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  • Worse is better. Is there an example?

    - by J.F. Sebastian
    Is there a widely-used algorithm that has time complexity worse than that of another known algorithm but it is a better choice in all practical situations (worse complexity but better otherwise)? An acceptable answer might be in a form: There are algorithms A and B that have O(N**2) and O(N) time complexity correspondingly, but B has such a big constant that it has no advantages over A for inputs less then a number of atoms in the Universe. Examples highlights from the answers: Simplex algorithm -- worst-case is exponential time -- vs. known polynomial-time algorithms for convex optimization problems. A naive median of medians algorithm -- worst-case O(N**2) vs. known O(N) algorithm. Backtracking regex engines -- worst-case exponential vs. O(N) Thompson NFA -based engines. All these examples exploit worst-case vs. average scenarios. Are there examples that do not rely on the difference between the worst case vs. average case scenario? Related: The Rise of ``Worse is Better''. (For the purpose of this question the "Worse is Better" phrase is used in a narrower (namely -- algorithmic time-complexity) sense than in the article) Python's Design Philosophy: The ABC group strived for perfection. For example, they used tree-based data structure algorithms that were proven to be optimal for asymptotically large collections (but were not so great for small collections). This example would be the answer if there were no computers capable of storing these large collections (in other words large is not large enough in this case). Coppersmith–Winograd algorithm for square matrix multiplication is a good example (it is the fastest (2008) but it is inferior to worse algorithms). Any others? From the wikipedia article: "It is not used in practice because it only provides an advantage for matrices so large that they cannot be processed by modern hardware (Robinson 2005)."

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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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  • Interesting articles and blogs on SPARC T4

