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  • How to ramp up my data structures skills after a long hibernation

    - by Anon
    I was pretty good with algorithms and data structures once, a long long time ago. Since then, I programmed professionally, and then went to manage a small team, which totally shot my tech skills in this field back. I've decided I want to be a developer again, and work for Google. The thing is, I'm so out of practice, that if I were to be interviewed right now I would surely flunk out in 10 minutes. What training program would you recommend for me to get back into shape? I already started this weekend by going back to the absolute basics and implementing a few sort algorithms, linked list, and hash table. Next, I think I'll read through the entire course material on the other basic data structures and graph algorithms. I want to find a focused set of practical exercises I can do in a relatively short amount of time, to juggle the old brain cells. I know this stuff - I just need to remind myself that I know it.

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  • Abstracting functionality

    - by Ralf Westphal
    Originally posted on: http://geekswithblogs.net/theArchitectsNapkin/archive/2014/08/22/abstracting-functionality.aspxWhat is more important than data? Functionality. Yes, I strongly believe we should switch to a functionality over data mindset in programming. Or actually switch back to it. Focus on functionality Functionality once was at the core of software development. Back when algorithms were the first thing you heard about in CS classes. Sure, data structures, too, were important - but always from the point of view of algorithms. (Niklaus Wirth gave one of his books the title “Algorithms + Data Structures” instead of “Data Structures + Algorithms” for a reason.) The reason for the focus on functionality? Firstly, because software was and is about doing stuff. Secondly because sufficient performance was hard to achieve, and only thirdly memory efficiency. But then hardware became more powerful. That gave rise to a new mindset: object orientation. And with it functionality was devalued. Data took over its place as the most important aspect. Now discussions revolved around structures motivated by data relationships. (John Beidler gave his book the title “Data Structures and Algorithms: An Object Oriented Approach” instead of the other way around for a reason.) Sure, this data could be embellished with functionality. But nevertheless functionality was second. When you look at (domain) object models what you mostly find is (domain) data object models. The common object oriented approach is: data aka structure over functionality. This is true even for the most modern modeling approaches like Domain Driven Design. Look at the literature and what you find is recommendations on how to get data structures right: aggregates, entities, value objects. I´m not saying this is what object orientation was invented for. But I´m saying that´s what I happen to see across many teams now some 25 years after object orientation became mainstream through C++, Delphi, and Java. But why should we switch back? Because software development cannot become truly agile with a data focus. The reason for that lies in what customers need first: functionality, behavior, operations. To be clear, that´s not why software is built. The purpose of software is to be more efficient than the alternative. Money mainly is spent to get a certain level of quality (e.g. performance, scalability, security etc.). But without functionality being present, there is nothing to work on the quality of. What customers want is functionality of a certain quality. ASAP. And tomorrow new functionality needs to be added, existing functionality needs to be changed, and quality needs to be increased. No customer ever wanted data or structures. Of course data should be processed. Data is there, data gets generated, transformed, stored. But how the data is structured for this to happen efficiently is of no concern to the customer. Ask a customer (or user) whether she likes the data structured this way or that way. She´ll say, “I don´t care.” But ask a customer (or user) whether he likes the functionality and its quality this way or that way. He´ll say, “I like it” (or “I don´t like it”). Build software incrementally From this very natural focus of customers and users on functionality and its quality follows we should develop software incrementally. That´s what Agility is about. Deliver small increments quickly and often to get frequent feedback. That way less waste is produced, and learning can take place much easier (on the side of the customer as well as on the side of developers). An increment is some added functionality or quality of functionality.[1] So as it turns out, Agility is about functionality over whatever. But software developers’ thinking is still stuck in the object oriented mindset of whatever over functionality. Bummer. I guess that (at least partly) explains why Agility always hits a glass ceiling in projects. It´s a clash of mindsets, of cultures. Driving software development by demanding small increases in functionality runs against thinking about software as growing (data) structures sprinkled with functionality. (Excuse me, if this sounds a bit broad-brush. But you get my point.) The need for abstraction In the end there need to be data structures. Of course. Small and large ones. The phrase functionality over data does not deny that. It´s not functionality instead of data or something. It´s just over, i.e. functionality should be thought of first. It´s a tad more important. It´s what the customer wants. That´s why we need a way to design functionality. Small and large. We need to be able to think about functionality before implementing it. We need to be able to reason about it among team members. We need to be able to communicate our mental models of functionality not just by speaking about them, but also on paper. Otherwise reasoning about it does not scale. We learned thinking about functionality in the small using flow charts, Nassi-Shneiderman diagrams, pseudo code, or UML sequence diagrams. That´s nice and well. But it does not scale. You can use these tools to describe manageable algorithms. But it does not work for the functionality triggered by pressing the “1-Click Order” on an amazon product page for example. There are several reasons for that, I´d say. Firstly, the level of abstraction over code is negligible. It´s essentially non-existent. Drawing a flow chart or writing pseudo code or writing actual code is very, very much alike. All these tools are about control flow like code is.