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  • Can Foswiki be used as a distributed Redmine replacement? [closed]

    - by Tobias Kienzler
    I am quite familiar with and love using git, among other reasons due to its distributed nature. Now I'd like to set up some similarly distributed (FOSS) Project Management software with features similar to what Redmine offers, such as Issue & time tracking, milestones Gantt charts, calendar git integration, maybe some automatic linking of commits and issues Wiki (preferably with Mathjax support) Forum, news, notifications Multiple Projects However, I am looking for a solution that does not require a permanently accesible server, i.e. like in git, each user should have their own copy which can be easily synchronized with others. However it should be possible to not have a copy of every Project on every machine. Since trac uses multiple instances for multiple projects anyway, I was considering using that, but I neither know how well it adapts to simply giting the database itself (which would be be easiest way to handle the distribution due to git being used anyway), nor does it include all of Redmine's feature. After checking http://www.wikimatrix.org for Wikis with integrated tracking system and RCS support, and filtering out seemingly stale project, the choices basically boil down to Foswiki, TWiki and Ikiwiki. The latter doesn't seem to offer as many usability features, and in the TWiki vs Foswiki issue I tend to the latter. Finally, there is Fossil, which starts from the other end by attempting to replace git entirely and tracking itself. I am however not too comfortable with the thought of replacing git, and Fossil's non-SCM features don't seem to be as developed. Now before I invest too much time when someone else might already have tried this, I basically have two questions: Are there crucial features of Project Management software like Redmine that Foswiki does not provide even with all the extensions available? How to set Foswiki up to use git instead of the perl RcsLite?

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  • topics in distributed systems

    - by scatman
    what do you think is an interesting topic in distributed systems. i should pic a topic and present it on monday. at first i chose to talk about Wuala, but after reading about it, i don't think its that interesting. so what is an interesting (new) topic in distributed systems that i can research about. sorry if this is the wrong place to post.

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  • Algorithm to reduce a bitmap mask to a list of rectangles?

    - by mos
    Before I go spend an afternoon writing this myself, I thought I'd ask if there was an implementation already available --even just as a reference. The first image is an example of a bitmap mask that I would like to turn into a list of rectangles. A bad algorithm would return every set pixel as a 1x1 rectangle. A good algorithm would look like the second image, where it returns the coordinates of the orange and red rectangles. The fact that the rectangles overlap don't matter, just that there are only two returned. To summarize, the ideal result would be these two rectangles (x, y, w, h): [ { 3, 1, 2, 6 }, { 1, 3, 6, 2 } ]

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  • DRY Authenticated Tasks in Cocoa (with distributed objects)

    - by arbales
    I'm kind of surprise/infuriated that the only way for me to run an authenticated task, like perhaps sudo gem install shi*t, is to make a tool with pre-written code. I'm writing a MacRuby application, which doesn't seem to expose the KAuthorization* constants/methods. So.. I learned Cocoa and Objective-C. My application creates a object, serves it and calls the a tool that elevates itself and then performs a selector on a distributed object (in the tool's thread). I hoped that the distributed object's methods would evaluated inside the tool, so I could use delegation to create "privileged" tasks. If this won't work, don't try to save it, I just want a DRY/cocoa solution. AuthHelper.m //AuthorizationExecuteWithPrivileges of this. AuthResponder* my_responder = [AuthResponder sharedResponder]; // Gets the proxy object (and it's delegate) NSString *selector = [NSString stringWithUTF8String:argv[3]]; NSLog(@"Performing selector: %@", selector); setuid(0); if ([[my_responder delegate] respondsToSelector:NSSelectorFromString(selector)]){ [[my_responder delegate] performSelectorOnMainThread:NSSelectorFromString(selector) withObject:nil waitUntilDone:YES]; } RandomController.m - (void)awakeFromNib { helperToolPath = [[[NSBundle mainBundle] resourcePath] stringByAppendingString:@"/AuthHelper"]; delegatePath = [[[NSBundle mainBundle] resourcePath] stringByAppendingString:@"/ABExtensions.rb"]; AuthResponder* my_responder = [AuthResponder initAsService]; [my_responder setDelegate:self]; } -(oneway void)install_gems{ NSArray *args = [NSArray arrayWithObjects: @"gem", @"install", @"sinatra", nil]; [NSTask launchedTaskWithLaunchPath:@"/usr/bin/sudo" arguments:args]; NSLog(@"Ran AuthResponder.delegate.install_gems"); // This prints. } ... other privileges tasks. "sudo gem update --system" for one. I'm guessing the proxy object is performing the selector in it's own thread, but I want the current (privileged thread) to do it so I can use sudo. Can I force the distributed object to evaluate the selector on the tool's thread? How else can I accomplish this dryly/cocoaly?