    - by mv
    Interesting articles and blogs on SPARC T4 processor   I have consolidated all the interesting information I could get on SPARC T4 processor and its hardware cryptographic capabilities.  Hope its useful. 1. Advantages of SPARC T4 processor  Most important points in this T4 announcement are : "The SPARC T4 processor was designed from the ground up for high speed security and has a cryptographic stream processing unit (SPU) integrated directly into each processor core. These accelerators support 16 industry standard security ciphers and enable high speed encryption at rates 3 to 5 times that of competing processors. By integrating encryption capabilities directly inside the instruction pipeline, the SPARC T4 processor eliminates the performance and cost barriers typically associated with secure computing and makes it possible to deliver high security levels without impacting the user experience." Data Sheet has more details on these  : "New on-chip Encryption Instruction Accelerators with direct non-privileged support for 16 industry-standard cryptographic algorithms plus random number generation in each of the eight cores: AES, Camellia, CRC32c, DES, 3DES, DH, DSA, ECC, Kasumi, MD5, RSA, SHA-1, SHA-224, SHA-256, SHA-384, SHA-512" I ran "isainfo -v" command on Solaris 11 Sparc T4-1 system. It shows the new instructions as expected  : $ isainfo -v 64-bit sparcv9 applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc 32-bit sparc applications crc32c cbcond pause mont mpmul sha512 sha256 sha1 md5 camellia kasumi des aes ima hpc vis3 fmaf asi_blk_init vis2 vis popc v8plus div32 mul32  2.  Dan Anderson's Blog have some interesting points about how these can be used : "New T4 crypto instructions include: aes_kexpand0, aes_kexpand1, aes_kexpand2,         aes_eround01, aes_eround23, aes_eround01_l, aes_eround_23_l, aes_dround01, aes_dround23, aes_dround01_l, aes_dround_23_l.       Having SPARC T4 hardware crypto instructions is all well and good, but how do we access it ?      The software is available with Solaris 11 and is used automatically if you are running Solaris a SPARC T4.  It is used internally in the kernel through kernel crypto modules.  It is available in user space through the PKCS#11 library." 3.   Dans' Blog on Where's the Crypto Libraries? Although this was written in 2009 but still is very useful  "Here's a brief tour of the major crypto libraries shown in the digraph:   The libpkcs11 library contains the PKCS#11 API (C_\*() functions, such as C_Initialize()). That in turn calls library pkcs11_softtoken or pkcs11_kernel, for userland or kernel crypto providers. The latter is used mostly for hardware-assisted cryptography (such as n2cp for Niagara2 SPARC processors), as that is performed more efficiently in kernel space with the "kCF" module (Kernel Crypto Framework). Additionally, for Solaris 10, strong crypto algorithms were split off in separate libraries, pkcs11_softtoken_extra libcryptoutil contains low-level utility functions to help implement cryptography. libsoftcrypto (OpenSolaris and Solaris Nevada only) implements several symmetric-key crypto algorithms in software, such as AES, RC4, and DES3, and the bignum library (used for RSA). libmd implements MD5, SHA, and SHA2 message digest algorithms" 4. Difference in T3 and T4 Diagram in this blog is good and self explanatory. Jeff's blog also highlights the differences  "The T4 servers have improved crypto acceleration, described at https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine. It is "just built in" so administrators no longer have to assign crypto accelerator units to domains - it "just happens". Every physical or virtual CPU on a SPARC-T4 has full access to hardware based crypto acceleration at all times. .... For completeness sake, it's worth noting that the T4 adds more crypto algorithms, and accelerates Camelia, CRC32c, and more SHA-x." 5. About performance counters In this blog, performance counters are explained : "Note that unlike T3 and before, T4 crypto doesn't require kernel modules like ncp or n2cp, there is no visibility of crypto hardware with kstats or cryptoadm. T4 does provide hardware counters for crypto operations.  You can see these using cpustat: cpustat -c pic0=Instr_FGU_crypto 5 You can check the general crypto support of the hardware and OS with the command "isainfo -v". Since T4 crypto's implementation now allows direct userland access, there are no "crypto units" visible to cryptoadm.  " For more details refer Martin's blog as well. 6. How to turn off  SPARC T4 or Intel AES-NI crypto acceleration  I found this interesting blog from Darren about how to turn off  SPARC T4 or Intel AES-NI crypto acceleration. "One of the new Solaris 11 features of the linker/loader is the ability to have a single ELF object that has multiple different implementations of the same functions that are selected at runtime based on the capabilities of the machine.   The alternate to this is having the application coded to call getisax(2) system call and make the choice itself.  We use this functionality of the linker/loader when we build the userland libraries for the Solaris Cryptographic Framework (specifically libmd.so and libsoftcrypto.so) The Solaris linker/loader allows control of a lot of its functionality via environment variables, we can use that to control the version of the cryptographic functions we run.  To do this we simply export the LD_HWCAP environment variable with values that tell ld.so.1 to not select the HWCAP section matching certain features even if isainfo says they are present.  This will work for consumers of the Solaris Cryptographic Framework that use the Solaris PKCS#11 libraries or use libmd.so interfaces directly.  For SPARC T4 : export LD_HWCAP="-aes -des -md5 -sha256 -sha512 -mont -mpul" .. For Intel systems with AES-NI support: export LD_HWCAP="-aes"" Note that LD_HWCAP is explained in  http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html "LD_HWCAP, LD_HWCAP_32, and LD_HWCAP_64 -  Identifies an alternative hardware capabilities value... A “-” prefix results in the capabilities that follow being removed from the alternative capabilities." 7. Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing This Whitepaper on SPARC T4 Servers—Optimized for End-to-End Data Center Computing explains more details.  It has DTrace scripts which may come in handy : "To ensure the hardware-assisted cryptographic acceleration is configured to use and working with the security scenarios, it is recommended to use the following Solaris DTrace script. #!/usr/sbin/dtrace -s pid$1:libsoftcrypto:yf*:entry, pid$target:libsoftcrypto:rsa*:entry, pid$1:libmd:yf*:entry { @[probefunc] = count(); } tick-1sec { printa(@ops); trunc(@ops); }" Note that I have slightly modified the D Script to have RSA "libsoftcrypto:rsa*:entry" as well as per recommendations from Chi-Chang Lin. 8. References http://www.oracle.com/us/corporate/features/sparc-t4-announcement-494846.html http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-1-ds-487858.pdf https://blogs.oracle.com/DanX/entry/sparc_t4_openssl_engine https://blogs.oracle.com/DanX/entry/where_s_the_crypto_libraries https://blogs.oracle.com/darren/entry/howto_turn_off_sparc_t4 http://docs.oracle.com/cd/E23823_01/html/816-5165/ld.so.1-1.html   https://blogs.oracle.com/hardware/entry/unleash_the_power_of_cryptography https://blogs.oracle.com/cmt/entry/t4_crypto_cheat_sheet https://blogs.oracle.com/martinm/entry/t4_performance_counters_explained  https://blogs.oracle.com/jsavit/entry/no_mau_required_on_a http://www.oracle.com/us/products/servers-storage/servers/sparc-enterprise/t-series/sparc-t4-business-wp-524472.pdf

