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  • Cowboy Agile?

    - by Robert May
    In a previous post, I outlined the rules of Scrum.  This post details one of those rules. I’ve often heard similar phrases around Scrum that clue me in to someone who doesn’t understand Scrum.  The phrases go something like this: “We don’t do Agile because the idea of letting people just do whatever they want is wrong.  We believe in a more structured approach.” (i.e. Work is Prison, and I’m the Warden!) “I love Agile.  Agile lets us do whatever we want!” (Cowboy Agile?) “We’re Agile, but we use a process that I’ve created.” (Cowboy Agile?) All of those phrases have one thing in common:  The assumption that Agile, and I mean Scrum, lets you do whatever you want.  This is simply not true. Executing Scrum properly requires more dedication, rigor, and diligence than happens in most traditional development methods. Scrum and Waterfall Compared Since Scrum and Waterfall are two of the most commonly used methodologies, a little bit of contrasting and comparing is in order. Waterfall Scrum A project manager defines all tasks and then manages the tasks that team members are working on. The team members define the tasks and estimates of the stories for the current iteration.  Any team member may work on any task in the iteration. Usually only a few milestones that need to be met, the milestones are measured in months, and these milestones are expected to be missed.  Little work is ever done to improve estimates and poor estimators can hide behind high estimates. Stories must be delivered every iteration, milestones are measured in hours, and the team is expected to figure out why their estimates were wrong, even when they were under.  Repeated misses can get the entire team fired. Partially completed work is normal. Partially completed work doesn’t count. Nobody knows the task you’re working on. Everyone knows what you’re working on, whether or not you’re making progress and how much longer you think its going to take, in hours. Little requirement to show working code.  Prototypes are ok. Working code must be shown each iteration.  No smoke and mirrors allowed.  Testing is done in lengthy cycles at the end of development.  Developers aren’t held accountable. Testing is part of the team.  If the testers don’t accept the story as complete, the team can’t count it.  Complete means that the story’s functionality works as designed.  The team can’t have any open defects on the story. Velocity is rarely truly measured and difficult to evaluate. Velocity is integral to the process and can be seen at a glance and everyone in the company knows what it is. A business analyst writes requirements.  Designers mock up screens.  Developers hide behind “I did it just like the spec doc told me to and made the screen exactly like the picture” Developers are expected to collaborate in real time.  If a design is bad or lacks needed details, the developers are required to get it right in the iteration, because all software must be functional.  Designers and Business Analysts are part of the team and must do their work in iterations slightly ahead of the developers. Upper Management is often surprised.  “You told me things were going well two months ago!” Management receives updates at the end of every iteration showing them exactly what the team did and how that compares to what' is remaining in the backlog.  Managers know every iteration what their money is buying. Status meetings are rare or don’t occur.  Email is a primary form of communication. Teams coordinate every single day with each other and use other high bandwidth communication channels to make sure they’re making progress.  Email is used only as a last resort.  Instead, team members stand up, walk to each other, and talk, face to face.  If that’s not possible, they pick up the phone. IF someone asks what happened, its at the end of a lengthy development cycle measured in months, and nobody really knows why it happened. Someone asks what happened every iteration.  The team talks about what happened, and then adapts to make sure that what happened either never happens again or happens every time.   That’s probably enough for now.  As you can see, a lot is required of Scrum teams! One of the key differences in Scrum is that the burden for many activities is shifted to a group of people who share responsibility, instead of a single person having responsibility.  This is a very good thing, since small groups usually come up with better and more insightful work than single individuals.  This shift also results in better velocity.  Team members can take vacations and the rest of the team simply picks up the slack.  With Waterfall, if a key team member takes a vacation, delays can ensue. Scrum requires much more out of every team member and as a result, Scrum teams outperform non-Scrum teams working 60 hour weeks. Recommended Reading Everyone considering Scrum should read Mike Cohn’s excellent book, User Stories Applied. Technorati Tags: Agile,Scrum,Waterfall

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  • Some non-generic collections

    - by Simon Cooper
    Although the collections classes introduced in .NET 2, 3.5 and 4 cover most scenarios, there are still some .NET 1 collections that don't have generic counterparts. In this post, I'll be examining what they do, why you might use them, and some things you'll need to bear in mind when doing so. BitArray System.Collections.BitArray is conceptually the same as a List<bool>, but whereas List<bool> stores each boolean in a single byte (as that's what the backing bool[] does), BitArray uses a single bit to store each value, and uses various bitmasks to access each bit individually. This means that BitArray is eight times smaller than a List<bool>. Furthermore, BitArray has some useful functions for bitmasks, like And, Xor and Not, and it's not limited to 32 or 64 bits; a BitArray can hold as many bits as you need. However, it's not all roses and kittens. There are some fundamental limitations you have to bear in mind when using BitArray: It's a non-generic collection. The enumerator returns object (a boxed boolean), rather than an unboxed bool. This means that if you do this: foreach (bool b in bitArray) { ... } Every single boolean value will be boxed, then unboxed. And if you do this: foreach (var b in bitArray) { ... } you'll have to manually unbox b on every iteration, as it'll come out of the enumerator an object. Instead, you should manually iterate over the collection using a for loop: for (int i=0; i<bitArray.Length; i++) { bool b = bitArray[i]; ... } Following on from that, if you want to use BitArray in the context of an