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  • How to prepare for a programming competition? Graphs, Stacks, Trees, oh my! [closed]

    - by Simucal
    Last semester I attended ACM's (Association for Computing Machinery) bi-annual programming competition at a local University. My University sent 2 teams of 3 people and we competed amongst other schools in the mid-west. We got our butts kicked. You are given a packet with about 11 problems (1 problem per page) and you have 4 hours to solve as many as you can. They'll run your program you submit against a set of data and your output must match theirs exactly. In fact, the judging is automated for the most part. In any case.. I went there fairly confident in my programming skills and I left there feeling drained and weak. It was a terribly humbling experience. In 4 hours my team of 3 people completed only one of the problems. The top team completed 4 of them and took 1st place. The problems they asked were like no problems I have ever had to answer before. I later learned that in order to solve them some of them effectively you have to use graphs/graph algorithms, trees, stacks. Some of them were simply "greedy" algo's. My question is, how can I better prepare for this semesters programming competition so I don't leave there feeling like a complete moron? What tips do you have for me to be able to answer these problems that involve graphs, trees, various "well known" algorithms? How can I easily identify the algorithm we should implement for a given problem? I have yet to take Algorithm Design in school so I just feel a little out of my element. Here are some examples of the questions asked at the competitions: ACM Problem Sets Update: Just wanted to update this since the latest competition is over. My team placed 1st for our small region (about 6-7 universities with between 1-5 teams each school) and ~15th for the midwest! So, it is a marked improvement over last years performance for sure. We also had no graduate students on our team and after reviewing the rules we found out that many teams had several! So, that would be a pretty big advantage in my own opinion. Problems this semester ranged from about 1-2 "easy" problems (ie bit manipulation, string manipulation) to hard (graph problems involving fairly complex math and network flow problems). We were able to solve 4 problems in our 5 hours. Just wanted to thank everyone for the resources they provided here, we used them for our weekly team practices and it definitely helped! Some quick tips that I have that aren't suggested below: When you are seated at your computer before the competition starts, quickly type out various data structures that you might need that you won't have access to in your languages libraries. I typed out a Graph data-structure complete with floyd-warshall and dijkstra's algorithm before the competition began. We ended up using it in our 2nd problem that we solved and this is the main reason why we solved this problem before anyone else in the midwest. We had it ready to go from the beginning. Similarly, type out the code to read in a file since this will be required for every problem. Save this answer "template" someplace so you can quickly copy/paste it to your IDE at the beginning of each problem. There are no rules on programming anything before the competition starts so get any boilerplate code out the way. We found it useful to have one person who is on permanent whiteboard duty. This is usually the person who is best at math and at working out solutions to get a head start on future problems you will be doing. One person is on permanent programming duty. Your fastest/most skilled "programmer" (most familiar with the language). This will save debugging time also. The last person has several roles between assessing the packet of problems for the next "easiest" problem, helping the person on the whiteboard work out solutions and helping the person programming work out bugs/issues. This person needs to be flexible and be able to switch between roles easily.

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  • Clever memory usage through the years

    - by Ben Emmett
    A friend and I were recently talking about the really clever tricks people have used to get the most out of memory. I thought I’d share my favorites, and would love to hear yours too! Interleaving on drum memory Back in the ye olde days before I’d been born (we’re talking the 50s / 60s here), working memory commonly took the form of rotating magnetic drums. These would spin at a constant speed, and a fixed head would read from memory when the correct part of the drum passed it by, a bit like a primitive platter disk. Because each revolution took a few milliseconds, programmers took to manually arranging information non-sequentially on the drum, timing when an instruction or memory address would need to be accessed, then spacing information accordingly around the edge of the drum, thus reducing the access delay. Similar techniques were still used on hard disks and floppy disks into the 90s, but have become irrelevant with modern disk technologies. The Hashlife algorithm Conway’s Game of Life has attracted numerous implementations over the years, but Bill Gosper’s Hashlife algorithm is particularly impressive. Taking advantage of the repetitive nature of many cellular automata, it uses a quadtree structure to store the hashes of pieces of the overall grid. Over time there are fewer and fewer new structures which need to be evaluated, so it starts to run faster with larger grids, drastically outperforming other algorithms both in terms of speed and the size of grid which can be simulated. The actual amount of memory used is huge, but it’s used in a clever way, so makes the list . Elite’s procedural generation Ok, so this isn’t exactly a memory optimization – more a storage optimization – but it gets an honorable mention anyway. When writing Elite, David Braben and Ian Bell wanted to build a rich world which gamers could explore, but their 22K memory was something of a limitation (for comparison that’s about the size of my avatar picture at the top of this page). They procedurally generated all the characteristics of the 2048 planets in their virtual universe, including the names, which were stitched together using a lookup table of parts of names. In fact the original plans were for 2^52 planets, but it was decided that that was probably too many. Oh, and they did that all in assembly language. Other games of the time used similar techniques too – The Sentinel’s landscape generation algorithm being another example. Modern Garbage Collectors Garbage collection in managed languages like Java and .NET ensures that most of the time, developers stop needing to care about how they use and clean up memory as the garbage collector handles it automatically. Achieving this without killing performance is a near-miraculous feet of software engineering. Much like when learning chemistry, you find that every time you think you understand how the garbage collector works, it turns out to be a mere simplification; that there are yet more complexities and heuristics to help it run efficiently. Of course introducing memory problems is still possible (and there are tools like our memory profiler to help if that happens to you) but they’re much, much rarer. A cautionary note In the examples above, there were good and well understood reasons for the optimizations, but cunningly optimized code has usually had to trade away readability and maintainability to achieve its gains. Trying to optimize memory usage without being pretty confident that there’s actually a problem is doing it wrong. So what have I missed? Tell me about the ingenious (or stupid) tricks you’ve seen people use. Ben