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  • Algorithm shortest path between all points

    - by Jeroen
    Hi, suppose I have 10 points. I know the distance between each point. I need to find the shortest possible route passing trough all points. I have tried a couple of algorithms (Dijkstra, Floyd Warshall,...) and the all give me the shortest path between start and end, but they don't make a route with all points on it. Permutations work fine, but they are to resource expensive. What algorithms can you advise me to look into for this problem? Or is there a documented way to do this with the above mentioned algorithms? Tnx Jeroen

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  • Algorithm and data structure learning resources for dynamic programming

    - by Pranav
    Im learning dynamic programming now, and while I know the theory well, designing DP algorithms for new problems is still difficult. This is what i would really like now- A book or a website, which poses a problem which can be solved by dynamic programming. Also there is the solution with an explanation available, which i would like to see if i cant solve the problem even after butting my head at it for a few hours. Is there some resource that provides this sort of a thing for several categories of algorithms- like graph algorithms, dynamic programming, etc? P.S. I considered Topcoder, but the solutions there are not really appropriate for learning to implement efficient solutions.

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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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  • Practical non-Turing-complete languages?

    - by Kyle Cronin
    Nearly all programming languages used are Turing Complete, and while this affords the language to represent any computable algorithm, it also comes with its own set of problems. Seeing as all the algorithms I write are intended to halt, I would like to be able to represent them in a language that guarantees they will halt. Regular expressions used for matching strings and finite state machines are used when lexing, but I'm wondering if there's a more general, broadly language that's not Turing complete? edit: I should clarify, by 'general purpose' I don't necessarily want to be able to write all halting algorithms in the language (I don't think that such a language would exist) but I suspect that there are common threads in halting proofs that can be generalized to produce a language in which all algorithms are guaranteed to halt. There's also another way to tackle this problem - eliminate the need for theoretically infinite memory. Once you limit the amount of memory the machine is allowed, the number of states the machine is in is finite and countable, and therefore you can determine if the algorithm will halt (by not allowing the machine to move into a state it's been in before).

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  • Finding recurrence relations of an algorithm

    - by Roarke
    I'm reading my algorithms text book, and I'm reading about recurrence relations and finding the algorithms big O complexity. I run across this line "In the case of the merge-sort algorithm, we get the recurrence equation: t(n) = b if n < 2 = 2t(n/2) +bn if n >= 2 for b > 0 my response was "how the heck did we know that?!?!" So i'm wondering if there is a systematic approach, or just a logical way of getting these recurrence relations from the algorithms can some one explain where the b and the two 2's come from?

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  • Genetic programming in c++, library suggestions?

    - by shuttle87
    I'm looking to add some genetic algorithms to an Operations research project I have been involved in. Currently we have a program that aids in optimizing some scheduling and we want to add in some heuristics in the form of genetic algorithms. Are there any good libraries for generic genetic programming/algorithms in c++? Or would you recommend I just code my own? I should add that while I am not new to c++ I am fairly new to doing this sort of mathematical optimization work in c++ as the group I worked with previously had tended to use a proprietary optimization package. We have a fitness function that is fairly computationally intensive to evaluate and we have a cluster to run this on so parallelized code is highly desirable. So is c++ a good language for this? If not please recommend some other ones as I am willing to learn another language if it makes life easier. thanks!

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  • Thread Local Memory for Scratch Memory.