IEnumerable<bool>, ICollection<bool> or IList<bool>, you'll need to write a wrapper class, or use the Enumerable.Cast<bool> extension method (although Cast would box and unbox every value you get out of it). There is no Add or Remove method. You specify the number of bits you need in the constructor, and that's what you get. You can change the length yourself using the Length property setter though. It doesn't implement IList. Although not really important if you're writing a generic wrapper around it, it is something to bear in mind if you're using it with pre-generic code. However, if you use BitArray carefully, it can provide significant gains over a List<bool> for functionality and efficiency of space. OrderedDictionary System.Collections.Specialized.OrderedDictionary does exactly what you would expect - it's an IDictionary that maintains items in the order they are added. It does this by storing key/value pairs in a Hashtable (to get O(1) key lookup) and an ArrayList (to maintain the order). You can access values by key or index, and insert or remove items at a particular index. The enumerator returns items in index order. However, the Keys and Values properties return ICollection, not IList, as you might expect; CopyTo doesn't maintain the same ordering, as it copies from the backing Hashtable, not ArrayList; and any operations that insert or remove items from the middle of the collection are O(n), just like a normal list. In short; don't use this class. If you need some sort of ordered dictionary, it would be better to write your own generic dictionary combining a Dictionary<TKey, TValue> and List<KeyValuePair<TKey, TValue>> or List<TKey> for your specific situation. ListDictionary and HybridDictionary To look at why you might want to use ListDictionary or HybridDictionary, we need to examine the performance of these dictionaries compared to Hashtable and Dictionary<object, object>. For this test, I added n items to each collection, then randomly accessed n/2 items: So, what's going on here? Well, ListDictionary is implemented as a linked list of key/value pairs; all operations on the dictionary require an O(n) search through the list. However, for small n, the constant factor that big-o notation doesn't measure is much lower than the hashing overhead of Hashtable or Dictionary. HybridDictionary combines a Hashtable and ListDictionary; for small n, it uses a backing ListDictionary, but switches to a Hashtable when it gets to 9 items (you can see the point it switches from a ListDictionary to Hashtable in the graph). Apart from that, it's got very similar performance to Hashtable. So why would you want to use either of these? In short, you wouldn't. Any gain in performance by using ListDictionary over Dictionary<TKey, TValue> would be offset by the generic dictionary not having to cast or box the items you store, something the graphs above don't measure. Only if the performance of the dictionary is vital, the dictionary will hold less than 30 items, and you don't need type safety, would you use ListDictionary over the generic Dictionary. And even then, there's probably more useful performance gains you can make elsewhere.

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  • About Solaris 11 and UltraSPARC II/III/IV/IV+

    - by nospam(at)example.com (Joerg Moellenkamp)
    I know that I will get the usual amount of comments like "Oh, Jörg ? you can't be negative about Oracle" for this article. However as usual I want to explain the logic behind my reasoning. Yes ? I know that there is a lot of UltraSPARC III, IV and IV+ gear out there. But there are some very basic questions: Does your application you are currently running on this gear stops running just because you can't run Solaris 11 on it? What is the need to upgrade a system already in production to Solaris 11? I have the impression, that some people think that the systems get useless in the moment Oracle releases Solaris 11. I know that Sun sold UltraSPARC IV+ systems until 2009. The Sun SF490 introduced 2004 for example, that was a Sun SF480 with UltraSPARC IV and later with UltraSPARC IV+. And yes, Sun made some speedbumps. At that time the systems of the UltraSPARC III to IV+ generations were supported on Solaris 8, on Solaris 9 and on Solaris 10. However from my perspective we sold them to customers, which weren't able to migrate to Solaris 10 because they used applications not supported on Solaris 9 or who just didn't wanted to migrate to Solaris 10. Believe it or not ? I personally know two customers that migrated core systems to Solaris 10 in ? well 2008/9. This was especially true when the M3000 was announced in 2008 when it closed the darned single socket gap. It may be different at you site, however that's what I remember about that time when talking with customers. At first: Just because there is no Solaris 11 for UltraSPARC III, IV and IV+, it doesn't mean that Solaris 10 will go away anytime soon. I just want to point you to "Expect Lifetime Support - Hardware and Operating Systems". It states about Premier Support:Maintenance and software upgrades are included for Oracle operating systems and Oracle VM for a minimum of eight years from the general availability date.GA for Solaris 10 was in 2005. Plus 8 years ? 2013 ? at minimum. Then you can still opt for 3 years of "Extended Support" ? 2016 ? at minimum. 2016 your systems purchased in 2009 are 7 years old. Even on systems purchased at the very end of the lifetime of that system generation. That are the rules as written in the linked document. I said minimum The actual dates are even further in the future: Premier Support for Solaris 10 ends in 2015, Extended support ends 2018. Sustaining support ? indefinite. You will find this in the document "Oracle Lifetime Support Policy: Oracle Hardware and Operating Systems".So I don't understand when some people write, that Oracle is less protective about hardware investments than Sun. And for hardware it's the same as with Sun: Service 5 years after EOL as part of Premier Support. I would like to write about a different perspective as well: I have to be a little cautious here, because this is going in the roadmap area, so I will mention the public sources here: John Fowler told last year that we have to expect at at least 3x the single thread performance of T3 for T4. We have 8 cores in T4, as stated by Rick Hetherington. Let's assume for a moment that a T4 core will have the performance of a UltraSPARC core (just to simplify math and not to disclosing anything about the performance, all existing SPARC cores are considered equal). So given this pieces of information, you could consolidate 8 V215, 4 or 8 V245, 2 full blown V445,2 full blown 490, 