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  • Observing flow control idle time in TCP

    - by user12820842
    Previously I described how to observe congestion control strategies during transmission, and here I talked about TCP's sliding window approach for handling flow control on the receive side. A neat trick would now be to put the pieces together and ask the following question - how often is TCP transmission blocked by congestion control (send-side flow control) versus a zero-sized send window (which is the receiver saying it cannot process any more data)? So in effect we are asking whether the size of the receive window of the peer or the congestion control strategy may be sub-optimal. The result of such a problem would be that we have TCP data that we could be transmitting but we are not, potentially effecting throughput. So flow control is in effect: when the congestion window is less than or equal to the amount of bytes outstanding on the connection. We can derive this from args[3]-tcps_snxt - args[3]-tcps_suna, i.e. the difference between the next sequence number to send and the lowest unacknowledged sequence number; and when the window in the TCP segment received is advertised as 0 We time from these events until we send new data (i.e. args[4]-tcp_seq = snxt value when window closes. Here's the script: #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::send / (args[3]-tcps_snxt - args[3]-tcps_suna) = args[3]-tcps_cwnd / { cwndclosed[args[1]-cs_cid] = timestamp; cwndsnxt[args[1]-cs_cid] = args[3]-tcps_snxt; @numclosed["cwnd", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } tcp:::send / cwndclosed[args[1]-cs_cid] && args[4]-tcp_seq = cwndsnxt[args[1]-cs_cid] / { @meantimeclosed["cwnd", args[2]-ip_daddr, args[4]-tcp_dport] = avg(timestamp - cwndclosed[args[1]-cs_cid]); @stddevtimeclosed["cwnd", args[2]-ip_daddr, args[4]-tcp_dport] = stddev(timestamp - cwndclosed[args[1]-cs_cid]); @numclosed["cwnd", args[2]-ip_daddr, args[4]-tcp_dport] = count(); cwndclosed[args[1]-cs_cid] = 0; cwndsnxt[args[1]-cs_cid] = 0; } tcp:::receive / args[4]-tcp_window == 0 && (args[4]-tcp_flags & (TH_SYN|TH_RST|TH_FIN)) == 0 / { swndclosed[args[1]-cs_cid] = timestamp; swndsnxt[args[1]-cs_cid] = args[3]-tcps_snxt; @numclosed["swnd", args[2]-ip_saddr, args[4]-tcp_dport] = count(); } tcp:::send / swndclosed[args[1]-cs_cid] && args[4]-tcp_seq = swndsnxt[args[1]-cs_cid] / { @meantimeclosed["swnd", args[2]-ip_daddr, args[4]-tcp_sport] = avg(timestamp - swndclosed[args[1]-cs_cid]); @stddevtimeclosed["swnd", args[2]-ip_daddr, args[4]-tcp_sport] = stddev(timestamp - swndclosed[args[1]-cs_cid]); swndclosed[args[1]-cs_cid] = 0; swndsnxt[args[1]-cs_cid] = 0; } END { printf("%-6s %-20s %-8s %-25s %-8s %-8s\n", "Window", "Remote host", "Port", "TCP Avg WndClosed(ns)", "StdDev", "Num"); printa("%-6s %-20s %-8d %@-25d %@-8d %@-8d\n", @meantimeclosed, @stddevtimeclosed, @numclosed); } So this script will show us whether the peer's receive window size is preventing flow ("swnd" events) or whether congestion control is limiting flow ("cwnd" events). As an example I traced on a server with a large file transfer in progress via a webserver and with an active ssh connection running "find / -depth -print". Here is the output: ^C Window Remote host Port TCP Avg WndClosed(ns) StdDev Num cwnd 10.175.96.92 80 86064329 77311705 125 cwnd 10.175.96.92 22 122068522 151039669 81 So we see in this case, the congestion window closes 125 times for port 80 connections and 81 times for ssh. The average time the window is closed is 0.086sec for port 80 and 0.12sec for port 22. So if you wish to change congestion control algorithm in Oracle Solaris 11, a useful step may be to see if congestion really is an issue on your network. Scripts like the one posted above can help assess this, but it's worth reiterating that if congestion control is occuring, that's not necessarily a problem that needs fixing. Recall that congestion control is about controlling flow to prevent large-scale drops, so looking at congestion events in isolation doesn't tell us the whole story. For example, are we seeing more congestion events with one control algorithm, but more drops/retransmission with another? As always, it's best to start with measures of throughput and latency before arriving at a specific hypothesis such as "my congestion control algorithm is sub-optimal".