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  • Why hill climbing is called anytime algorithm?

    - by crucified soul
    From wikipedia, Anytime algorithm In computer science an anytime algorithm is an algorithm that can return a valid solution to a problem even if it's interrupted at any time before it ends. The algorithm is expected to find better and better solutions the more time it keeps running. Hill climbing Hill climbing can often produce a better result than other algorithms when the amount of time available to perform a search is limited, such as with real-time systems. It is an anytime algorithm: it can return a valid solution even if it's interrupted at any time before it ends. Hill climbing algorithm can stuck into local optima or ridge, after that even if it runs infinite time, the result won't be any better. Then, why hill climbing is called anytime algorithm?

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  • What is lightweight lock in distributed shared memory systems?

    - by Kutluhan Metin
    I started reading Tanenbaum's Distributed Systems book a while ago. I read about two phase locking and timestamp reordering in transactions chapter. While having a deeper look from google I heard of lightweight transactions/lightweight transactional memory. But I couldn't find any good explanation and implementation. So what is lightweight memory? What are the benefits of lightweight locks? And how can I implement them?

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  • Where do you earn more money (Autonomous Systems vs Distributed Systems)? [closed]

    - by Puckl
    I am interested in both topics and I can choose between them for my computer science master. I think the distributed systems master focuses more on software technologies and the autononmous systems master is focused on robotics and machine learning. Do you get good jobs in the fild of machine learning without a Ph.D.? I guess there are more jobs available in the Software-Tech world, is this right? Where do you earn more money? (It is not the only criteria, but it matters)

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  • Dijkstra’s algorithm and functions

    - by baris_a
    Hi guys, the question is: suppose I have an input function like sin(2-cos(3*A/B)^2.5)+0.756*(C*D+3-B) specified with a BNF, I will parse input using recursive descent algorithm, and then how can I use or change Dijkstra’s algorithm to handle this given function? After parsing this input function, I need to execute it with variable inputs, where Dijkstra’s algorithm should do the work. Thanks in advance. EDIT: May be I should ask also: What is the best practice or data structure to represent given function?

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  • Efficient algorithm for finding largest eigenpair of small general complex matrix

    - by mklassen
    I am looking for an efficient algorithm to find the largest eigenpair of a small, general (non-square, non-sparse, non-symmetric), complex matrix, A, of size m x n. By small I mean m and n is typically between 4 and 64 and usually around 16, but with m not equal to n. This problem is straight forward to solve with the general LAPACK SVD algorithms, i.e. gesvd or gesdd. However, as I am solving millions of these problems and only require the largest eigenpair, I am looking for a more efficient algorithm. Additionally, in my application the eigenvectors will generally be similar for all cases. This lead me to investigate Arnoldi iteration based methods, but I have neither found a good library nor algorithm that applies to my small general complex matrix. Is there an appropriate algorithm and/or library?

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  • Algorithm for Text Wrapping Within a Shape

    - by devongovett
    I am looking for an algorithm to wrap text within a non-rectangular shape, preferably based on the Knuth and Plass algorithm. The hardest part of this is that the lines may have different heights due to differing font sizes in the text. The image below is an example of what the algorithm should be able to generate. Thanks for any help!

