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  • Best netbook for light development

    - by CodingBytes
    I'm looking into purchasing a netbook for traveling. I realize that most of these machines are designed for surfing the web and checking email. What model(s) are most likely to handle a development environment with Visual Studio 2008?

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  • Start Windows GUI Application Development With C++

    - by Chris
    I'm looking into creating a GUI program for Windows in C++, I have a good knowledge of C++ in the command line and also in game creation. But I'm not sure where to start with GUI application development. I have Visual Studio 2010 and have created new projects with a GUI but these templates are complex and leaves me not understanding whats happening and how to modify it. So I'm asking where do I start? Preferably good websites that you can recommend or tutorials, rather than books being a poor student :)

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  • Visual Map about Microsoft development products

    - by Eduardo
    Hello: I listen much about new Microsoft terminologies such as WPF, WCF, WWF, ASP.NET MVC, Silverlight, entity framework, LINQ. I would like to see in a visual map: 1) how these products interrelate 2) Which are complements of which. 3) Order of priority to learn I think all the names that I mentioned, together with the use of Visual Studio applies to web developments. I need a good answer to guide my efforts of Web development in the best way. Thanks.

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  • Is there a simple PHP development server?

    - by pinchyfingers
    When writing web apps in Python, it brain dead easy to run a development server. Django and Google App Engine both ship with simple servers. The main feature I'm looking for is no configuration. I want something like the GAE dev server where you just pass the directory of the app as a parameter when the server is started. Is there a reason that this is more difficult with PHP?

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  • OpenSource programming-languages in development?

    - by pile of junk
    I'm very interested in interpreter and compiler development and because I don't want to continue building mini compilers and interpreters I thought I could help some open-source project. Are there currently open-source projects on compilers/interpreters in early stages seeking developers? I mean yeah.. There won't be much to do for someone like me in Python, Ruby, and so on.

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  • Paralell development Branches w/ Bazaar

    - by Kristopher Ives
    I have two branches (or tags?) where I need to keep the same file structure with different versioned contents. One version contains everything, like development scripts, configuration files, etc. while the other contains only things that get redistributed. How can I accomplish this using Bazaar?

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  • iPhone development

    - by sid
    Hi All, I am new to iPhone development. I want to make a simple iPhone application which when launched computes the distance travelled by the user,calories burnt,postion of the user,movement.Can anybody provide me the details or approach to follow to develop this application.

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  • Facebook application development resources

    - by Michael
    What is the most efficient way to start learning develop Facebook applications? Any web resource or book that you would recommend to start from? Any MUST READ or Bibles available for this? There are plenty of them in Amazon, but which one really worth to spend time? What kind of development technologies are used in this? Is PHP/MySQL/JS enough to jump in? Thanks

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  • What do I need to be able to use Joomla as an online application development enbironment

    - by howdyworld
    I develop applications using PHP and MySQL. They're not trivial, though they're not too complex. As an example to that I have written an online application to enable football administrators manage the player, competition and judiciary processes. Separately to that I have used Joomla to create websites for small businesses. I'd like to be able to use Joomla as my online application development environment. Is there a way I can use Joomla for that?

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  • Continuous Integration for SQL Server Part II – Integration Testing