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  • Reading graph inputs for a programming puzzle and then solving it

    - by Vrashabh
    I just took a programming competition question and I absolutely bombed it. I had trouble right at the beginning itself from reading the input set. The question was basically a variant of this puzzle http://codercharts.com/puzzle/evacuation-plan but also had an hour component in the first line(say 3 hours after start of evacuation). It reads like this This puzzle is a tribute to all the people who suffered from the earthquake in Japan. The goal of this puzzle is, given a network of road and locations, to determine the maximum number of people that can be evacuated. The people must be evacuated from evacuation points to rescue points. The list of road and the number of people they can carry per hour is provided. Input Specifications Your program must accept one and only one command line argument: the input file. The input file is formatted as follows: the first line contains 4 integers n r s t n is the number of locations (each location is given by a number from 0 to n-1) r is the number of roads s is the number of locations to be evacuated from (evacuation points) t is the number of locations where people must be evacuated to (rescue points) the second line contains s integers giving the locations of the evacuation points the third line contains t integers giving the locations of the rescue points the r following lines contain to the road definitions. Each road is defined by 3 integers l1 l2 width where l1 and l2 are the locations connected by the road (roads are one-way) and width is the number of people per hour that can fit on the road Now look at the sample input set 5 5 1 2 3 0 3 4 0 1 10 0 2 5 1 2 4 1 3 5 2 4 10 The 3 in the first line is the additional component and is defined as the number of hours since the resuce has started which is 3 in this case. Now my solution was to use Dijisktras algorithm to find the shortest path between each of the rescue and evac nodes. Now my problem started with how to read the input set. I read the first line in python and stored the values in variables. But then I did not know how to store the values of the distance between the nodes and what DS to use and how to input it to say a standard implementation of dijikstras algorithm. So my question is two fold 1.) How do I take the input of such problems? - I have faced this problem in quite a few competitions recently and I hope I can get a simple code snippet or an explanation in java or python to read the data input set in such a way that I can input it as a graph to graph algorithms like dijikstra and floyd/warshall. Also a solution to the above problem would also help. 2.) How to solve this puzzle? My algorithm was: Find shortest path between evac points (in the above example it is 14 from 0 to 3) Multiply it by number of hours to get maximal number of saves Also the answer given for the variant for the input set was 24 which I dont understand. Can someone explain that also. UPDATE: I get how the answer is 14 in the given problem link - it seems to be just the shortest path between node 0 and 3. But with the 3 hour component how is the answer 24 UPDATE I get how it is 24 - its a complete graph traversal at every hour and this is how I solve it Hour 1 Node 0 to Node 1 - 10 people Node 0 to Node 2- 5 people TotalRescueCount=0 Node 1=10 Node 2= 5 Hour 2 Node 1 to Node 3 = 5(Rescued) Node 2 to Node 4 = 5(Rescued) Node 0 to Node 1 = 10 Node 0 to Node 2 = 5 Node 1 to Node 2 = 4 TotalRescueCount = 10 Node 1 = 10 Node 2= 5+4 = 9 Hour 3 Node 1 to Node 3 = 5(Rescued) Node 2 to Node 4 = 5+4 = 9(Rescued) TotalRescueCount = 9+5+10 = 24 It hard enough for this case , for multiple evac and rescue points how in the world would I write a pgm for this ?

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  • Modular Reduction of Polynomials in NTRUEncrypt

    - by Neville
    Hello everyone. I'm implementing the NTRUEncrypt algorithm, according to an NTRU tutorial, a polynomial f has an inverse g such that f*g=1 mod x, basically the polynomial multiplied by its inverse reduced modulo x gives 1. I get the concept but in an example they provide, a polynomial f = -1 + X + X^2 - X4 + X6 + X9 - X10 which we will represent as the array [-1,1,1,0,-1,0,1,0,0,1,-1] has an inverse g of [1,2,0,2,2,1,0,2,1,2,0], so that when we multiply them and reduce the result modulo 3 we get 1, however when I use the NTRU algorithm for multiplying and reducing them I get -2. Here is my algorithm for multiplying them written in Java: public static int[] PolMulFun(int a[],int b[],int c[],int N,int M) { for(int k=N-1;k>=0;k--) { c[k]=0; int j=k+1; for(int i=N-1;i>=0;i--) { if(j==N) { j=0; } if(a[i]!=0 && b[j]!=0) { c[k]=(c[k]+(a[i]*b[j]))%M; } j=j+1; } } return c; } It basicall taken in polynomial a and multiplies it b, resturns teh result in c, N specifies the degree of the polynomials+1, in teh example above N=11; and M is the reuction modulo, in teh exampel above 3. Why am I getting -2 and not 1?

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  • Progress Bar design patterns?