[2] In addition all tools are computationally complete. They are about logic which is expressions and especially control statements. Whatever you code in Java you can fully (!) describe using a flow chart. And then there is no data. They are about control flow and leave out the data altogether. Thus data mostly is assumed to be global. That´s shooting yourself in the foot, as I hope you agree. Even if it´s functionality over data that does not mean “don´t think about data”. Right to the contrary! Functionality only makes sense with regard to data. So data needs to be in the picture right from the start - but it must not dominate the thinking. The above tools fail on this. Bottom line: So far we´re unable to reason in a scalable and abstract manner about functionality. That´s why programmers are so driven to start coding once they are presented with a problem. Programming languages are the only tool they´ve learned to use to reason about functional solutions. Or, well, there might be exceptions. Mathematical notation and SQL may have come to your mind already. Indeed they are tools on a higher level of abstraction than flow charts etc. That´s because they are declarative and not computationally complete. They leave out details - in order to deliver higher efficiency in devising overall solutions. We can easily reason about functionality using mathematics and SQL. That´s great. Except for that they are domain specific languages. They are not general purpose. (And they don´t scale either, I´d say.) Bummer. So to be more precise we need a scalable general purpose tool on a higher than code level of abstraction not neglecting data. Enter: Flow Design. Abstracting functionality using data flows I believe the solution to the problem of abstracting functionality lies in switching from control flow to data flow. Data flow very naturally is not about logic details anymore. There are no expressions and no control statements anymore. There are not even statements anymore. Data flow is declarative by nature. With data flow we get rid of all the limiting traits of former approaches to modeling functionality. In addition, nomen est omen, data flows include data in the functionality picture. With data flows, data is visibly flowing from processing step to processing step. Control is not flowing. Control is wherever it´s needed to process data coming in. That´s a crucial difference and needs some rewiring in your head to be fully appreciated.[2] Since data flows are declarative they are not the right tool to describe algorithms, though, I´d say. With them you don´t design functionality on a low level. During design data flow processing steps are black boxes. They get fleshed out during coding. Data flow design thus is more coarse grained than flow chart design. It starts on a higher level of abstraction - but then is not limited. By nesting data flows indefinitely you can design functionality of any size, without losing sight of your data. Data flows scale very well during design. They can be used on any level of granularity. And they can easily be depicted. Communicating designs using data flows is easy and scales well, too. The result of functional design using data flows is not algorithms (too low level), but processes. Think of data flows as descriptions of industrial production lines. Data as material runs through a number of processing steps to be analyzed, enhances, transformed. On the top level of a data flow design might be just one processing step, e.g. “execute 1-click order”. But below that are arbitrary levels of flows with smaller and smaller steps. That´s not layering as in “layered architecture”, though. Rather it´s a stratified design à la Abelson/Sussman. Refining data flows is not your grandpa´s functional decomposition. That was rooted in control flows. Refining data flows does not suffer from the limits of functional decomposition against which object orientation was supposed to be an antidote. Summary I´ve been working exclusively with data flows for functional design for the past 4 years. It has changed my life as a programmer. What once was difficult is now easy. And, no, I´m not using Clojure or F#. And I´m not a async/parallel execution buff. Designing the functionality of increments using data flows works great with teams. It produces design documentation which can easily be translated into code - in which then the smallest data flow processing steps have to be fleshed out - which is comparatively easy. Using a systematic translation approach code can mirror the data flow design. That way later on the design can easily be reproduced from the code if need be. And finally, data flow designs play well with object orientation. They are a great starting point for class design. But that´s a story for another day. To me data flow design simply is one of the missing links of systematic lightweight software design. There are also other artifacts software development can produce to get feedback, e.g. process descriptions, test cases. But customers can be delighted more easily with code based increments in functionality. ? No, I´m not talking about the endless possibilities this opens for parallel processing. Data flows are useful independently of multi-core processors and Actor-based designs. That´s my whole point here. Data flows are good for reasoning and evolvability. So forget about any special frameworks you might need to reap benefits from data flows. None are necessary. Translating data flow designs even into plain of Java is possible. ?