    - by Ben Rees
    My previous post, on setting up Continuous Integration for SQL Server databases using GitHub, Bamboo and Red Gate’s tools, covered the first two parts of a simple Database Continuous Delivery process: Putting your database in to a source control system, and, Running a continuous integration process, each time changes are checked in. However there is, of course, a lot more to to Continuous Delivery than that. Specifically, in addition to the above: Putting some actual integration tests in to the CI process (otherwise, they don’t really do much, do they!?), Deploying the database changes with a managed, automated approach, Monitoring what you’ve just put live, to make sure you haven’t broken anything. This post will detail how to set up a very simple pipeline for implementing the first of these (continuous integration testing). NB: A lot of the setup in this post is built on top of the configuration from before, so it might be difficult to implement this post without running through part I first. There’ll then be a third post on automated database deployment followed by a final post dealing with the last item – monitoring changes on the live system. In the previous post, I used a mixture of Red Gate products and other 3rd party software – GitHub and Atlassian Bamboo specifically. This was partly because I believe most people work in an heterogeneous environment, using software from different vendors to suit their purposes and I wanted to show how this could work for this process. For example, you could easily substitute Atlassian’s BitBucket or Stash for GitHub, depending on your needs, or use an alternative CI server such as TeamCity, TFS or Jenkins. However, in this, post, I’ll be mostly using Red Gate products only (other than tSQLt). I would do this, firstly because I work for Red Gate. However, I also think that in the area of Database Delivery processes, nobody else has the offerings to implement this process fully – so I didn’t have any choice!   Background on Continuous Delivery For me, a great source of information on what makes a proper Continuous Delivery process is the Jez Humble and David Farley classic: Continuous Delivery – Reliable Software Releases through Build, Test, and Deployment Automation This book is not of course, primarily about databases, and the process I outline here and in the previous article is a gross simplification of what Jez and David describe (not least because it’s that much harder for databases!). However, a lot of the principles that they describe can be equally applied to database development and, I would argue, should be. As I say however, what I describe here is a very simple version of what would be required for a full production process. A couple of useful resources on handling some of these complexities can be found in the following two references: Refactoring Databases – Evolutionary Database Design, by Scott J Ambler and Pramod J. Sadalage Versioning Databases – Branching and Merging, by Scott Allen In particular, I don’t deal at all with the issues of multiple branches and merging of those branches, an issue made particularly acute by the use of GitHub. The other point worth making is that, in the words of Martin Fowler: Continuous Delivery is about keeping your application in a state where it is always able to deploy into production.   I.e. we are not talking about continuously delivery updates to the production database every time someone checks in an amendment to a stored procedure. That is possible (and what Martin calls Continuous Deployment). However, again, that’s more than I describe in this article. And I doubt I need to remind DBAs or Developers to Proceed with Caution!   Integration Testing Back to something practical. The next stage, building on our set up from the previous article, is to add in some integration tests to the process. As I say, the CI process, though interesting, isn’t enormously useful without some sort of test process running. For this we’ll use the tSQLt framework, an open source framework designed specifically for running SQL Server tests. tSQLt is part of Red Gate’s SQL Test found on http://www.red-gate.com/products/sql-development/sql-test/ or can be downloaded separately from www.tsqlt.org - though I’ll provide a step-by-step guide below for setting this up. Getting tSQLt set up via SQL Test Click on the link http://www.red-gate.com/products/sql-development/sql-test/ and click on the blue Download button to download the Red Gate SQL Test product, if not already installed. Follow the install process for SQL Test to install the SQL Server Management Studio (SSMS) plugin on to your machine, if not already installed. Open SSMS. You should now see SQL Test under the Tools menu:   Clicking this link will give you the basic SQL Test dialogue: As yet, though we’ve installed the SQL Test product we haven’t yet installed the tSQLt test framework on to any particular database. To do this, we need to add our RedGateApp database using this dialogue, by clicking on the + Add Database to SQL Test… link, selecting the RedGateApp database and clicking the Add Database link:   In the next screen, SQL Test describes what will be installed on the database for the tSQLt framework. Also in this dialogue, uncheck the “Add SQL Cop tests” option (shown below). SQL Cop is a great set of pre-defined tests that work within the tSQLt framework to check the general health of your SQL Server database. However, we won’t be using them in this particular simple example: Once you’ve clicked on the OK button, the changes described in the dialogue will be made to your database. Some of these are shown in the left-hand-side below: We’ve now installed the framework. However, we haven’t actually created any tests, so this will be the next step. But, before we proceed, we’ve made an update to our database so should, again check this in to source control, adding comments as required:   Also worth a quick check that your build still runs with the new additions!: (And a quick check of the RedGateAppCI database shows that the changes have been made).   Creating and Testing a Unit Test There are, of course, a lot of very interesting unit tests that you could and should set up for a database. The great thing about the tSQLt framework is that you can write these in SQL. The example I’m going to use here is pretty Mickey Mouse – our database table is going to include some email addresses as reference data and I want to check whether these are all in a correct email format. Nothing clever but it illustrates the process and hopefully shows the method by which more interesting tests could be set up. Adding Reference Data to our Database To start, I want to add some reference data to my database, and have this source controlled (as well as the schema). First of all I need to add some data in to my solitary table – this can be done a number of ways, but I’ll do this in SSMS for simplicity: I then add some reference data to my table: Currently this reference data just exists in the database. For proper integration testing, this needs to form part of the source-controlled version of the database – and so needs to be added to the Git repository. This can be done via SQL Source Control, though first a Primary Key needs to be added to the table. Right click the table, select Design, then right-click on the first “id” row. Then click on “Set Primary