    - by shoosh
    The application I'm writing performs a length algorithm which usually takes a few minutes to finish. During this time I'd like to show the user a progress bar which indicates how much of the algorithm is done as precisely as possible. The algorithm is divided into several steps, each with its own typical timing. For instance- initialization (500 milli-sec) reading inputs (5 sec) step 1 (30 sec) step 2 (3 minutes) writing outputs (7 sec) shutting down (10 milli-sec) Each step can report its progress quite easily by setting the range its working on, say [0 to 150] and then reporting the value it completed in its main loop. What I currently have set up is a scheme of nested progress monitors which form a sort of implicit tree of progress reporting. All progress monitors inherit from an interface IProgressMonitor: class IProgressMonitor { public: void setRange(int from, int to) = 0; void setValue(int v) = 0; }; The root of the tree is the ProgressMonitor which is connected to the actual GUI interface: class GUIBarProgressMonitor : public IProgressMonitor { GUIBarProgressMonitor(ProgressBarWidget *); }; Any other node in the tree are monitors which take control of a piece of the parent progress: class SubProgressMonitor : public IProgressMonitor { SubProgressMonitor(IProgressMonitor *parent, int parentFrom, int parentLength) ... }; A SubProgressMonitor takes control of the range [parentFrom, parentFrom+parentLength] of its parent. With this scheme I am able to statically divide the top level progress according to the expected relative portion of each step in the global timing. Each step can then be further subdivided into pieces etc' The main disadvantage of this is that the division is static and it gets painful to make changes according to variables which are discovered at run time. So the question: are there any known design patterns for progress monitoring which solve this issue?

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  • Updating a Minimum spanning tree when a new edge is inserted

    - by Lynette
    Hello, I've been presented the following problem in University: Let G = (V, E) be an (undirected) graph with costs ce = 0 on the edges e € E. Assume you are given a minimum-cost spanning tree T in G. Now assume that a new edge is added to G, connecting two nodes v, tv € V with cost c. a) Give an efficient algorithm to test if T remains the minimum-cost spanning tree with the new edge added to G (but not to the tree T). Make your algorithm run in time O(|E|). Can you do it in O(|V|) time? Please note any assumptions you make about what data structure is used to represent the tree T and the graph G. b)Suppose T is no longer the minimum-cost spanning tree. Give a linear-time algorithm (time O(|E|)) to update the tree T to the new minimum-cost spanning tree. This is the solution I found: Let e1=(a,b) the new edge added Find in T the shortest path from a to b (BFS) if e1 is the most expensive edge in the cycle then T remains the MST else T is not the MST It seems to work but i can easily make this run in O(|V|) time, while the problem asks O(|E|) time. Am i missing something? By the way we are authorized to ask for help from anyone so I'm not cheating :D Thanks in advance

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  • Python MD5 Hash Faster Calculation

    - by balgan
    Hi everyone. I will try my best to explain my problem and my line of thought on how I think I can solve it. I use this code for root, dirs, files in os.walk(downloaddir): for infile in files: f = open(os.path.join(root,infile),'rb') filehash = hashlib.md5() while True: data = f.read(10240) if len(data) == 0: break filehash.update(data) print "FILENAME: " , infile print "FILE HASH: " , filehash.hexdigest() and using start = time.time() elapsed = time.time() - start I measure how long it takes to calculate an hash. Pointing my code to a file with 653megs this is the result: root@Mars:/home/tiago# python algorithm-timer.py FILENAME: freebsd.iso FILE HASH: ace0afedfa7c6e0ad12c77b6652b02ab 12.624 root@Mars:/home/tiago# python algorithm-timer.py FILENAME: freebsd.iso FILE HASH: ace0afedfa7c6e0ad12c77b6652b02ab 12.373 root@Mars:/home/tiago# python algorithm-timer.py FILENAME: freebsd.iso FILE HASH: ace0afedfa7c6e0ad12c77b6652b02ab 12.540 Ok now 12 seconds +- on a 653mb file, my problem is I intend to use this code on a program that will run through multiple files, some of them might be 4/5/6Gb and it will take wayy longer to calculate. What am wondering is if there is a faster way for me to calculate the hash of the file? Maybe by doing some multithreading? I used a another script to check the use of the CPU second by second and I see that my code is only using 1 out of my 2 CPUs and only at 25% max, any way I can change this? Thank you all in advance for the given help.

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  • Finding the left-most and right-most points of a list. std::find_if the right way to go?