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  • Design for a machine learning artificial intelligence framework

    - by Lirik
    This is a community wiki which aims to provide a good design for a machine learning/artificial intelligence framework (ML/AI framework). Please contribute to the design of a language-agnostic framework which would allow multiple ML/AI algorithms to be plugged into a single framework which: runs the algorithms with a user-specified data set. facilitates learning, qualification, and classification. allows users to easily plug in new algorithms. can aggregate or create an ensemble of the existing algorithms. can save/load the progress of the algorithm (i.e. save the network and weights of a neural network, save the tree of a decision tree, etc.). What is a good design for this sort of ML/AI framework?

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  • Design for a machine learning artificial intelligence framework (community wiki)

    - by Lirik
    This is a community wiki which aims to provide a good design for a machine learning/artificial intelligence framework (ML/AI framework). Please contribute to the design of a language-agnostic framework which would allow multiple ML/AI algorithms to be plugged into a single framework which: runs the algorithms with a user-specified data set. facilitates learning, qualification, and classification. allows users to easily plug in new algorithms. can aggregate or create an ensemble of the existing algorithms. can save/load the progress of the algorithm (i.e. save the network and weights of a neural network, save the tree of a decision tree, etc.). What is a good design for this sort of ML/AI framework?

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  • Advice on String Similarity Metrics (Java). Distance, sounds like or combo?

    - by andreas
    Hello, A part of a process requires to apply String Similarity Algorithms. The results of this process will be stored and produce lets say SS_Dataset. Based on this Dataset, further decisions will have to be made. My questions are: Should i apply one or more string similarity algorithms to produce SS_Dataset ? Any comparisons between algorithms that calculate the 'distance' and the 'Sounds Like' similarity ? Does one family of algorithms produces more accurate results over the other? Does a combination give more accurate results on similarity? Can you recommend implementations that you have worked with? My implementation will include packages from the following libraries http://www.dcs.shef.ac.uk/~sam/simmetrics.html http://jtmt.sourceforge.net/ Regards,

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  • Good Java graph algorithm library?

    - by Nick Fortescue
    Has anyone had good experiences with any Java libraries for Graph algorithms. I've tried JGraph and found it ok, and there are a lot of different ones in google. Are there any that people are actually using successfully in production code or would recommend? To clarify, I'm not looking for a library that produces graphs/charts, I'm looking for one that helps with Graph algorithms, eg minimum spanning tree, Kruskal's algorithm Nodes, Edges, etc. Ideally one with some good algorithms/data structures in a nice Java OO API.

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  • How do people prove the correctness of Computer Vision methods?

    - by solvingPuzzles
    I'd like to pose a few abstract questions about computer vision research. I haven't quite been able to answer these questions by searching the web and reading papers. How does someone know whether a computer vision algorithm is correct? How do we define "correct" in the context of computer vision? Do formal proofs play a role in understanding the correctness of computer vision algorithms? A bit of background: I'm about to start my PhD in Computer Science. I enjoy designing fast parallel algorithms and proving the correctness of these algorithms. I've also used OpenCV from some class projects, though I don't have much formal training in computer vision. I've been approached by a potential thesis advisor who works on designing faster and more scalable algorithms for computer vision (e.g. fast image segmentation). I'm trying to understand the common practices in solving computer vision problems.

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  • Is it possible to predict future using machine learning and/or AI?

    - by Shekhar
    Recently I have started reading about machine learning. From 3000 feet view, machine learning seems really great thing but as if now I have found that machine learning is limited to only 3 types of algorithms namely classification, clustering and recommendations. I would like to know if my assumption about types of machine learning algorithms is correct or not and What is the extreme thing which we can do using machine learning and/or AI? Is it possible to predict future (same way we predict weather) using AI and/or machine learning?

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  • Algorithm for approximating sihlouette image as polygon

    - by jack
    I want to be able to analyze a texture in real time and approximate a polygon to represent a silhouette. Imagine a person standing in front of a green screen and I want to approximately trace around their outline and get a 2D polygon as the result. Are there algorithms to do this and are they fast enough to work frame-to-frame in a game? (I have found algorithms to triangulate polygons, but I am having trouble knowing what to search for that describes my goal.)

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  • SEO, SEM Tools

    Search engine optimization allows you to optimize your website and get the traffic. The search engines have complicated algorithms. The search engines use these algorithms to rank the websites.

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  • Scaling Down Pixel Art?

    - by Michael Stum
    There's plenty of algorithms to scale up pixel art (I prefer hqx personally), but are there any notable algorithms to scale it down? In my case, the game is designed to run at 1280x720, but if someone plays at a lower resolution I want it to still look good. Most Pixel Art discussions center around 320x200 or 640x480 and upscaling for use in console emulators, but I wonder how modern 2D games like the Monkey Island Remake look good on lower resolutions? (Ignoring the options of having multiple versions of assets (essentially, mipmapping))

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  • Isn't MVC anti OOP?

    - by m3th0dman
    The main idea behind OOP is to unify data and behavior in a single entity - the object. In procedural programming there is data and separately algorithms modifying the data. In the Model-View-Controller pattern the data and the logic/algorithms are placed in distinct entities, the model and the controller respectively. In an equivalent OOP approach shouldn't the model and the controller be placed in the same logical entity?