Key”: NB: once this change is made, click Save to save the change to the table. Then, to source control this reference data, right click on the table (dbo.Email) and selecting the following option:   In the next screen, link the data in the Email table, by selecting it from the list and clicking “save and close”: We should at this point re-commit the changes (both the addition of the Primary Key, and the data) to the Git repo. NB: From here on, I won’t show screenshots for the GitHub side of things – it’s the same each time: whenever a change is made in SQL Source Control and committed to your local folder, you then need to sync this in the GitHub Windows client (as this is where the build server, Bamboo is taking it from). An interesting point to note here, when these changes are committed in SQL Source Control (right-click database and select “Commit Changes to Source Control..”): The display gives a warning about possibly needing a migration script for the “Add Primary Key” step of the changes. This isn’t actually necessary in this case, but this mechanism would allow you to create override scripts to replace the default change scripts created by the SQL Compare engine (which runs underneath SQL Source Control). Ignoring this message (!), we add a comment and commit the changes to Git. I then sync these, run a build (or the build gets run automatically), and check that the data is being deployed over to the target RedGateAppCI database:   Creating and Running the Test As I mention, the test I’m going to use here is a very simple one - are the email addresses in my reference table valid? This isn’t of course, a full test of email validation (I expect the email addresses I’ve chosen here aren’t really the those of the Fab Four) – but just a very basic check of format used. I’ve taken the relevant SQL from this Stack Overflow article. In SSMS select “SQL Test” from the Tools menu, then click on + New Test: In the next screen, give your new test a name, and also enter a name in the Test Class box (test classes are schemas that help you keep things organised). Also check that the database in which the test is going to be created is correct – RedGateApp in this example: Click “Create Test”. After closing a couple of subsequent dialogues, you’ll see a dummy script for the test, that needs filling in:   We now need to define the SQL for our test. As mentioned before, tSQLt allows you to write your unit tests in T-SQL, and the code I’m going to use here is as below. This needs to be copied and pasted in to the query window, to replace the default given by tSQLt: –  Basic email check test ALTER PROCEDURE [MyChecks].[test Check Email Addresses] AS BEGIN SET NOCOUNT ON         Declare @Output VarChar(max)     Set @Output = ”       SELECT  @Output = @Output + Email +Char(13) + Char(10) FROM dbo.Email WHERE email NOT LIKE ‘%_@__%.__%’       If @Output > ”         Begin             Set @Output = Char(13) + Char(10)                           + @Output             EXEC tSQLt.Fail@Output         End   END;   Once this script is entered, hit execute to add the Stored Procedure to the database. Before committing the test to source control,  it’s worth just checking that it works! For a positive test, click on “SQL Test” from the Tools menu, then click Run Tests. You should see output like the following: - a green tick to indicate success! But of course, what we also need to do is test that this is actually doing something by showing a failed test. Edit one of the email addresses in your table to an incorrect format: Now, re-run the same SQL Test as before and you’ll see the following: Great – we now know that our test is really doing something! You’ll also see a useful error message at the bottom of SSMS: (leave the email address as invalid for now, for the next steps). The next stage is to check this new test in to source control again, by right-clicking on the database and checking in the changes with a commit message (and not forgetting to sync in the GitHub client):   Checking that the Tests are Running as Integration Tests After the changes above are made, and after a build has run on Bamboo (manual or automatic), looking at the Stored Procedures for the RedGateAppCI, the SPROC for the new test has been moved over to the database. However this is not exactly what we were after. We didn’t want to just copy objects from one database to another, but actually run the tests as part of the build/integration test process. I.e. we’re continuously checking any changes we make (in this case, to the reference data emails), to ensure we’re not breaking a test that we’ve set up. The behaviour we want to see is that, if we check in static data that is incorrect (as we did in step 9 above) and we have the tSQLt test set up, then our build in Bamboo should fail. However, re-running the build shows the following: - sadly, a successful build! To make sure the tSQLt tests are run as part of the integration test, we need to amend a switch in the Red Gate CI config file. First, navigate to file sqlCI.targets in your working folder: Edit this document, make the following change, save the document, then commit and sync this change in the GitHub client: <!-- tSQLt tests --> <!-- Optional --> <!-- To run tSQLt tests in source control for the database, enter true. --> <enableTsqlt>true</enableTsqlt> Now, if we re-run the build in Bamboo (NB: I’ve moved to a new server here, hence different address and build number): - superb, a broken build!! The error message isn’t great here, so to get more detailed info, click on the full build log link on this page (below the fold). The interesting part of the log shown is towards the bottom. Pulling out this part:   21-Jun-2013 11:35:19 Build FAILED. 21-Jun-2013 11:35:19 21-Jun-2013 11:35:19 "C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj" (default target) (1) -> 21-Jun-2013 11:35:19 (sqlCI target) -> 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: RedGate.Deploy.SqlServerDbPackage.Shared.Exceptions.InvalidSqlException: Test Case Summary: 1 test case(s) executed, 0 succeeded, 1 failed, 0 errored. [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj] 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: [MyChecks].[test Check Email Addresses] failed: [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj] 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: ringo.starr@beatles [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj] 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj] 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: +----------------------+ [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj] 21-Jun-2013 11:35:19 EXEC : sqlCI error occurred: |Test Execution Summary| [C:\Users\Administrator\bamboo-home\xml-data\build-dir\RGA-RGP-JOB1\sqlCI.proj]   As a final check, we should make sure that, if we now fix this error, the build succeeds. So in SSMS, I’m going to correct the invalid email address, then check this change in to SQL Source Control (with a comment), commit to GitHub, and re-run the build:   This should have fixed the build: It worked! Summary This has been a very quick run through the implementation of CI for databases, including tSQLt tests to test whether your database updates are working. The next post in this series will focus on automated deployment – we’ve tested our database changes, how can we now deploy these to target sites?  