    - by Tom
    Hi, I have a list of Point objects, (each one with x,y properties) and would like to find the left-most and right-most points. I've been trying to do it with find_if, but i'm not sure its the way to go, because i can't seem to pass a comparator instance. Is find_if the way to go? Seems not. So, is there an algorithm in <algorithm> to achieve this? Thanks in advance. #include <iostream> #include <list> #include <algorithm> using namespace std; typedef struct Point{ float x; float y; } Point; bool left(Point& p1,Point& p2) { return p1.x < p2.x; } int main(){ Point p1 ={-1,0}; Point p2 ={1,0}; Point p3 ={5,0}; Point p4 ={7,0}; list <Point> points; points.push_back(p1); points.push_back(p2); points.push_back(p3); points.push_back(p4); //Should return an interator to p1. find_if(points.begin(),points.end(),left); return 0; }

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  • Boost lambda: Invoke method on object

    - by ckarras
    I'm looking at boost::lambda as a way to to make a generic algorithm that can work with any "getter" method of any class. The algorithm is used to detect duplicate values of a property, and I would like for it to work for any property of any class. In C#, I would do something like this: class Dummy { public String GetId() ... public String GetName() ... } IEnumerable<String> FindNonUniqueValues<ClassT> (Func<ClassT,String> propertyGetter) { ... } Example use of the method: var duplicateIds = FindNonUniqueValues<Dummy>(d => d.GetId()); var duplicateNames = FindNonUniqueValues<Dummy>(d => d.GetName()); I can get the for "any class" part to work, using either interfaces or template methods, but have not found yet how to make the "for any method" part work. Is there a way to do something similar to the "d = d.GetId()" lambda in C++ (either with or without Boost)? Alternative, more C++ian solutions to make the algorithm generic are welcome too. I'm using C++/CLI with VS2008, so I can't use C++0x lambdas.

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  • Password hashing, salt and storage of hashed values

    - by Jonathan Leffler
    Suppose you were at liberty to decide how hashed passwords were to be stored in a DBMS. Are there obvious weaknesses in a scheme like this one? To create the hash value stored in the DBMS, take: A value that is unique to the DBMS server instance as part of the salt, And the username as a second part of the salt, And create the concatenation of the salt with the actual password, And hash the whole string using the SHA-256 algorithm, And store the result in the DBMS. This would mean that anyone wanting to come up with a collision should have to do the work separately for each user name and each DBMS server instance separately. I'd plan to keep the actual hash mechanism somewhat flexible to allow for the use of the new NIST standard hash algorithm (SHA-3) that is still being worked on. The 'value that is unique to the DBMS server instance' need not be secret - though it wouldn't be divulged casually. The intention is to ensure that if someone uses the same password in different DBMS server instances, the recorded hashes would be different. Likewise, the user name would not be secret - just the password proper. Would there be any advantage to having the password first and the user name and 'unique value' second, or any other permutation of the three sources of data? Or what about interleaving the strings? Do I need to add (and record) a random salt value (per password) as well as the information above? (Advantage: the user can re-use a password and still, probably, get a different hash recorded in the database. Disadvantage: the salt has to be recorded. I suspect the advantage considerably outweighs the disadvantage.) There are quite a lot of related SO questions - this list is unlikely to be comprehensive: Encrypting/Hashing plain text passwords in database Secure hash and salt for PHP passwords The necessity of hiding the salt for a hash Clients-side MD5 hash with time salt Simple password encryption Salt generation and Open Source software I think that the answers to these questions support my algorithm (though if you simply use a random salt, then the 'unique value per server' and username components are less important).

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  • Deterministic and non uniform long string generation from seed

    - by Limonup
    I had this weird idea for an encryption that I wanted to try out, it may be bad, and it may have done before, but I'm just doing it for fun. The short version of the question is: Is it possible to generate a long, deterministic and non-uniformly distributed string/sequence of numbers from a small seed? Long(er) version: I was thinking to encrypt a text by changing encoding. The new encoding would be generated via Huffman algorithm. To work well, the Huffman algorithm would need a fairly long text with non uniform distribution. Then characters can have different bit-lengths which would be the primary strength of this encryption. The problem is that its impractical to enter in/remember a long text each time you want to decrypt the text. So I was wondering if it was possible to generate a text from password seed? It doesn't matter what the text is, as long as it has non uniform distribution of characters and that the exact same sequence can be recreated each time you give it the same seed. Preferably, are there any functions/extensions in Python that can do this? EDIT: To expand on the "strength" of varying bit length: if I have a string "test", ASCII values 116, 101, 115, 116, which gives bit values of 1110100 1100101 1110011 1110100 Then, say my Huffman algorithm generates encoding like t = 101 e = 1100111 s = 10001 The final string is 101 1100111 10001 101, if we encode this back to ASCII, we get 1011100 1111000 1101000, which is 3 entirely different characters. Obviously its impossible to perform any kind of frequency analysis or something like that on this.

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  • Which design pattern is most appropriate?