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  • Best way to implement an AI for Dominion? [on hold]

    - by j will
    I'm creating a desktop client and server backend for the game, Dominion, by Donald X. Vaccarino. I've been reading up on AI techniques and algorithms and I just wanted to what is the best way to implement an AI for such a game? Would it better to look at neural networks, genetic algorithms, decision trees, fuzzy logic, or any other methodology? For those who do not know how Dominion works, check out this part of the wikipedia article: http://en.wikipedia.org/wiki/Dominion_(card_game)#Gameplay

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  • ignoring informational payload, type INVALID_COOKIE msgid=00000000

    - by user197279
    I'm configuring a site-to-site vpn between openswan ipsec and cisco asa 5540. After the step, i started ipesc service but the error i'm seeing is: ignoring informational payload, type INVALID_COOKIE msgid=00000000 Nov 5 09:42:30 pluto[11712]: "myVPN" #1: received and ignored informational message Nov 5 09:42:51 pluto[11712]: "myVPN" #1: ignoring informational payload, type INVALID_COOKIE msgid=00000000 Nov 5 09:42:51 pluto[11712]: "myVPN" #1: received and ignored informational message Nov 5 09:43:30 pluto[11712]: "myVPN" #1: max number of retransmissions (2) reached STATE_MAIN_I2 Nov 5 09:43:30 pluto[11712]: "myVPN" #1: starting keying attempt 2 of at most 3 Any advise why I'm getting this error on openswan? Also sudo ipsec whack --status gives: "myVPN": 10.0.xx.0/24===10.0.7x.x[54.209.y.yyy,+S=C]---10.0.xx.x...10.0.70.x---41.22x.4.xx<41.22x.4.xx[+S=C]===41.22y.4.yyy/32; unrouted; eroute owner: #0 000 "myVPN": myip=54.209.zz.zz; hisip=unset; 000 "myVPN": ike_life: 86400s; ipsec_life: 28800s; rekey_margin: 540s; rekey_fuzz: 100%; keyingtries: 3 000 "myVPN": policy: PSK+ENCRYPT+TUNNEL+DONTREKEY+UP+IKEv2ALLOW+SAREFTRACK+lKOD+rKOD; prio: 24,32; interface: eth0; 000 "myVPN": newest ISAKMP SA: #0; newest IPsec SA: #0; 000 "myVPN": IKE algorithms wanted: AES_CBC(7)_256-SHA1(2)_000-MODP1024(2); flags=-strict 000 "myVPN": IKE algorithms found: AES_CBC(7)_256-SHA1(2)_160-MODP1024(2) 000 "myVPN": ESP algorithms wanted: AES(12)_256-SHA1(2)_000; flags=-strict 000 "myVPN": ESP algorithms loaded: AES(12)_256-SHA1(2)_160 000 000 #5: "myVPN":500 STATE_MAIN_I2 (sent MI2, expecting MR2); EVENT_RETRANSMIT in 8s; nodpd; idle; import:admin initiate 000 #5: pending Phase 2 for "myVPN" replacing #0 Thanks.

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  • List of resources for database continuous integration

    - by David Atkinson
    Because there is so little information on database continuous integration out in the wild, I've taken it upon myself to aggregate as much as possible and post the links to this blog. Because it's my area of expertise, this will focus on SQL Server and Red Gate tooling, although I am keen to include any quality articles that discuss the topic in general terms. Please let me know if you find a resource that I haven't listed! General database Continuous Integration · What is Database Continuous Integration? (David Atkinson) · Continuous Integration for SQL Server Databases (Troy Hunt) · Installing NAnt to drive database continuous integration (David Atkinson) · Continuous Integration Tip #3 - Version your Databases as part of your automated build (Doug Rathbone) · How the "migrations" approach makes database continuous integration possible (David Atkinson) · Continuous Integration for the Database (Keith Bloom) Setting up Continuous Integration with Red Gate tools · Continuous integration for databases using Red Gate tools - A technical overview (White Paper, Roger Hart and David Atkinson) · Continuous integration for databases using Red Gate SQL tools (Product pages) · Database continuous integration step by step (David Atkinson) · Database Continuous Integration with Red Gate Tools (video, David Atkinson) · Database schema synchronisation with RedGate (Vincent Brouillet) · Database continuous integration and deployment with Red Gate tools (David Duffett) · Automated database releases with TeamCity and Red Gate (Troy Hunt) · How to build a database from source control (David Atkinson) · Continuous Integration Automated Database Update Process (Lance Lyons) Other · Evolutionary Database Design (Martin Fowler) · Recipes for Continuous Database Integration: Evolutionary Database Development (book, Pramod J Sadalage) · Recipes for Continuous Database Integration (book, Pramod Sadalage) · The Red Gate Guide to SQL Server Team-based Development (book, Phil Factor, Grant Fritchey, Alex Kuznetsov, Mladen Prajdic) · Using SQL Test Database Unit Testing with TeamCity Continuous Integration (Dave Green) · Continuous Database Integration (covers MySQL, Perason Education) Technorati Tags: SQL Server,Continous Integration

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  • Continuous Physics Engine's Collision Detection Techniques