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  • Game development: “Play Now” via website vs. download & install

    - by Inside
    Heyo, I've spent some time looking over the various threads here on gamedev and also on the regular stackoverflow and while I saw a lot of posts and threads regarding various engines that could be used in game development, I haven't seen very much discussion regarding the various platforms that they can be used on. In particular, I'm talking about browser games vs. desktop games. I want to develop a simple 3D networked multiplayer game - roughly on the graphics level of Paper Mario and gameplay with roughly the same level of interaction as a hack & slash action/adventure game - and I'm having a hard time deciding what platform I want to target with it. I have some experience with using C++/Ogre3D and Python/Panda3D (and also some synchronized/networked programming), but I'm wondering if it's worth it to spend the extra time to learn another language and another engine/toolkit just so that the game can be played in a browser window (I'm looking at jMonkeyEngine right now). For simple & short games the newgrounds approach (go to the site, click "play now", instant gratification) seems to work well. What about for more complex games? Is there a point where the complexity of a game is enough for people to say "ok, I'm going to download and play that"? Is it worth it to go with engines that are less-mature, have less documentation, have fewer features, and smaller communities* just so that a (possibly?) larger audience can be reached? Does it make sense to even go with a web-environment for the kind of game that I want to make? Does anyone have any experiences with decisions like this? Thanks! (* With the exception of flash-based engines it seems like most of the other approaches have these downsides when compared to what is available for desktop-based environments. I'd go with flash, but I'm worried that flash's 3D capabilities aren't mature enough right now to do what I want easily. There's also Unity3D, but I'm not sure how I feel about that at all. It seems highly polished, but requires a plugin to be downloaded for the game to be played -- at that rate I might as well have players download my game.)

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  • Basics of Join Factorization