    - by Anon
    Hello, I want to create a class that can use one of four algorithms (and the algorithm to use is only known at run-time). I was thinking that the Strategy design pattern sounds appropriate, but my problem is that each algorithm requires slightly different parameters. Would it be a bad design to use strategy, but pass in the relevant parameters into the constructor?. Here is an example (for simplicity, let's say there are only two possible algorithms) ... class Foo { private: // At run-time the correct algorithm is used, e.g. a = new Algorithm1(1); AlgorithmInterface* a; }; class AlgorithmInterface { public: virtual void DoSomething = 0; }; class Algorithm1 : public AlgorithmInterface { public: Algorithm1( int i ) : value(i) {} virtual void DoSomething(){ // Does something with int value }; int value; }; class Algorithm2 : public AlgorithmInterface { public: Algorithm2( bool b ) : value(b) {} virtual void DoSomething(){ // Do something with bool value }; bool value; };

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  • NHibernate correct way to reattach cached entity to different session

    - by Chris Marisic
    I'm using NHibernate to query a list of objects from my database. After I get the list of objects over them I iterate over the list of objects and apply a distance approximation algorithm to find the nearest object. I consider this function of getting the list of objects and apply the algorithm over them to be a heavy operation so I cache the object which I find from the algorithm in HttpRuntime.Cache. After this point whenever I'm given the supplied input again I can just directly pull the object from Cache instead of having to hit the database and traverse the list. My object is a complex object that has collections attached to it, inside the query where I return the full list of objects I don't bring back any of the sub collections eagerly so when I read my cached object I need lazy loading to work correctly to be able to display the object fully. Originally I tried using this to re-associate my cached object back to a new session _session.Lock(obj, LockMode.None); However when accessing the page concurrently from another instance I get the error Illegal attempt to associate a collection with two open sessions I then tried something different with _session.Merge(obj); However watching the output of this in NHProf shows that it is deleting and re-associating my object's contained collections with my object, which is not what I want although it seems to work fine. What is the correct way to do this? Neither of these seem to be right.

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  • CakePHP: Interaction between different files/classes

    - by Alexx Hardt
    Hey, I'm cloning a commercial student management system. Students use the frontend to apply for lectures, uni staff can modify events (time, room, etc). The core of the app will be the algortihm which distributes the seats to students. I already asked about it here: How to implement a seat distribution algorithm for uni lectures Now, I found a class for that algorithm here: http://www.phpclasses.org/browse/file/10779.html I put the 'class GA' into app/vendors. I need to write a 'class Solution', which represents one object (a child, and later a parent for the evolutionary process). I'll also have to write functions mutate(), crossover() and fitness(). fitness calculates a score of a solution, based on if there are overbooked courses etc; crossover() is the crazy monkey sex function which produces a child from two parents, and mutate() modifies a child after crossover. Now, the fitness()-function needs to access a few related models, and their find()-functions. It evaluates a solution's fitness by checking e.g. if there are overbooked courses, or unfulfilled wishes, and penalizes that. Where would I put the ga.php, solution.php and the three functions? ga.php has to access the functions, but the functions have to access the models. I also don't want to call any App::import()'s from within the fitness()-function, because it gets called many thousand times when the algorithm runs. Hope someone can help me. Thanks in advance =)

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  • Calculating distance from latitude, longitude and height using a geocentric co-ordinate system

    - by Sarge
    I've implemented this method in Javascript and I'm roughly 2.5% out and I'd like to understand why. My input data is an array of points represented as latitude, longitude and the height above the WGS84 ellipsoid. These points are taken from data collected from a wrist-mounted GPS device during a marathon race. My algorithm was to convert each point to cartesian geocentric co-ordinates and then compute the Euclidean distance (c.f Pythagoras). Cartesian geocentric is also known as Earth Centred Earth Fixed. i.e. it's an X, Y, Z co-ordinate system which rotates with the earth. My test data was the data from a marathon and so the distance should be very close to 42.26km. However, the distance comes to about 43.4km. I've tried various approaches and nothing changes the result by more than a metre. e.g. I replaced the height data with data from the NASA SRTM mission, I've set the height to zero, etc. Using Google, I found two points in the literature where lat, lon, height had been transformed and my transformation algorithm is matching. What could explain this? Am I expecting too much from Javascript's double representation? (The X, Y, Z numbers are very big but the differences between two points is very small). My alternative is to move to computing the geodesic across the WGS84 ellipsoid using Vincenty's algorithm (or similar) and then calculating the Euclidean distance with the two heights but this seems inaccurate. Thanks in advance for your help!

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  • Largest triangle from a set of points

    - by Faken
    I have a set of random points from which i want to find the largest triangle by area who's verticies are each on one of those points. So far I have figured out that the largest triangle's verticies will only lie on the outside points of the cloud of points (or the convex hull) so i have programmed a function to do just that (using Graham scan in nlogn time). However that's where I'm stuck. The only way I can figure out how to find the largest triangle from these points is to use brute force at n^3 time which is still acceptable in an average case as the convex hull algorithm usually kicks out the vast majority of points. However in a worst case scenario where points are on a circle, this method would fail miserably. Dose anyone know an algorithm to do this more efficiently? Note: I know that CGAL has this algorithm there but they do not go into any details on how its done. I don't want to use libraries, i want to learn this and program it myself (and also allow me to tweak it to exactly the way i want it to operate, just like the graham scan in which other implementations pick up collinear points that i don't want).

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  • Is memory allocation in linux non-blocking?