    - by Griffin
    I'm working on a purely continuous physics engine, and I need to choose algorithms for broad and narrow phase collision detection. "Purely continuous" means I never do intersection tests, but instead want to find ways to catch every collision before it happens, and put each into "planned collisions" stack that is ordered by TOI. Broad Phase The only continuous broad-phase method I can think of is encasing each body in a circle and testing if each circle will ever overlap another. This seems horribly inefficient however, and lacks any culling. I have no idea what continuous analogs might exist for today's discrete collision culling methods such as quad-trees either. How might I go about preventing inappropriate and pointless broad test's such as a discrete engine does? Narrow Phase I've managed to adapt the narrow SAT to a continuous check rather than discrete, but I'm sure there's other better algorithms out there in papers or sites you guys might have come across. What various fast or accurate algorithm's do you suggest I use and what are the advantages / disatvantages of each? Final Note: I say techniques and not algorithms because I have not yet decided on how I will store different polygons which might be concave, convex, round, or even have holes. I plan to make a decision on this based on what the algorithm requires (for instance if I choose an algorithm that breaks down a polygon into triangles or convex shapes I will simply store the polygon data in this form).

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  • How to tell if SPARC T4 crypto is being used?

    - by danx
    A question that often comes up when running applications on SPARC T4 systems is "How can I tell if hardware crypto accleration is being used?" To review, the SPARC T4 processor includes a crypto unit that supports several crypto instructions. For hardware crypto these include 11 AES instructions, 4 xmul* instructions (for AES GCM carryless multiply), mont for Montgomery multiply (optimizes RSA and DSA), and 5 des_* instructions (for DES3). For hardware hash algorithm optimization, the T4 has the md5, sha1, sha256, and sha512 instructions (the last two are used for SHA-224 an SHA-384). First off, it's easy to tell if the processor T4 crypto instructions—use the isainfo -v command and look for "sparcv9" and "aes" (and other hash and crypto algorithms) in the output: $ 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 These instructions are not-privileged, so are available for direct use in user-level applications and libraries (such as OpenSSL). Here is the "openssl speed -evp" command shown with the built-in t4 engine and with the pkcs11 engine. Both run the T4 AES instructions, but the t4 engine is faster than the pkcs11 engine because it has less overhead (especially for smaller packet sizes): t-4 $ /usr/bin/openssl version OpenSSL 1.0.0j 10 May 2012 t-4 $ /usr/bin/openssl engine (t4) SPARC T4 engine support (dynamic) Dynamic engine loading support (pkcs11) PKCS #11 engine support t-4 $ /usr/bin/openssl speed -evp aes-128-cbc # t4 engine used by default . . . The 'numbers' are in 1000s of bytes per second processed. type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 487777.10k 816822.21k 986012.59k 1017029.97k 1053543.08k t-4 $ /usr/bin/openssl speed -engine pkcs11 -evp aes-128-cbc engine "pkcs11" set. . . . The 'numbers' are in 1000s of bytes per second processed. type 16 bytes 64 bytes 256 bytes 1024 bytes 8192 bytes aes-128-cbc 31703.58k 116636.39k 350672.81k 696170.50k 993599.49k Note: The "-evp" flag indicates use the OpenSSL "EnVeloPe" API, which gives more accurate results. That's because it tells OpenSSL to use the same API that external programs use when calling OpenSSL libcrypto functions, evp(3openssl). DTrace Shows if T4 Crypto Functions Are Used OK, good enough, the isainfo(1) command shows the instructions are present, but how does one know if they are being used? Chi-Chang Lin, who works on Oracle Solaris performance, wrote a Dtrace script to show if T4 instructions are being executed. To show the T4 instructions are being used, run the following Dtrace script. Look for functions named "t4" and "yf" in the output. The OpenSSL T4 engine uses functions named "t4" and the PKCS#11 engine uses functions named "yf". To demonstrate, I'll first run "openssl speed" with the built-in t4 engine then with the pkcs11 engine. The performance numbers are not valid due to dtrace probes slowing things down. t-4 # dtrace -Z -n ' pid$target::*yf*:entry,pid$target::*t4_*:entry{ @[probemod, probefunc] = count();}' \ -c "/usr/bin/openssl speed -evp aes-128-cbc" dtrace: description 'pid$target::*yf*:entry' matched 101 probes . . . dtrace: pid 2029 has exited libcrypto.so.1.0.0 ENGINE_load_t4 1 libcrypto.so.1.0.0 t4_DH 1 libcrypto.so.1.0.0 t4_DSA 1 libcrypto.so.1.0.0 t4_RSA 1 libcrypto.so.1.0.0 t4_destroy 1 libcrypto.so.1.0.0 t4_free_aes_ctr_NIDs 1 libcrypto.so.1.0.0 t4_init 1 libcrypto.so.1.0.0 t4_add_NID 3 libcrypto.so.1.0.0 t4_aes_expand128 5 libcrypto.so.1.0.0 t4_cipher_init_aes 5 libcrypto.so.1.0.0 t4_get_all_ciphers 6 libcrypto.so.1.0.0 t4_get_all_digests 59 libcrypto.so.1.0.0 t4_digest_final_sha1 65 libcrypto.so.1.0.0 t4_digest_init_sha1 65 libcrypto.so.1.0.0 t4_sha1_multiblock 126 libcrypto.so.1.0.0 t4_digest_update_sha1 261 libcrypto.so.1.0.0 t4_aes128_cbc_encrypt 1432979 libcrypto.so.1.0.0 t4_aes128_load_keys_for_encrypt 1432979 libcrypto.so.1.0.0 t4_cipher_do_aes_128_cbc 1432979 t-4 # dtrace -Z -n 'pid$target::*yf*:entry{ @[probemod, probefunc] = count();}   