    - by Hassan Syed
    I am using Protocol Buffers and OpensSSL to generate, HMACs and then CBC encrypt the two fields to obfuscate the session cookies -- similar Kerberos tokens. Protocol Buffers' API communicates with std::strings and has a buffer caching mechanism; I exploit the caching mechanism, for successive calls in the the same thread, by placing it in thread local memory; additionally the OpenSSL HMAC and EVP CTX's are also placed in the same thread local memory structure ( see this question for some detail on why I use thread local memory and the massive amount of speedup it enables even with a single thread). The generation and deserialization, "my algorithms", of these cookie strings uses intermediary void *s and std::strings and since Protocol Buffers has an internal memory retention mechanism I want these characteristics for "my algorithms". So how do I implement a common scratch memory ? I don't know much about the rdbuf of the std::string object. I would presumeably need to grow it to the lowest common size ever encountered during the execution of "my algorithms". Thoughts ?

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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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  • Programming cookbook? [closed]

    - by user73669
    Possible Duplicate: What is the single most influential book every programmer should read? Hello With sites like The Daily WTF and recurring threads on Slashdot and elsewhere about bad programming, I figured that, to avoid people reinventing the wheel (badly or not), there should be a good, fat book on programming that would go through typical programming problems and show good, known algorithms, either in pseudo-code or some language with an easy syntax so that the language is not an issue. Here's the list of books on the subject I saw at my local computer bookstore. Can you recommend a couple, or add to this list if it's missing better options? The art of computer programming Code complete Masterminds of programming 97 things every programmer should know The passionate programmer Pragmatic thinking & learning Coders at work The algorithm design manual Algorithms and programming How to think about algorithms How to think like a programmer Why programs fail Beautiful data Beautiful code The productive programmer Solid code Write great code Clean code Programming language pragmatics Hello world Learning Processing Learn to program Thank you.

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  • Enumerating combinations in a distributed manner

    - by Reyzooti
    I have a problem where I must analyse 500C5 combinations (255244687600) of something. Distributing it over a 10 node cluster where each cluster processes roughly 10^6 combinations per second means the job will be complete in about 7hours. The problem I have is distributing the 255244687600 combinations over the 10 nodes. I'd like to present each node with 25524468760, however the algorithms I'm using can only produce the combinations sequentially, I'd like to be able to pass the set of elements and a range of combination indicies eg: [0-10^7) or [10^7,2.0 10^7) etc and have the nodes themselves figure out the combinations. The algorithms I'm using at the moment are from the following: http://home.roadrunner.com/~hinnant/combinations.html A logical question I've considered using a master node, that enumerates each of the combinations and sends work to each of the nodes, however the overhead incurred in iterating the combinations from a single node and communicating back and forth work is enormous, and will subsequently lead to the master node becoming the bottleneck. Are there any good combination iterating algorithms geared up for efficient/optimal distributed enumeration?

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  • Which parallel sorting algorithm has the best average case performance?

    - by Craig P. Motlin
    Sorting takes O(n log n) in the serial case. If we have O(n) processors we would hope for a linear speedup. O(log n) parallel algorithms exist but they have a very high constant. They also aren't applicable on commodity hardware which doesn't have anywhere near O(n) processors. With p processors, reasonable algorithms should take O(n/p log n/p) time. In the serial case, quick sort has the best runtime complexity on average. A parallel quick sort algorithm is easy to implement (see here and here). However it doesn't perform well since the very first step is to partition the whole collection on a single core. I have found information on many parallel sort algorithms but so far I have not seen anything pointing to a clear winner. I'm looking to sort lists of 1 million to 100 million elements in a JVM language running on 8 to 32 cores.

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  • Subaru Starts Thinking about their Path to Fusion Applications

    Brian Simmermon, VP and CIO, Subaru of America, and a member of Oracle's Fusion Strategy Council explains how Subaru is aligning their business and IT strategy to improve sales through Siebel and EBS, and is looking at implementing Fusion Technologies such as BPEL, AIA and Enterprise Manager to begin their evolutionary path to Fusion.