    - by Mark
    I am curious to know if the allocating memory using a default new operator is a non-blocking operation. e.g. struct Node { int a,b; }; ... Node foo = new Node(); If multiple threads tried to create a new Node and if one of them was suspended by the OS in the middle of allocation, would it block other threads from making progress? The reason why I ask is because I had a concurrent data structure that created new nodes. I then modified the algorithm to recycle the nodes. The throughput performance of the two algorithms was virtually identical on a 24 core machine. However, I then created an interference program that ran on all the system cores in order to create as much OS pre-emption as possible. The throughput performance of the algorithm that created new nodes decreased by a factor of 5 relative the the algorithm that recycled nodes. I'm curious to know why this would occur. Thanks. *Edit : pointing me to the code for the c++ memory allocator for linux would be helpful as well. I tried looking before posting this question, but had trouble finding it.

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  • Best way to implement plugin framework - are DLLs the only way (C/C++ project)?

    - by Microkernel
    Introduction: I am currently developing a document classifier software in C/C++ and I will be using Naive-Bayesian model for classification. But I wanted the users to use any algorithm that they want(or I want in the future), hence I went to separate the algorithm part in the architecture as a plugin that will be attached to the main app @ app start-up. Hence any user can write his own algorithm as a plugin and use it with my app. Problem Statement: The way I am intending to develop this is to have each of the algorithms that user wants to use to be made into a DLL file and put into a specific directory. And at the start, my app will search for all the DLLs in that directory and load them. My Questions: (1) What if a malicious code is made as a DLL (and that will have same functions mandated by plugin framework) and put into my plugins directory? In that case, my app will think that its a plugin and picks it and calls its functions, so the malicious code can easily bring down my entire app down (In the worst case could make my app as a malicious code launcher!!!). (2) Is using DLLs the only way available to implement plugin design pattern? (Not only for the fear of malicious plugin, but its a generic question out of curiosity :) ) (3) I think a lot of softwares are written with plugin model for extendability, if so, how do they defend against such attacks? (4) In general what do you think about my decision to use plugin model for extendability (do you think I should look at any other alternatives?) Thank you -MicroKernel :)

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  • Fast path cache generation for a connected node graph

    - by Sukasa
    I'm trying to get a faster pathfinding mechanism in place in a game I'm working on for a connected node graph. The nodes are classed into two types, "Networks" and "Routers." In this picture, the blue circles represent routers and the grey rectangles networks. Each network keeps a list of which routers it is connected to, and vice-versa. Routers cannot connect directly to other routers, and networks cannot connect directly to other networks. Networks list which routers they're connected to Routers do the same I need to get an algorithm that will map out a path, measured in the number of networks crossed, for each possible source and destination network excluding paths where the source and destination are the same network. I have one right now, however it is unusably slow, taking about two seconds to map the paths, which becomes incredibly noticeable for all connected players. The current algorithm is a depth-first brute-force search (It was thrown together in about an hour to just get the path caching working) which returns an array of networks in the order they are traversed, which explains why it's so slow. Are there any algorithms that are more efficient? As a side note, while these example graphs have four networks, the in-practice graphs have 55 networks and about 20 routers in use. Paths which are not possible also can occur, and as well at any time the network/router graph topography can change, requiring the path cache to be rebuilt. What approach/algorithm would likely provide the best results for this type of a graph?

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  • How can I implement a splay tree that performs the zig operation last, not first?

    - by Jakob
    For my Algorithms & Data Structures class, I've been tasked with implementing a splay tree in Haskell. My algorithm for the splay operation is as follows: If the node to be splayed is the root, the unaltered tree is returned. If the node to be splayed is one level from the root, a zig operation is performed and the resulting tree is returned. If the node to be splayed is two or more levels from the root, a zig-zig or zig-zag operation is performed on the result of splaying the subtree starting at that node, and the resulting tree is returned. This is valid according to my teacher. However, the Wikipedia description of a splay tree says the zig step "will be done only as the last step in a splay operation" whereas in my algorithm it is the first step in a splay operation. I want to implement a splay tree that performs the zig operation last instead of first, but I'm not sure how it would best be done. It seems to me that such an algorithm would become more complex, seeing as how one needs to find the node to be splayed before it can be determined whether a zig operation should be performed or not. How can I implement this in Haskell (or some other functional language)?

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  • Efficient Multiplication of Varying-Length #s [Conceptual]

    - by Milan Patel
    Write the pseudocode of an algorithm that takes in two arbitrary length numbers (provided as strings), and computes the product of these numbers. Use an efficient procedure for multiplication of large numbers of arbitrary length. Analyze the efficiency of your algorithm. I decided to take the (semi) easy way out and use the Russian Peasant Algorithm. It works like this: a * b = a/2 * 2b if a is even a * b = (a-1)/2 * 2b + a if a is odd My pseudocode is: rpa(x, y){ if x is 1 return y if x is even return rpa(x/2, 2y) if x is odd return rpa((x-1)/2, 2y) + y } I have 3 questions: Is this efficient for arbitrary length numbers? I implemented it in C and tried varying length numbers. The run-time in was near-instant in all cases so it's hard to tell empirically... Can I apply the Master's Theorem to understand the complexity...? a = # subproblems in recursion = 1 (max 1 recursive call across all states) n / b = size of each subproblem = n / 1 - b = 1 (problem doesn't change size...?) f(n^d) = work done outside recursive calls = 1 - d = 0 (the addition when a is odd) a = 1, b^d = 1, a = b^d - complexity is in n^d*log(n) = log(n) this makes sense logically since we are halving the problem at each step, right? What might my professor mean by providing arbitrary length numbers "as strings". Why do that? Many thanks in advance