pid$target::*yf*:entry,pid$target::*t4_*:entry{ @[probemod, probefunc] = count();}' \ -c "/usr/bin/openssl speed -engine pkcs11 -evp aes-128-cbc" dtrace: description 'pid$target::*yf*:entry' matched 101 probes engine "pkcs11" set. . . . dtrace: pid 2033 has exited libcrypto.so.1.0.0 ENGINE_load_t4 1 libcrypto.so.1.0.0 t4_DH 1 libcrypto.so.1.0.0 t4_DSA 1 libcrypto.so.1.0.0 t4_RSA 1 libcrypto.so.1.0.0 t4_destroy 1 libcrypto.so.1.0.0 t4_free_aes_ctr_NIDs 1 libcrypto.so.1.0.0 t4_get_all_ciphers 1 libcrypto.so.1.0.0 t4_get_all_digests 1 libsoftcrypto.so.1 rijndael_key_setup_enc_yf 1 libsoftcrypto.so.1 yf_aes_expand128 1 libcrypto.so.1.0.0 t4_add_NID 3 libsoftcrypto.so.1 yf_aes128_cbc_encrypt 1542330 libsoftcrypto.so.1 yf_aes128_load_keys_for_encrypt 1542330 So, as shown above the OpenSSL built-in t4 engine executes t4_* functions (which are hand-coded assembly executing the T4 AES instructions) and the OpenSSL pkcs11 engine executes *yf* functions. Programmatic Use of OpenSSL T4 engine The OpenSSL t4 engine is used automatically with the /usr/bin/openssl command line. Chi-Chang Lin also points out that if you're calling the OpenSSL API (libcrypto.so) from a program, you must call ENGINE_load_built_engines(), otherwise the built-in t4 engine will not be loaded. You do not call ENGINE_set_default(). That's because "openssl speed -evp" test calls ENGINE_load_built_engines() even though the "-engine" option wasn't specified. OpenSSL T4 engine Availability The OpenSSL t4 engine is available with Solaris 11 and 11.1. For Solaris 10 08/11 (U10), you need to use the OpenSSL pkcs311 engine. The OpenSSL t4 engine is distributed only with the version of OpenSSL distributed with Solaris (and not third-party or self-compiled versions of OpenSSL). The OpenSSL engine implements the AES cipher for Solaris 11, released 11/2011. For Solaris 11.1, released 11/2012, the OpenSSL engine adds optimization for the MD5, SHA-1, and SHA-2 hash algorithms, and DES-3. Although the T4 processor has Camillia and Kasumi block cipher instructions, these are not implemented in the OpenSSL T4 engine. The following charts may help view availability of optimizations. The first chart shows what's available with Solaris CLIs and APIs, the second chart shows what's available in Solaris OpenSSL. Native Solaris Optimization for SPARC T4 This table is shows Solaris native CLI and API support. As such, they are all available with the OpenSSL pkcs11 engine. CLIs: "openssl -engine pkcs11", encrypt(1), decrypt(1), mac(1), digest(1), MD5sum(1), SHA1sum(1), SHA224sum(1), SHA256sum(1), SHA384sum(1), SHA512sum(1) APIs: PKCS#11 library libpkcs11(3LIB) (incluDES Openssl pkcs11 engine), libMD(3LIB), and Solaris kernel modules AlgorithmSolaris 1008/11 (U10)Solaris 11Solaris 11.1 AES-ECB, AES-CBC, AES-CTR, AES-CBC AES-CFB128 XXX DES3-ECB, DES3-CBC, DES2-ECB, DES2-CBC, DES-ECB, DES-CBC XXX bignum Montgomery multiply (RSA, DSA) XXX MD5, SHA-1, SHA-256, SHA-384, SHA-512 XXX SHA-224 X ARCFOUR (RC4) X Solaris OpenSSL T4 Engine Optimization This table is for the Solaris OpenSSL built-in t4 engine. Algorithms listed above are also available through the OpenSSL pkcs11 engine. CLI: openssl(1openssl) APIs: openssl(5), engine(3openssl), evp(3openssl), libcrypto crypto(3openssl) AlgorithmSolaris 11Solaris 11SRU2Solaris 11.1 AES-ECB, AES-CBC, AES-CTR, AES-CBC AES-CFB128 XXX DES3-ECB, DES3-CBC, DES-ECB, DES-CBC X bignum Montgomery multiply (RSA, DSA) X MD5, SHA-1, SHA-256, SHA-384, SHA-512 XX SHA-224 X Source Code Availability Solaris Most of the T4 assembly code that called the new T4 crypto instructions was written by Ferenc Rákóczi of the Solaris Security group, with assistance from others. You can download the Solaris source for this and other parts of Solaris as a few zip files at the Oracle Download website. The relevant source files are generally under directories usr/src/common/crypto/{aes,arcfour,des,md5,modes,sha1,sha2}}/sun4v/. and usr/src/common/bignum/sun4v/. Solaris 11 binary is available from the Oracle Solaris 11 download website. OpenSSL t4 engine The source for the OpenSSL t4 engine, which is based on the Solaris source above, is viewable through the OpenGrok source code browser in directory src/components/openssl/openssl-1.0.0/engines/t4 . You can download the source from the same website or through Mercurial source code management, hg(1). Conclusion Oracle Solaris with SPARC T4 provides a rich set of accelerated cryptographic and hash algorithms. Using the latest update, Solaris 11.1, provides the best set of optimized algorithms, but alternatives are often available, sometimes slightly slower, for releases back to Solaris 10 08/11 (U10). Reference See also these earlier blogs. SPARC T4 OpenSSL Engine by myself, Dan Anderson (2011), discusses the Openssl T4 engine and reviews the SPARC T4 processor for the Solaris 11 release. Exciting Crypto Advances with the T4 processor and Oracle Solaris 11 by Valerie Fenwick (2011) discusses crypto algorithms that were optimized for the T4 processor with the Solaris 11 FCS (11/11) and Solaris 10 08/11 (U10) release. T4 Crypto Cheat Sheet by Stefan Hinker (2012) discusses how to make T4 crypto optimization available to various consumers (such as SSH, Java, OpenSSL, Apache, etc.) High Performance Security For Oracle Database and Fusion Middleware Applications using SPARC T4 (PDF, 2012) discusses SPARC T4 and its usage to optimize application security. Configuring Oracle iPlanet WebServer / Oracle Traffic Director to use crypto accelerators on T4-1 servers by Meena Vyas (2012)