2 full blown M3000 on a single T4 SPARC processor. The Fowler roadmap prezo talked about 4-socket systems with T4. So 32 V215, 16 to 8 V245, 8 fullblown V445, 8 full blown V490, 8 full blown M3000 in a system image. I think you get the idea. That said, most of the systems we are talking about have already amortized and perhaps it's just time to invest in new systems to yield other advantages like reduced space consumptions, like reduced power consumption, like some of the neat features sun4v gives you, and yes ? reduced number of processor licenses for Oracle and less money for Oracle HW/SW support. As much as I dislike it myself that my own UltraSPARC III and UltraSPARC II based systems won't run on Solaris 11 (and I have quite a few of them in my personal lab), I really think that the impact on production environments will be much less than most people think now. By the way: The reason for this move is a quite significant new feature. I will tell you that it was this feature, when it's out. I assume, telling just a word more could lead to much more time to blog.

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  • When is my View too smart?

    - by Kyle Burns
    In this posting, I will discuss the motivation behind keeping View code as thin as possible when using patterns such as MVC, MVVM, and MVP.  Once the motivation is identified, I will examine some ways to determine whether a View contains logic that belongs in another part of the application.  While the concepts that I will discuss are applicable to most any pattern which favors a thin View, any concrete examples that I present will center on ASP.NET MVC. Design patterns that include a Model, a View, and other components such as a Controller, ViewModel, or Presenter are not new to application development.  These patterns have, in fact, been around since the early days of building applications with graphical interfaces.  The reason that these patterns emerged is simple – the code running closest to the user tends to be littered with logic and library calls that center around implementation details of showing and manipulating user interface widgets and when this type of code is interspersed with application domain logic it becomes difficult to understand and much more difficult to adequately test.  By removing domain logic from the View, we ensure that the View has a single responsibility of drawing the screen which, in turn, makes our application easier to understand and maintain. I was recently asked to take a look at an ASP.NET MVC View because the developer reviewing it thought that it possibly had too much going on in the view.  I looked at the .CSHTML file and the first thing that occurred to me was that it began with 40 lines of code declaring member variables and performing the necessary calculations to populate these variables, which were later either output directly to the page or used to control some conditional rendering action (such as adding a class name to an HTML element or not rendering another element at all).  This exhibited both of what I consider the primary heuristics (or code smells) indicating that the View is too smart: Member variables – in general, variables in View code are an indication that the Model to which the View is being bound is not sufficient for the needs of the View and that the View has had to augment that Model.  Notable exceptions to this guideline include variables used to hold information specifically related to rendering (such as a dynamically determined CSS class name or the depth within a recursive structure for indentation purposes) and variables which are used to facilitate looping through collections while binding. Arithmetic – as with member variables, the presence of arithmetic operators within View code are an indication that the Model servicing the View is insufficient for its needs.  For example, if the Model represents a line item in a sales order, it might seem perfectly natural to “normalize” the Model by storing the quantity and unit price in the Model and multiply these within the View to show the line total.  While this does seem natural, it introduces a business rule to the View code and makes it impossible to test that the rounding of the result meets the requirement of the business without executing the View.  Within View code, arithmetic should only be used for activities such as incrementing loop counters and calculating element widths. In addition to the two characteristics of a “Smart View” that I’ve discussed already, this View also exhibited another heuristic that commonly indicates to me the need to refactor a View and make it a bit less smart.  That characteristic is the existence of Boolean logic that either does not work directly with properties of the Model or works with too many properties of the Model.  Consider the following code and consider how logic that does not work directly with properties of the Model is just another form of the “member variable” heuristic covered earlier: @if(DateTime.Now.Hour < 12) {     <div>Good Morning!</div> } else {     <div>Greetings</div> } This code performs business logic to determine whether it is morning.  A possible refactoring would be to add an IsMorning property to the Model, but in this particular case there is enough similarity between the branches that the entire branching structure could be collapsed by adding a Greeting property to the Model and using it similarly to the following: <div>@Model.Greeting</div> Now let’s look at some complex logic around multiple Model properties: @if (ModelPageNumber + Model.NumbersToDisplay == Model.PageCount         || (Model.PageCount != Model.CurrentPage             && !Model.DisplayValues.Contains(Model.PageCount))) {     <div>There's more to see!</div> } In this scenario, not only is the View code difficult to read (you shouldn’t have to play “human compiler” to determine the purpose of the code), but it also complex enough to be at risk for logical errors that cannot be detected without executing the View.  Conditional logic that requires more than a single logical operator should be looked at more closely to determine whether the condition should be evaluated elsewhere and exposed as a single property of the Model.  Moving the logic above outside of the View and exposing a new Model property would simplify the View code to: @if(Model.HasMoreToSee) {     <div>There’s more to see!</div> } In this posting I have briefly discussed some of the more prominent heuristics that indicate a need to push code from the View into other pieces of the application.  You should now be able to recognize these symptoms when building or maintaining Views (or the Models that support them) in your applications.