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  • Clustering [assessment] algorithm with distance matrix as an input

    - by Max
    Can anyone suggest some clustering algorithm which can work with distance matrix as an input? Or the algorithm which can assess the "goodness" of the clustering also based on the distance matrix? At this moment I'm using a modification of Kruskal's algorithm (http://en.wikipedia.org/wiki/Kruskal%27s_algorithm) to split data into two clusters. It has a problem though. When the data has no distinct clusters the algorithm will still create two clusters with one cluster containing one element and the other containing all the rest. In this case I would rather have one cluster containing all the elements and another one which is empty. Are there any algorithms which are capable of doing this type of clustering? Are there any algorithms which can estimate how well the clustering was done or even better how many clusters are there in the data? The algorithms should work only with distance(similarity) matrices as an input.

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  • Dijkstra's algorithm: why does it work? (not how)

    - by BeeBand
    I understand what Dijkstra's algorithm is but I don't understand why it works. When selecting the next vertice to examine, why does Dijkstra's algorithm select the one with the smallest weight? Why not just select a vertex arbitrarily, since the algorithm visits all vertices anyway?

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  • Algorithm for matching partially filled words

    - by adnanhb
    Hello All, I am writing a game which when given a partially filled word, searches a dictionary and returns all the matching words. To that effect, I am trying to find an algorithm that can be used for the said purpose. For example, given - - a -, the algorithm will search a dictionary for all the words which have length 4 and have 'a' as the third letter. Is there such an algorithm already? If not, can somebody given a rough idea of how to design such an algorithm? Thanks in Advance.

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  • isometric drawing order with larger than single tile images - drawing order algorithm?

    - by Roger Smith
    I have an isometric map over which I place various images. Most images will fit over a single tile, but some images are slightly larger. For example, I have a bed of size 2x3 tiles. This creates a problem when drawing my objects to the screen as I get some tiles erroneously overlapping other tiles. The two solutions that I know of are either splitting the image into 1x1 tile segments or implementing my own draw order algorithm, for example by assigning each image a number. The image with number 1 is drawn first, then 2, 3 etc. Does anyone have advice on what I should do? It seems to me like splitting an isometric image is very non obvious. How do you decide which parts of the image are 'in' a particular tile? I can't afford to split up all of my images manually either. The draw order algorithm seems like a nicer choice but I am not sure if it's going to be easy to implement. I can't solve, in my head, how to deal with situations whereby you change the index of one image, which causes a knock on effect to many other images. If anyone has an resources/tutorials on this I would be most grateful.

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  • Distributed, persistent cache using EHCache

    - by Richard
    I currently have a distributed cache using EHCache via RMI that works just fine. I was wondering if you can include persistence with the caches to create a distributed, persistent cache. Alongside this, if the cache was persistent, would it load from the file store, then bootstrap from the cache cluster? Basically, what I want is: Cache starts Cache loads persistent objects from the file store Cache joins the distruted cluster and bootstraps as normal The usecase behind this is having 2 identical components running on independent machines, distributing the cache to avoid losing data in the event that one of the components fails. The persistence would guard against losing all data on the rare occasion that both components fail. Would moving to another distribution method (such as Terracotta) support this?

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  • What algorithm to use to fill a KenKen square board with cages?

    - by JimmyBoh
    I am working on recreating KenKen, a popular math puzzle involving a blank grid that is divided into "cages". Each cage is just a collection of adjacent squares and has a clue which is generally a number and an operand, shown below: What type of algorithm would be best to fill the square with cages? Assume the maximum number of cells per cage would be 3 and the board is 4x4 in size, like in the example above.