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  • How will technological singularity affect programmers?

    - by Amir Rezaei
    I'm one of the believers that think that we will hit the technological singularity sooner or later. Then the question is if any profession will be unaffected by changes that will come. In the end it will be we programmers that will implement the first self-aware AI. How will technological singularity affect us programmer? What is your professional opinion regarding technological singularity? EDIT: By self-aware I refer to an entity that questions and seek answers, able to analyze and solve problem. Artificial neural network is branch in mathematics/statistics with many widely used algorithms. The algorithms are applied where recognition of data is needed. For example hidden Markov model is used for voice recognition. Another well-known area is business intelligence and data mining. Today algorithms are self-learning. That is a bit of AI what many never think of. Let an ultraintelligent machine be defined as a machine that can far surpass all the intellectual activities of any man however clever. Since the design of machines is one of these intellectual activities, an ultraintelligent machine could design even better machines; there would then unquestionably be an ‘intelligence explosion,’ and the intelligence of man would be left far behind. Thus the first ultraintelligent machine is the last invention that man need ever make. Link to Ref.

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  • I am not the most logically-organized person. Do I have any chance at being a good 'low-level' programmer?

    - by user217902
    Background: I am entering college next year. I really enjoy making stuff and solving logical problems, so I'm thinking of majoring in compsci and working in software development. I hope to have the kind of job where I can work with implementing / improving algorithms and data structures on a regular basis.. as opposed to, say, a job that's purely concerned with mashing different libraries together, or 'finding the right APIs for the job'. (Hence the word 'low-level' in the title. No, I don't wish to write assembly all day.) Thing is, I've never been the most logically-sharp person. Thus far I have only worked on hobby projects, but I find that I make the silliest of errors ever so often, and it can take me ages to find it. Like anywhere between three hours to a day to locate a simple segfault, off-by-one error, or other logical mistake. (Of course, I do other things in the meantime, like browsing SO, reddit, and the like..) It's not like I'm 'new' to programming either; I first tried C++ maybe five years ago. My question is: is this normal? Should a programmer with any talent solve it in less time? Having read Spolsky's Smart and gets things done, where he talks about the large variance in programming speed, am I near the bottom of the curve, and therefore destined to work in companies that cannot afford to hire quality programmers? I'd like to think that conceptually I'm okay -- I can grasp algorithms and concepts pretty well, I do fine in math and science, although I probably drop signs in my equations more often than the next guy. Still, grokking concepts makes me happy, and is the reason why I want to work with algorithms. I'm hoping to hear from those of you with real-world programming experience. TL;DR: I make many careless mistakes, should I not consider programming as a career?