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  • Using R to Analyze G1GC Log Files

    - by user12620111
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  Using R to Analyze G1GC Log Files   Using R to Analyze G1GC Log Files Introduction Working in Oracle Platform Integration gives an engineer opportunities to work on a wide array of technologies. My team’s goal is to make Oracle applications run best on the Solaris/SPARC platform. When looking for bottlenecks in a modern applications, one needs to be aware of not only how the CPUs and operating system are executing, but also network, storage, and in some cases, the Java Virtual Machine. I was recently presented with about 1.5 GB of Java Garbage First Garbage Collector log file data. If you’re not familiar with the subject, you might want to review Garbage First Garbage Collector Tuning by Monica Beckwith. The customer had been running Java HotSpot 1.6.0_31 to host a web application server. I was told that the Solaris/SPARC server was running a Java process launched using a commmand line that included the following flags: -d64 -Xms9g -Xmx9g -XX:+UseG1GC -XX:MaxGCPauseMillis=200 -XX:InitiatingHeapOccupancyPercent=80 -XX:PermSize=256m -XX:MaxPermSize=256m -XX:+PrintGC -XX:+PrintGCTimeStamps -XX:+PrintHeapAtGC -XX:+PrintGCDateStamps -XX:+PrintFlagsFinal -XX:+DisableExplicitGC -XX:+UnlockExperimentalVMOptions -XX:ParallelGCThreads=8 Several sources on the internet indicate that if I were to print out the 1.5 GB of log files, it would require enough paper to fill the bed of a pick up truck. Of course, it would be fruitless to try to scan the log files by hand. Tools will be required to summarize the contents of the log files. Others have encountered large Java garbage collection log files. There are existing tools to analyze the log files: IBM’s GC toolkit The chewiebug GCViewer gchisto HPjmeter Instead of using one of the other tools listed, I decide to parse the log files with standard Unix tools, and analyze the data with R. Data Cleansing The log files arrived in two different formats. I guess that the difference is that one set of log files was generated using a more verbose option, maybe -XX:+PrintHeapAtGC, and the other set of log files was generated without that option. Format 1 In some of the log files, the log files with the less verbose format, a single trace, i.e. the report of a singe garbage collection event, looks like this: {Heap before GC invocations=12280 (full 61): garbage-first heap total 9437184K, used 7499918K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 1 young (4096K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. 2014-05-14T07:24:00.988-0700: 60586.353: [GC pause (young) 7324M->7320M(9216M), 0.1567265 secs] Heap after GC invocations=12281 (full 61): garbage-first heap total 9437184K, used 7496533K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) region size 4096K, 0 young (0K), 0 survivors (0K) compacting perm gen total 262144K, used 144077K [0xffffffff40000000, 0xffffffff50000000, 0xffffffff50000000) the space 262144K, 54% used [0xffffffff40000000, 0xffffffff48cb3758, 0xffffffff48cb3800, 0xffffffff50000000) No shared spaces configured. } A simple grep can be used to extract a summary: $ grep "\[ GC pause (young" g1gc.log 2014-05-13T13:24:35.091-0700: 3.109: [GC pause (young) 20M->5029K(9216M), 0.0146328 secs] 2014-05-13T13:24:35.440-0700: 3.459: [GC pause (young) 9125K->6077K(9216M), 0.0086723 secs] 2014-05-13T13:24:37.581-0700: 5.599: [GC pause (young) 25M->8470K(9216M), 0.0203820 secs] 2014-05-13T13:24:42.686-0700: 10.704: [GC pause (young) 44M->15M(9216M), 0.0288848 secs] 2014-05-13T13:24:48.941-0700: 16.958: [GC pause (young) 51M->20M(9216M), 0.0491244 secs] 2014-05-13T13:24:56.049-0700: 24.066: [GC pause (young) 92M->26M(9216M), 0.0525368 secs] 2014-05-13T13:25:34.368-0700: 62.383: [GC pause (young) 602M->68M(9216M), 0.1721173 secs] But that format wasn't easily read into R, so I needed to be a bit more tricky. I used the following Unix command to create a summary file that was easy for R to read. $ echo "SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime" $ grep "\[GC pause (young" g1gc.log | grep -v mark | sed -e 's/[A-SU-z\(\),]/ /g' -e 's/->/ /' -e 's/: / /g' | more