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  • Lawler's Algorithm Implementation Assistance

    - by Richard Knop
    Here is my implemenation of Lawler's algorithm in PHP (I know... but I'm used to it): <?php $jobs = array(1, 2, 3, 4, 5, 6); $jobsSubset = array(2, 5, 6); $n = count($jobs); $processingTimes = array(2, 3, 4, 3, 2, 1); $dueDates = array(3, 15, 9, 7, 11, 20); $optimalSchedule = array(); foreach ($jobs as $j) { $optimalSchedule[] = 0; } $dicreasedCardinality = array(); for ($i = $n; $i >= 1; $i--) { $x = 0; $max = 0; // loop through all jobs for ($j = 0; $j < $i; $j++) { // ignore if $j already is in the $dicreasedCardinality array if (false === in_array($j, $dicreasedCardinality)) { // if the job has no succesor in $jobsSubset if (false === isset($jobs[$j+1]) || false === in_array($jobs[$j+1], $jobsSubset)) { // here I find an array index of a job with the maximum due date // amongst jobs with no sucessor in $jobsSubset if ($x < $dueDates[$j]) { $x = $dueDates[$j]; $max = $j; } } } } // move the job at the end of $optimalSchedule $optimalSchedule[$i-1] = $jobs[$max]; // decrease the cardinality of $jobs $dicreasedCardinality[] = $max; } print_r($optimalSchedule); Now the above returns an optimal schedule like this: Array ( [0] => 1 [1] => 1 [2] => 1 [3] => 3 [4] => 2 [5] => 6 ) Which doesn't seem right to me. The problem might be with my implementation of the algorithm because I am not sure I understand it correctly. I used this source to implement it: http://www.google.com/books?id=aSiBs6PDm9AC&pg=PA166&dq=lawler%27s+algorithm+code&lr=&hl=sk&cd=4#v=onepage&q=&f=false The description there is a little confusing. For example, I didn't quite get how is the subset D defined (I guess it is arbitrary). Could anyone help me out with this? I have been trying to find some sources with simpler explanation of the algorithm but all sources I found were even more complicated (with math proofs and such) so I am stuck with the link above. Yes, this is a homework, if it wasn't obvious. I still have few weeks to crack this but I have spent few days already trying to get how exactly this algorithm works with no success so I don't think I will get any brighter during that time.

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  • Shuffling algorithm with no "self-mapping"?

    - by OregonTrail
    To randomly shuffle an array, with no bias towards any particular permutation, there is the Knuth Fischer-Yeats algorithm. In Python: #!/usr/bin/env python import sys from random import randrange def KFYShuffle(items): i = len(items) - 1 while i > 0: j = randrange(i+1) # 0 <= j <= i items[j], items[i] = items[i], items[j] i = i - 1 return items print KFYShuffle(range(int(sys.argv[1]))) There is also Sattolo's algorithm, which produces random cycles. In Python: #!/usr/bin/env python import sys from random import randrange def SattoloShuffle(items): i = len(items) while i > 1: i = i - 1 j = randrange(i) # 0 <= j <= i-1 items[j], items[i] = items[i], items[j] return items print SattoloShuffle(range(int(sys.argv[1]))) I'm currently writing a simulation with the following specifications for a shuffling algorithm: The algorithm is unbiased. If a true random number generator was used, no permutation would be more likely than any other. No number ends up at its original index. The input to the shuffle will always be A[i] = i for i from 0 to N-1 Permutations are produced that are not cycles, but still meet specification 2. The cycles produced by Sattolo's algorithm meet specification 2, but not specification 1 or 3. I've been working at creating an algorithm that meets these specifications, what I came up with was equivalent to Sattolo's algorithm. Does anyone have an algorithm for this problem?

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  • Simplest distributed persistent key/value store that supports primary key range queries

    - by StaxMan
    I am looking for a properly distributed (i.e. not just sharded) and persisted (not bounded by available memory on single node, or cluster of nodes) key/value ("nosql") store that does support range queries by primary key. So far closest such system is Cassandra, which does above. However, it adds support for other features that are not essential for me. So while I like it (and will consider using it of course), I am trying to figure out if there might be other mature projects that implement what I need. Specifically, for me the only aspect of value I need is to access it as a blob. For key, however, I need range queries (as in, access values ordered, limited by start and/or end values). While values can have structures, there is no need to use that structure for anything on server side (can do client-side data binding, flexible value/content types etc). For added bonus, Cassandra style storage (journaled, all sequential writes) seems quite optimal for my use case. To help filter out answers, I have investigated some alternatives within general domain like: Voldemort (key/value, but no ordering) and CouchDB (just sharded, more batch-oriented); and am aware of systems that are not quite distributed while otherwise qualifying (bdb variants, tokyo cabinet itself (not sure if Tyrant might qualify), redis (in-memory store only)).

