only need to check in four directions. public static void checkForWinner ( char [][] board ) { boolean redWins = false ; if ( board [ i ][ j ] !