SecondsSinceLaunch BeforeSize AfterSize TotalSize RealTime 2014-05-13T13:24:35.091-0700 3.109 20 5029 9216 0.0146328 2014-05-13T13:24:35.440-0700 3.459 9125 6077 9216 0.0086723 2014-05-13T13:24:37.581-0700 5.599 25 8470 9216 0.0203820 2014-05-13T13:24:42.686-0700 10.704 44 15 9216 0.0288848 2014-05-13T13:24:48.941-0700 16.958 51 20 9216 0.0491244 2014-05-13T13:24:56.049-0700 24.066 92 26 9216 0.0525368 2014-05-13T13:25:34.368-0700 62.383 602 68 9216 0.1721173 Format 2 In some of the log files, the log files with the more verbose format, a single trace, i.e. the report of a singe garbage collection event, was more complicated than Format 1. Here is a text file with an example of a single G1GC trace in the second format. As you can see, it is quite complicated. It is nice that there is so much information available, but the level of detail can be overwhelming. I wrote this awk script (download) to summarize each trace on a single line. #!/usr/bin/env awk -f BEGIN { printf("SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize\n") } ###################### # Save count data from lines that are at the start of each G1GC trace. # Each trace starts out like this: # {Heap before GC invocations=14 (full 0): # garbage-first heap total 9437184K, used 325496K [0xfffffffd00000000, 0xffffffff40000000, 0xffffffff40000000) ###################### /{Heap.*full/{ gsub ( "\\)" , "" ); nf=split($0,a,"="); split(a[2],b," "); getline; if ( match($0, "first") ) { G1GC=1; IncrementalCount=b[1]; FullCount=substr( b[3], 1, length(b[3])-1 ); } else { G1GC=0; } } ###################### # Pull out time stamps that are in lines with this format: # 2014-05-12T14:02:06.025-0700: 94.312: [GC pause (young), 0.08870154 secs] ###################### /GC pause/ { DateTime=$1; SecondsSinceLaunch=substr($2, 1, length($2)-1); } ###################### # Heap sizes are in lines that look like this: # [ 4842M->4838M(9216M)] ###################### /\[ .*]$/ { gsub ( "\\[" , "" ); gsub ( "\ \]" , "" ); gsub ( "->" , " " ); gsub ( "\\( " , " " ); gsub ( "\ \)" , " " ); split($0,a," "); if ( split(a[1],b,"M") > 1 ) {BeforeSize=b[1]*1024;} if ( split(a[1],b,"K") > 1 ) {BeforeSize=b[1];} if ( split(a[2],b,"M") > 1 ) {AfterSize=b[1]*1024;} if ( split(a[2],b,"K") > 1 ) {AfterSize=b[1];} if ( split(a[3],b,"M") > 1 ) {TotalSize=b[1]*1024;} if ( split(a[3],b,"K") > 1 ) {TotalSize=b[1];} } ###################### # Emit an output line when you find input that looks like this: # [Times: user=1.41 sys=0.08, real=0.24 secs] ###################### /\[Times/ { if (G1GC==1) { gsub ( "," , "" ); split($2,a,"="); UserTime=a[2]; split($3,a,"="); SysTime=a[2]; split($4,a,"="); RealTime=a[2]; print DateTime,SecondsSinceLaunch,IncrementalCount,FullCount,UserTime,SysTime,RealTime,BeforeSize,AfterSize,TotalSize; G1GC=0; } } The resulting summary is about 25X smaller that the original file, but still difficult for a human to digest. SecondsSinceLaunch IncrementalCount FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ... 2014-05-12T18:36:34.669-0700: 3985.744 561 0 0.57 0.06 0.16 1724416 1720320 9437184 2014-05-12T18:36:34.839-0700: 3985.914 562 0 0.51 0.06 0.19 1724416 1720320 9437184 2014-05-12T18:36:35.069-0700: 3986.144 563 0 0.60 0.04 0.27 1724416 1721344 9437184 2014-05-12T18:36:35.354-0700: 3986.429 564 0 0.33 0.04 0.09 1725440 1722368 9437184 2014-05-12T18:36:35.545-0700: 3986.620 565 0 0.58 0.04 0.17 1726464 1722368 9437184 2014-05-12T18:36:35.726-0700: 3986.801 566 0 0.43 0.05 0.12 1726464 1722368 9437184 2014-05-12T18:36:35.856-0700: 3986.930 567 0 0.30 0.04 0.07 1726464 1723392 9437184 2014-05-12T18:36:35.947-0700: 3987.023 568 0 0.61 0.04 0.26 1727488 1723392 9437184 2014-05-12T18:36:36.228-0700: 3987.302 569 0 0.46 0.04 0.16 1731584 1724416 9437184 Reading the Data into R Once the GC log data had been cleansed, either by processing the first format with the shell script, or by processing the second format with the awk script, it was easy to read the data into R. g1gc.df = read.csv("summary.txt", row.names = NULL, stringsAsFactors=FALSE,sep="") str(g1gc.df) ## 'data.frame': 8307 obs. of 10 variables: ## $ row.names : chr "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ... ## $ SecondsSinceLaunch: num 1.16 1.47 1.97 3.83 6.1 ... ## $ IncrementalCount : int 0 1 2 3 4 5 6 7 8 9 ... ## $ FullCount : int 0 0 0 0 0 0 0 0 0 0 ... ## $ UserTime : num 0.11 0.05 0.04 0.21 0.08 0.26 0.31 0.33 0.34 0.56 ... ## $ SysTime : num 0.04 0.01 0.01 0.05 0.01 0.06 0.07 0.06 0.07 0.09 ... ## $ RealTime : num 0.02 0.02 0.01 0.04 0.02 0.04 0.05 0.04 0.04 0.06 ... ## $ BeforeSize : int 8192 5496 5768 22528 24576 43008 34816 53248 55296 93184 ... ## $ AfterSize : int 1400 1672 2557 4907 7072 14336 16384 18432 19456 21504 ... ## $ TotalSize : int 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 9437184 ... head(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount ## 1 2014-05-12T14:00:32.868-0700: 1.161 0 ## 2 2014-05-12T14:00:33.179-0700: 1.472 1 ## 3 2014-05-12T14:00:33.677-0700: 1.969 2 ## 4 2014-05-12T14:00:35.538-0700: 3.830 3 ## 5 2014-05-12T14:00:37.811-0700: 6.103 4 ## 6 2014-05-12T14:00:41.428-0700: 9.720 5 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 1 0 0.11 0.04 0.02 8192 1400 9437184 ## 2 0 0.05 0.01 0.02 5496 1672 9437184 ## 3 0 0.04 0.01 0.01 5768 2557 9437184 ## 4 0 0.21 0.05 0.04 22528 4907 9437184 ## 5 0 0.08 0.01 0.02 24576 7072 9437184 ## 6 0 0.26 0.06 0.04 43008 14336 9437184 Basic Statistics Once the data has been read into R, simple statistics are very easy to generate. All of the numbers from high school statistics are available via simple commands. For example, generate a summary of every column: summary(g1gc.df) ## row.names SecondsSinceLaunch IncrementalCount FullCount ## Length:8307 Min. : 1 Min. : 0 Min. : 0.0 ## Class :character 1st Qu.: 9977 1st Qu.:2048 1st Qu.: 0.0 ## Mode :character Median :12855 Median :4136 Median : 12.0 ## Mean :12527 Mean :4156 Mean : 31.6 ## 3rd Qu.:15758 3rd Qu.:6262 3rd Qu.: 61.0 ## Max. :55484 Max. :8391 Max. :113.0 ## UserTime SysTime RealTime BeforeSize ## Min. :0.040 Min. :0.0000 Min. : 0.0 Min. : 5476 ## 1st Qu.:0.470 1st Qu.:0.0300 1st Qu.: 0.1 1st Qu.:5137920 ## Median :0.620 Median :0.0300 Median : 0.1 Median :6574080 ## Mean :0.751 Mean :0.0355 Mean : 0.3 Mean :5841855 ## 3rd Qu.:0.920 3rd Qu.:0.0400 3rd Qu.: 0.2 3rd Qu.:7084032 ## Max. :3.370 Max. :1.5600 Max. :488.1 Max. :8696832 ## AfterSize TotalSize ## Min. : 1380 Min. :9437184 ## 1st Qu.:5002752 1st Qu.:9437184 ## Median :6559744 Median :9437184 ## Mean :5785454 Mean :9437184 ## 3rd Qu.:7054336 3rd Qu.:9437184 ## Max. :8482816 Max. :9437184 Q: What is the total amount of User CPU time spent in garbage collection? sum(g1gc.df$UserTime) ## [1] 6236 As you can see, less than two hours of CPU time was spent in garbage collection. Is that too much? To find the percentage of time spent in garbage collection, divide the number above by total_elapsed_time*CPU_count. In this case, there are a lot of CPU’s and it turns out the the overall amount of CPU time spent in garbage collection isn’t a problem when viewed in isolation. When calculating rates, i.e. events per unit time, you need to ask yourself if the rate is homogenous across the time period in the log file. Does the log file include spikes of high activity that should be separately analyzed? Averaging in data from nights and weekends with data from business hours may alias problems. If you have a reason to suspect that the garbage collection rates include peaks and valleys that need independent analysis, see the “Time Series” section, below. Q: How much garbage is collected on each pass? The amount of heap space that is recovered per GC pass is surprisingly low: At least one collection didn’t recover any data. (“Min.=0”) 25% of the passes recovered 3MB or less. (“1st Qu.=3072”) Half of the GC passes recovered 4MB or less. (“Median=4096”) The average amount recovered was 56MB. (“Mean=56390”) 75% of the passes recovered 36MB or less. (“3rd Qu.=36860”) At least one pass recovered 2GB. (“Max.