    - by Hong Su
    We continue our series on optimizer transformations with a post that describes the Join Factorization transformation. The Join Factorization transformation was introduced in Oracle 11g Release 2 and applies to UNION ALL queries. Union all queries are commonly used in database applications, especially in data integration applications. In many scenarios the branches in a UNION All query share a common processing, i.e, refer to the same tables. In the current Oracle execution strategy, each branch of a UNION ALL query is evaluated independently, which leads to repetitive processing, including data access and join. The join factorization transformation offers an opportunity to share the common computations across the UNION ALL branches. Currently, join factorization only factorizes common references to base tables only, i.e, not views. Consider a simple example of query Q1. Q1:    select t1.c1, t2.c2    from t1, t2, t3    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2   union all    select t1.c1, t2.c2    from t1, t2, t4    where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3; Table t1 appears in both the branches. As does the filter predicates on t1 (t1.c1 > 1) and the join predicates involving t1 (t1.c1 = t2.c1). Nevertheless, without any transformation, the scan (and the filtering) on t1 has to be done twice, once per branch. Such a query may benefit from join factorization which can transform Q1 into Q2 as follows: Q2:    select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                   from t2, t3                    where t2.c2 = t3.c2 and t2.c2 = 2                                  union all                   select t2.c1 item_1, t2.c2 item_2                   from t2, t4                    where t2.c3 = t4.c3) VW_JF_1    where t1.c1 = VW_JF_1.item_1 and t1.c1 > 1; In Q2, t1 is "factorized" and thus the table scan and the filtering on t1 is done only once (it's shared). If t1 is large, then avoiding one extra scan of t1 can lead to a huge performance improvement. Another benefit of join factorization is that it can open up more join orders. Let's look at query Q3. Q3:    select *    from t5, (select t1.c1, t2.c2                  from t1, t2, t3                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c2 = 2 and t2.c2 = t3.c2                 union all                  select t1.c1, t2.c2                  from t1, t2, t4                  where t1.c1 = t2.c1 and t1.c1 > 1 and t2.c3 = t4.c3) V;   where t5.c1 = V.c1 In Q3, view V is same as Q1. Before join factorization, t1, t2 and t3 must be joined first before they can be joined with t5. But if join factorization factorizes t1 from view V, t1 can then be joined with t5. This opens up new join orders. That being said, join factorization imposes certain join orders. For example, in Q2, t2 and t3 appear in the first branch of the UNION ALL query in view VW_JF_1. T2 must be joined with t3 before it can be joined with t1 which is outside of the VW_JF_1 view. The imposed join order may not necessarily be the best join order. For this reason, join factorization is performed under cost-based transformation framework; this means that we cost the plans with and without join factorization and choose the cheapest plan. Note that if the branches in UNION ALL have DISTINCT clauses, join factorization is not valid. For example, Q4 is NOT semantically equivalent to Q5.   Q4:     select distinct t1.*      from t1, t2      where t1.c1 = t2.c1  union all      select distinct t1.*      from t1, t2      where t1.c1 = t2.c1 Q5:    select distinct t1.*     from t1, (select t2.c1 item_1                   from t2                union all                   select t2.c1 item_1                  from t2) VW_JF_1     where t1.c1 = VW_JF_1.item_1 Q4 might return more rows than Q5. Q5's results are guaranteed to be duplicate free because of the DISTINCT key word at the top level while Q4's results might contain duplicates.   The examples given so far involve inner joins only. Join factorization is also supported in outer join, anti join and semi join. But only the right tables of outer join, anti join and semi joins can be factorized. It is not semantically correct to factorize the left table of outer join, anti join or semi join. For example, Q6 is NOT semantically equivalent to Q7. Q6:     select t1.c1, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t2.c2 (+) = 2  union all    select t1.c1, t2.c2    from t1, t2      where t1.c1 = t2.c1(+) and t2.c2 (+) = 3 Q7:     select t1.c1, VW_JF_1.item_2    from t1, (select t2.c1 item_1, t2.c2 item_2                  from t2                  where t2.c2 = 2                union all                  select t2.c1 item_1, t2.c2 item_2                  from t2                                                                                                    where t2.c2 = 3) VW_JF_1       where t1.c1 = VW_JF_1.item_1(+)                                                                  However, the right side of an outer join can be factorized. For example, join factorization can transform Q8 to Q9 by factorizing t2, which is the right table of an outer join. Q8:    select t1.c2, t2.c2    from t1, t2      where t1.c1 = t2.c1 (+) and t1.c1 = 1 union all    select t1.c2, t2.c2    from t1, t2    where t1.c1 = t2.c1(+) and t1.c1 = 2 Q9:   select VW_JF_1.item_2, t2.c2   from t2,             (select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 1           union all            select t1.c1 item_1, t1.c2 item_2            from t1            where t1.c1 = 2) VW_JF_1   where VW_JF_1.item_1 = t2.c1(+) All of the examples in this blog show factorizing a single table from two branches. This is just for ease of illustration. Join factorization can factorize multiple tables and from more than two UNION ALL branches.  SummaryJoin factorization is a cost-based transformation. It can factorize common computations from branches in a UNION ALL query which can lead to huge performance improvement. 

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  • 9/18 Live Webcast: Three Compelling Reasons to Upgrade to Oracle Database 11g - Still time to register

    - by jgelhaus
    If you or your organization is still working with Oracle Database 10g or an even older version, now is the time to upgrade. Oracle Database 11g offers a wide variety of advantages to enhance your operation. Join us 10 am PT / 1pm ET September 18th for this live Webcast and learn about what you’re missing: the business, operational, and technical benefits. With Oracle Database 11g, you can: Upgrade with zero downtime Improve application performance and database security Reduce the amount of storage required Save time and money Register today 

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