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  • Moving From IT to Embedded software Developing

    - by Ameer Adel
    i worked for two years at a channel station, managing various Types of tasks, varying from printers installation, software solution, down to managing and maintaining server automation, to be honest, i always been enthusiastic about programming, i studied at some affordable college and finished my IT path successfully, my graduation project was in C# ADO.NET couple of years ago. Obviously it was so much of a beginner spaghetti code than a well furnished code. I also had the chance; after leaving the IT career, to study about some ASP.NET MVC and web apps development. I have rookie level of coding skills due to the poor level of education i endured, and sufficient resources. Currently i m working as a trainee in a newly opened embedded software development company, that is being said, i am, as i sound, have a little idea about the algorithms included, as i was reading for the past couple of days, embedded system development requires more strict coding skills, including memory management, CPU optimization according to its architect, and couple of other tricks regarding the display, and power management if mobile.. etc. My question is, What type of Algorithms am i supposed to use in such cases, as i mentioned before, i am really enthusiastic about learning programming skills and algorithms related to embedded systems and programming languages, including C/C++, Java, C#, and some EC++ if still operational.

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  • Help with design structure choice: Using classes or library of functions

    - by roverred
    So I have GUI Class that will call another class called ImageProcessor that contains a bunch functions that will perform image processing algorithms like edgeDetection, gaussianblur, contourfinding, contour map generations, etc. The GUI passes an image to ImageProcessor, which performs one of those algorithm on it and it returns the image back to the GUI to display. So essentially ImageProcessor is a library of independent image processing functions right now. It is called in the GUI like so Image image = ImageProcessor.EdgeDetection(oldImage); Some of the algorithms procedures require many functions, and some can be done in a single function or even one line. All these functions for the algorithms jam packed into ImageProcessor can be pretty messy, and ImageProcessor doesn't sound it should be a library. So I was thinking about making every algorithm be a class with a shared interface say IAlgorithm. Then I pass the IAlgorithm interface from the GUI to the ImageProcessor. public interface IAlgorithm{ public Image Process(); } public class ImageProcessor{ public Image Process(IAlgorithm TheAlgorithm){ return IAlgorithm.Process(); } } Calling in the GUI like so Image image = ImageProcessor.Process(new EdgeDetection(oldImage)); I think it makes sense in an object point of view, but the problem is I'll end up with some classes that are just one function. What do you think is a better design, or are they both crap and you have a much better idea? Thanks!

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  • List of freely available programming books

    - by Karan Bhangui
    I'm trying to amass a list of programming books with opensource licenses, like Creative Commons, GPL, etc. The books can be about a particular programming language or about computers in general. Hoping you guys could help: Languages BASH Advanced Bash-Scripting Guide (An in-depth exploration of the art of shell scripting) C The C book C++ Thinking in C++ C++ Annotations How to Think Like a Computer Scientist C# .NET Book Zero: What the C or C++ Programmer Needs to Know About C# and the .NET Framework Illustrated C# 2008 (Dead Link) Data Structures and Algorithms with Object-Oriented Design Patterns in C# Threading in C# Common Lisp Practical Common Lisp On Lisp Java Thinking in Java How to Think Like a Computer Scientist Java Thin-Client Programming JavaScript Eloquent JavaScript Haskell Real world Haskell Learn You a Haskell for Great Good! Objective-C The Objective-C Programming Language Perl Extreme Perl (license not specified - home page is saying "freely available") The Mason Book (Open Publication License) Practical mod_perl (CreativeCommons Attribution Share-Alike License) Higher-Order Perl Learning Perl the Hard Way PHP Practical PHP Programming Zend Framework: Survive the Deep End PowerShell Mastering PowerShell Prolog Building Expert Systems in Prolog Adventure in Prolog Prolog Programming A First Course Logic, Programming and Prolog (2ed) Introduction to Prolog for Mathematicians Learn Prolog Now! Natural Language Processing Techniques in Prolog Python Dive Into Python Dive Into Python 3 How to Think Like a Computer Scientist A Byte of Python Python for Fun Invent Your Own Computer Games With Python Ruby Why's (Poignant) Guide to Ruby Programming Ruby - The Pragmatic Programmer's Guide Mr. Neighborly's Humble Little Ruby Book SQL Practical PostgreSQL x86 assembly Paul Carter's tutorial Lua Programming In Lua (for v5 but still largely relevant) Algorithms and Data Structures Algorithms Data Structures and Algorithms with Object-Oriented Design Patterns in Java Planning Algorithms Frameworks/Projects The Django Book The Pylons Book Introduction to Design Patterns in C++ with Qt 4 (Open Publication License) Version control The SVN Book Mercurial: The Definitive Guide Pro Git UNIX / Linux The Art of Unix Programming Linux Device Drivers, Third Edition Others Structure and Interpretation of Computer Programs The Little Book of Semaphores Mathematical Logic - an Introduction An Introduction to the Theory of Computation Developers Developers Developers Developers Linkers and loaders Beej's Guide to Network Programming Maven: The Definitive Guide I will expand on this list as I get comments or when I think of more :D Related: Programming texts and reference material for my Kindle What are some good free programming books? Can anyone recommend a free software engineering book? Edit: Oh I didn't notice the community wiki feature. Feel free to edit your suggestions right in!

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