=2121000”) g1gc.df$Delta = g1gc.df$BeforeSize - g1gc.df$AfterSize summary(g1gc.df$Delta) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0 3070 4100 56400 36900 2120000 Q: What is the maximum User CPU time for a single collection? The worst garbage collection (“Max.”) is many standard deviations away from the mean. The data appears to be right skewed. summary(g1gc.df$UserTime) ## Min. 1st Qu. Median Mean 3rd Qu. Max. ## 0.040 0.470 0.620 0.751 0.920 3.370 sd(g1gc.df$UserTime) ## [1] 0.3966 Basic Graphics Once the data is in R, it is trivial to plot the data with formats including dot plots, line charts, bar charts (simple, stacked, grouped), pie charts, boxplots, scatter plots histograms, and kernel density plots. Histogram of User CPU Time per Collection I don't think that this graph requires any explanation. hist(g1gc.df$UserTime, main="User CPU Time per Collection", xlab="Seconds", ylab="Frequency") Box plot to identify outliers When the initial data is viewed with a box plot, you can see the one crazy outlier in the real time per GC. Save this data point for future analysis and drop the outlier so that it’s not throwing off our statistics. Now the box plot shows many outliers, which will be examined later, using times series analysis. Notice that the scale of the x-axis changes drastically once the crazy outlier is removed. par(mfrow=c(2,1)) boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(dominated by a crazy outlier)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") crazy.outlier.df=g1gc.df[g1gc.df$RealTime > 400,] g1gc.df=g1gc.df[g1gc.df$RealTime < 400,] boxplot(g1gc.df$UserTime,g1gc.df$SysTime,g1gc.df$RealTime, main="Box Plot of Time per GC\n(crazy outlier excluded)", names=c("usr","sys","elapsed"), xlab="Seconds per GC", ylab="Time (Seconds)", horizontal = TRUE, outcol="red") box(which = "outer", lty = "solid") Here is the crazy outlier for future analysis: crazy.outlier.df ## row.names SecondsSinceLaunch IncrementalCount ## 8233 2014-05-12T23:15:43.903-0700: 20741 8316 ## FullCount UserTime SysTime RealTime BeforeSize AfterSize TotalSize ## 8233 112 0.55 0.42 488.1 8381440 8235008 9437184 ## Delta ## 8233 146432 R Time Series Data To analyze the garbage collection as a time series, I’ll use Z’s Ordered Observations (zoo). “zoo is the creator for an S3 class of indexed totally ordered observations which includes irregular time series.” require(zoo) ## Loading required package: zoo ## ## Attaching package: 'zoo' ## ## The following objects are masked from 'package:base': ## ## as.Date, as.Date.numeric head(g1gc.df[,1]) ## [1] "2014-05-12T14:00:32.868-0700:" "2014-05-12T14:00:33.179-0700:" ## [3] "2014-05-12T14:00:33.677-0700:" "2014-05-12T14:00:35.538-0700:" ## [5] "2014-05-12T14:00:37.811-0700:" "2014-05-12T14:00:41.428-0700:" options("digits.secs"=3) times=as.POSIXct( g1gc.df[,1], format="%Y-%m-%dT%H:%M:%OS%z:") g1gc.z = zoo(g1gc.df[,-c(1)], order.by=times) head(g1gc.z) ## SecondsSinceLaunch IncrementalCount FullCount ## 2014-05-12 17:00:32.868 1.161 0 0 ## 2014-05-12 17:00:33.178 1.472 1 0 ## 2014-05-12 17:00:33.677 1.969 2 0 ## 2014-05-12 17:00:35.538 3.830 3 0 ## 2014-05-12 17:00:37.811 6.103 4 0 ## 2014-05-12 17:00:41.427 9.720 5 0 ## UserTime SysTime RealTime BeforeSize AfterSize ## 2014-05-12 17:00:32.868 0.11 0.04 0.02 8192 1400 ## 2014-05-12 17:00:33.178 0.05 0.01 0.02 5496 1672 ## 2014-05-12 17:00:33.677 0.04 0.01 0.01 5768 2557 ## 2014-05-12 17:00:35.538 0.21 0.05 0.04 22528 4907 ## 2014-05-12 17:00:37.811 0.08 0.01 0.02 24576 7072 ## 2014-05-12 17:00:41.427 0.26 0.06 0.04 43008 14336 ## TotalSize Delta ## 2014-05-12 17:00:32.868 9437184 6792 ## 2014-05-12 17:00:33.178 9437184 3824 ## 2014-05-12 17:00:33.677 9437184 3211 ## 2014-05-12 17:00:35.538 9437184 17621 ## 2014-05-12 17:00:37.811 9437184 17504 ## 2014-05-12 17:00:41.427 9437184 28672 Example of Two Benchmark Runs in One Log File The data in the following graph is from a different log file, not the one of primary interest to this article. I’m including this image because it is an example of idle periods followed by busy periods. It would be uninteresting to average the rate of garbage collection over the entire log file period. More interesting would be the rate of garbage collect in the two busy periods. Are they the same or different? Your production data may be similar, for example, bursts when employees return from lunch and idle times on weekend evenings, etc. Once the data is in an R Time Series, you can analyze isolated time windows. Clipping the Time Series data Flashing back to our test case… Viewing the data as a time series is interesting. You can see that the work intensive time period is between 9:00 PM and 3:00 AM. Lets clip the data to the interesting period:     