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  • Python to Java translation

    - by obelix1337
    Hello, i get quite short code of algorithm in python, but i need to translate it to Java. I didnt find any program to do that, so i will really appreciate to help translating it. I learned python a very little to know the idea how algorithm work. The biggest problem is because in python all is object and some things are made really very confuzing like sum(self.flow[(source, vertex)] for vertex, capacity in self.get_edges(source)) and "self.adj" is like hashmap with multiple values which i have no idea how to put all together. Is any better collection for this code in java? code is: [CODE] class FlowNetwork(object): def __init__(self): self.adj, self.flow, = {},{} def add_vertex(self, vertex): self.adj[vertex] = [] def get_edges(self, v): return self.adj[v] def add_edge(self, u,v,w=0): self.adj[u].append((v,w)) self.adj[v].append((u,0)) self.flow[(u,v)] = self.flow[(v,u)] = 0 def find_path(self, source, sink, path): if source == sink: return path for vertex, capacity in self.get_edges(source): residual = capacity - self.flow[(source,vertex)] edge = (source,vertex,residual) if residual > 0 and not edge in path: result = self.find_path(vertex, sink, path + [edge]) if result != None: return result def max_flow(self, source, sink): path = self.find_path(source, sink, []) while path != None: flow = min(r for u,v,r in path) for u,v,_ in path: self.flow[(u,v)] += flow self.flow[(v,u)] -= flow path = self.find_path(source, sink, []) return sum(self.flow[(source, vertex)] for vertex, capacity in self.get_edges(source)) g = FlowNetwork() map(g.add_vertex, ['s','o','p','q','r','t']) g.add_edge('s','o',3) g.add_edge('s','p',3) g.add_edge('o','p',2) g.add_edge('o','q',3) g.add_edge('p','r',2) g.add_edge('r','t',3) g.add_edge('q','r',4) g.add_edge('q','t',2) print g.max_flow('s','t') [/CODE] result of this example is "5". algorithm find max flow in graph(linked list or whatever) from source vertex "s" to destination "t". Many thanx for any idea

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  • Need advice on C++ coding pattern

    - by Kotti
    Hi! I have a working prototype of a game engine and right now I'm doing some refactoring. What I'm asking for is your opinion on usage of the following C++ coding patterns. I have implemented some trivial algorithms for collision detection and they are implemented the following way: Not shown here - class constructor is made private and using algorithms looks like Algorithm::HandleInnerCollision(...) struct Algorithm { // Private routines static bool is_inside(Point& p, Object& object) { // (...) } public: /** * Handle collision where the moving object should be always * located inside the static object * * @param MovingObject & mobject * @param const StaticObject & sobject * @return void * @see */ static void HandleInnerCollision(MovingObject& mobject, const StaticObject& sobject) { // (...) } So, my question is - somebody advised me to do it "the C++" way - so that all functions are wrapped in a namespace, but not in a class. Is there some good way to preserve privating if I will wrap them into a namespace as adviced? What I want to have is a simple interface and ability to call functions as Algorithm::HandleInnerCollision(...) while not polluting the namespace with other functions such as is_inside(...) Of, if you can advise any alternative design pattern for such kind of logics, I would really appreciate that...

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  • Boost Include Files in VC++

    - by Dr. K
    For the last few years, I have been exclusively a C# developer. Previously, I developed in C++ and have a C++ application that I built about 3 years ago using VS2005. It made extensive use of the Boost libraries. I recently decided to brush off the old app and rebuild it in VS2008 with the latest version of Boost (the latest version with the "easy" installation program from BoostPro Computing), 1.39. Previously when I had the program running I was at 1.33. Also, the last time the program was running was at least 2 OS installations ago. The Boost installation is located on my machine at: "C:\Program Files\boost\boost_1_39". Anyway, I have done the following: Set the project's "Additional Include Directories" directory to "C:\Program Files\boost\boost_1_39" Added "C:\Program Files\boost\boost_1_39" to VS2008's Tools - Options - Projects and Solutions - VC++ Directories - Include Files I have a number of Boost includes in my stdafx.h file. The compiler fails upon attempting to open the first one - #include <boost/algorithm/string/string.hpp> I have confirmed that the above file is indeed located at "C:\Program Files\boost\boost_1_39\boost\algorithm\string\string.hpp" I continue to get: fatal error C1083: Cannot open include file: 'boost/algorithm/string/string.hpp': No such file or directory Any tips on what else to check would be greatly appreciated. Again, this is an application that compiled fine a few years ago, but the source has now been moved to a new machine/compiler.

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