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  • Evolving Architectures Part I Whats Software Architecture

    Im writing a short series of posts for MS Israel MCS blog (in Hebrew) and Id thought Id translate them to English, as it seems to me they are interesting enough.In this series I am going to talk about Evolutionary Architecture or , some of the aspect of dealing with software architecture [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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  • L'apprentissage continu serait l'élément clé du succès des méthodes agiles, selon une fondatrice d'Agile Leadership Network

    L'apprentissage continu serait l'élément clé du succès des méthodes agiles ! selon la cofondatrice d'Agile Leadership NetworkAh ce cher jeunot d'Agile, il n'en finit pas de faire parler de lui et une chose est sûre, chacun y va avec sa propre vision. Pour certains, il se résume à flexibilité, pour d'autres, il serait discipliné ou bien encore adaptatif.Toutefois, ne serait-il pas caractérisé en premier lieu par l'apprentissage continu ? C'est ce que note Pollyanna Pixton, présidente d'Evolutionary...

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  • Non-perfect maze generation algorithm

    - by Shylux
    I want to generate a maze with the following properties: The maze is non-perfect. Means it has loops and multiple ways to reach the exit. The maze should be random. The algorithm should output different mazes for different input parameters The maze doesn't have to be braided. Means dead-ends are allowed and appreciated. I just can't find the right resources on google. The closest i found was this description of the different types of algorithms: http://www.astrolog.org/labyrnth/algrithm.htm. All other algorithms were for perfect mazes. Can anyone give me a website where i can look this up or maybe an algorithm directly?

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  • HPC Server Dynamic Job Scheduling: when jobs spawn jobs

    - by JoshReuben
    HPC Job Types HPC has 3 types of jobs http://technet.microsoft.com/en-us/library/cc972750(v=ws.10).aspx · Task Flow – vanilla sequence · Parametric Sweep – concurrently run multiple instances of the same program, each with a different work unit input · MPI – message passing between master & slave tasks But when you try go outside the box – job tasks that spawn jobs, blocking the parent task – you run the risk of resource starvation, deadlocks, and recursive, non-converging or exponential blow-up. The solution to this is to write some performance monitoring and job scheduling code. You can do this in 2 ways: manually control scheduling - allocate/ de-allocate resources, change job priorities, pause & resume tasks , restrict long running tasks to specific compute clusters Semi-automatically - set threshold params for scheduling. How – Control Job Scheduling In order to manage the tasks and resources that are associated with a job, you will need to access the ISchedulerJob interface - http://msdn.microsoft.com/en-us/library/microsoft.hpc.scheduler.ischedulerjob_members(v=vs.85).aspx This really allows you to control how a job is run – you can access & tweak the following features: max / min resource values whether job resources can grow / shrink, and whether jobs can be pre-empted, whether the job is exclusive per node the creator process id & the job pool timestamp of job creation & completion job priority, hold time & run time limit Re-queue count Job progress Max/ min Number of cores, nodes, sockets, RAM Dynamic task list – can add / cancel jobs on the fly Job counters When – poll perf counters Tweaking the job scheduler should be done on the basis of resource utilization according to PerfMon counters – HPC exposes 2 Perf objects: Compute Clusters, Compute Nodes http://technet.microsoft.com/en-us/library/cc720058(v=ws.10).aspx You can monitor running jobs according to dynamic thresholds – use your own discretion: Percentage processor time Number of running jobs Number of running tasks Total number of processors Number of processors in use Number of processors idle Number of serial tasks Number of parallel tasks Design Your algorithms correctly Finally , don’t assume you have unlimited compute resources in your cluster – design your algorithms with the following factors in mind: · Branching factor - http://en.wikipedia.org/wiki/Branching_factor - dynamically optimize the number of children per node · cutoffs to prevent explosions - http://en.wikipedia.org/wiki/Limit_of_a_sequence - not all functions converge after n attempts. You also need a threshold of good enough, diminishing returns · heuristic shortcuts - http://en.wikipedia.org/wiki/Heuristic - sometimes an exhaustive search is impractical and short cuts are suitable · Pruning http://en.wikipedia.org/wiki/Pruning_(algorithm) – remove / de-prioritize unnecessary tree branches · avoid local minima / maxima - http://en.wikipedia.org/wiki/Local_minima - sometimes an algorithm cant converge because it gets stuck in a local saddle – try simulated annealing, hill climbing or genetic algorithms to get out of these ruts   watch out for rounding errors – http://en.wikipedia.org/wiki/Round-off_error - multiple iterations can in parallel can quickly amplify & blow up your algo ! Use an epsilon, avoid floating point errors,  truncations, approximations Happy Coding !