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  • Framework or tool for "distributed unit testing"?

    - by user262646
    Is there any tool or framework able to make it easier to test distributed software written in Java? My system under test is a peer-to-peer software, and I'd like to perform testing using something like PNUnit, but with Java instead of .Net. The system under test is a framework I'm developing to build P2P applications. It uses JXTA as a lower subsystem, trying to hide some complexities of it. It's currently an academic project, so I'm pursuing simplicity at this moment. In my test, I want to demonstrate that a peer (running in its own process, possibly with multiple threads) can discover another one (running in another process or even another machine) and that they can exchange a few messages. I'm not using mocks nor stubs because I need to see both sides working simultaneously. I realize that some kind of coordination mechanism is needed, and PNUnit seems to be able to do that. I've bumped into some initiatives like Pisces, which "aims to provide a distributed testing environment that extends JUnit, giving the developer/tester an ability to run remote JUnits and create complex test suites that are composed of several remote JUnit tests running in parallel or serially", but this project and a few others I have found seem to be long dead.

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  • An implementation of Sharir's or Aurenhammer's deterministic algorithm for calculating the intersect

    - by RGrey
    The problem of finding the intersection/union of 'N' discs/circles on a flat plane was first proposed by M. I. Shamos in his 1978 thesis: Shamos, M. I. “Computational Geometry” Ph.D. thesis, Yale Univ., New Haven, CT 1978. Since then, in 1985, Micha Sharir presented an O(n log2n) time and O(n) space deterministic algorithm for the disc intersection/union problem (based on modified Voronoi diagrams): Sharir, M. Intersection and closest-pair problems for a set of planar discs. SIAM .J Comput. 14 (1985), pp. 448-468. In 1988, Franz Aurenhammer presented a more efficient O(n log n) time and O(n) space algorithm for circle intersection/union using power diagrams (generalizations of Voronoi diagrams): Aurenhammer, F. Improved algorithms for discs and balls using power diagrams. Journal of Algorithms 9 (1985), pp. 151-161. Earlier in 1983, Paul G. Spirakis also presented an O(n^2) time deterministic algorithm, and an O(n) probabilistic algorithm: Spirakis, P.G. Very Fast Algorithms for the Area of the Union of Many Circles. Rep. 98, Dept. Comput. Sci., Courant Institute, New York University, 1983. I've been searching for any implementations of the algorithms above, focusing on computational geometry packages, and I haven't found anything yet. As neither appear trivial to put into practice, it would be really neat if someone could point me in the right direction!

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  • average case running time of linear search algorithm

    - by Brahadeesh
    Hi all. I am trying to derive the average case running time for deterministic linear search algorithm. The algorithm searches an element x in an unsorted array A in the order A[1], A[2], A[3]...A[n]. It stops when it finds the element x or proceeds until it reaches the end of the array. I searched on wikipedia and the answer given was (n+1)/(k+1) where k is the number of times x is present in the array. I approached in another way and am getting a different answer. Can anyone please give me the correct proof and also let me know whats wrong with my method? E(T)= 1*P(1) + 2*P(2) + 3*P(3) ....+ n*P(n) where P(i) is the probability that the algorithm runs for 'i' time (i.e. compares 'i' elements). P(i)= (n-i)C(k-1) * (n-k)! / n! Here, (n-i)C(k-1) is (n-i) Choose (k-1). As the algorithm has reached the ith step, the rest of k-1 x's must be in the last n-i elements. Hence (n-i)C(k-i). (n-k)! is the total number of ways of arranging the rest non x numbers, and n! is the total number of ways of arranging the n elements in the array. I am not getting (n+1)/(k+1) on simplifying.

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