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  • Does Google use any “Language” flags / tags set within a PDF file when determining its language?

    - by Ally Ak
    When determining the language of a HTML page, I understand that Google looks at any language declarations that the page owner has set, and then also applies its own language detection algorithms. But does Google similarly look at language meta data set in PDF files when determining a PDF file's language? (Authors of PDF files can set document-wide properties describing the language (or languages) contained within it.) Or does Google rely exclusively on language detection algorithms and disregard the language flag set within the PDF file? Can anyone shed any light?

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  • Gilda Garretón, a Java Developer and Parallelism Computing Researcher

    - by Yolande
    In a new interview titled “Gilda Garretón, a Java Developer and Parallelism Computing Research,” Garretón shares her first-hand experience developing with Java and Java 7 for very large-scale integration (VLSI) of computer-aided design (CAD). Garretón gives an insightful overview of how Java is contributing to the parallelism development and to the Electric VLSI Design Systems, an open source VLSI CAD application used as a research platform for new CAD algorithms as well as the research flow for hardware test chips.  Garretón considers that parallelism programming is hard and complex, yet important developments are taking place.  "With the addition of the concurrent package in Java SE 6 and the Fork/Join feature in Java SE 7, developers have a chance to rely more on existing frameworks and dedicate more time to the essence of their parallel algorithms." Read the full article here  

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  • Pathfinding Java library

    - by Shivan Dragon
    I'm an amateur game developer and somewhat amateur Java developer as well. I'm trying to find a way to have path finding for my game(s). I've first googled for some existing Java libraries that have various path-finding implementations, but I've failed to find any. It seems to me that the only way to get pathfinding code is to use it via a game engine (like Unity). But I'd just like to have a library that I can use and make the game loop and other stuff on my own. Failing to find such a library I've tried implementing some algorithms myself. I've managed to make a running AStar in Java, but for fancier stuff like DStar I find it hard to do it by hand. So then, my question is, are there any Java libraries that contain at least some basic pathfinding algorithms implementations?

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  • Modified Strategy Design Pattern

    - by Samuel Walker
    I've started looking into Design Patterns recently, and one thing I'm coding would suit the Strategy pattern perfectly, except for one small difference. Essentially, some (but not all) of my algorithms, need an extra parameter or two passed to them. So I'll either need to pass them an extra parameter when I invoke their calculate method or store them as variables inside the ConcreteAlgorithm class, and be able to update them before I call the algorithm. Is there a design pattern for this need / How could I implement this while sticking to the Strategy Pattern? I've considered passing the client object to all the algorithms, and storing the variables in there, then using that only when the particular algorithm needs it. However, I think this is both unwieldy, and defeats the point of the strategy pattern. Just to be clear I'm implementing in Java, and so don't have the luxury of optional parameters (which would solve this nicely).

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  • Stack vs queue -based programming language efficiency [closed]

    - by Core Xii
    Suppose there are two programming languages; one where the only form of storage is one (preferred) or two (may be required for Turing-completeness) stacks, and another where the only form of storage is a single queue, with appropriate instructions in each to manipulate their respective storage to achieve Turing-completeness. Which one can more efficiently encode complex algorithms? Such that most given algorithms take less code to implement, less time to compute and less memory to do so. Also, how do they compare to a language with a traditional array (or unbounded tape, if you will) as storage?

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  • Pathfinding library

    - by Shivan Dragon
    I'm an amateur game developer and somewhat amateur Java developer as well. I'm trying to find a way to have path finding for my game(s). I've first Googled for some existing Java libraries that have various path-finding implementations, but I've failed to find any. It seems to me that the only way to get pathfinding code is to use it via a game engine (like Unity). But I'd just like to have a library that I can use and make the game loop and other stuff on my own. Failing to find such a library I've tried implementing some algorithms myself. I've managed to make a running A* in Java, but for fancier stuff like D* I find it hard to do it by hand. So then, my question is, are there any Java libraries that contain at least some basic pathfinding algorithms implementations?

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