par(mfrow=c(2,1)) plot(g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Complete Log File", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") clipped.g1gc.z=window(g1gc.z, start=as.POSIXct("2014-05-12 21:00:00"), end=as.POSIXct("2014-05-13 03:00:00")) plot(clipped.g1gc.z$UserTime, type="h", main="User Time per GC\nTime: Limited to Benchmark Execution", xlab="Time of Day", ylab="CPU Seconds per GC", col="#1b9e77") box(which = "outer", lty = "solid") Cumulative Incremental and Full GC count Here is the cumulative incremental and full GC count. When the line is very steep, it indicates that the GCs are repeating very quickly. Notice that the scale on the Y axis is different for full vs. incremental. plot(clipped.g1gc.z[,c(2:3)], main="Cumulative Incremental and Full GC count", xlab="Time of Day", col="#1b9e77") GC Analysis of Benchmark Execution using Time Series data In the following series of 3 graphs: The “After Size” show the amount of heap space in use after each garbage collection. Many Java objects are still referenced, i.e. alive, during each garbage collection. This may indicate that the application has a memory leak, or may indicate that the application has a very large memory footprint. Typically, an application's memory footprint plateau's in the early stage of execution. One would expect this graph to have a flat top. The steep decline in the heap space may indicate that the application crashed after 2:00. The second graph shows that the outliers in real execution time, discussed above, occur near 2:00. when the Java heap seems to be quite full. The third graph shows that Full GCs are infrequent during the first few hours of execution. The rate of Full GC's, (the slope of the cummulative Full GC line), changes near midnight.   plot(clipped.g1gc.z[,c("AfterSize","RealTime","FullCount")], xlab="Time of Day", col=c("#1b9e77","red","#1b9e77")) GC Analysis of heap recovered Each GC trace includes the amount of heap space in use before and after the individual GC event. During garbage coolection, unreferenced objects are identified, the space holding the unreferenced objects is freed, and thus, the difference in before and after usage indicates how much space has been freed. The following box plot and bar chart both demonstrate the same point - the amount of heap space freed per garbage colloection is surprisingly low. par(mfrow=c(2,1)) boxplot(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", horizontal = TRUE, col="red") hist(as.vector(clipped.g1gc.z$Delta), main="Amount of Heap Recovered per GC Pass", xlab="Size in KB", breaks=100, col="red") box(which = "outer", lty = "solid") This graph is the most interesting. The dark blue area shows how much heap is occupied by referenced Java objects. This represents memory that holds live data. The red fringe at the top shows how much data was recovered after each garbage collection. barplot(clipped.g1gc.z[,c("AfterSize","Delta")], col=c("#7570b3","#e7298a"), xlab="Time of Day", border=NA) legend("topleft", c("Live Objects","Heap Recovered on GC"), fill=c("#7570b3","#e7298a")) box(which = "outer", lty = "solid") When I discuss the data in the log files with the customer, I will ask for an explaination for the large amount of referenced data resident in the Java heap. There are two are posibilities: There is a memory leak and the amount of space required to hold referenced objects will continue to grow, limited only by the maximum heap size. After the maximum heap size is reached, the JVM will throw an “Out of Memory” exception every time that the application tries to allocate a new object. If this is the case, the aplication needs to be debugged to identify why old objects are referenced when they are no longer needed. The application has a legitimate requirement to keep a large amount of data in memory. The customer may want to further increase the maximum heap size. Another possible solution would be to partition the application across multiple cluster nodes, where each node has responsibility for managing a unique subset of the data. Conclusion In conclusion, R is a very powerful tool for the analysis of Java garbage collection log files. The primary difficulty is data cleansing so that information can be read into an R data frame. Once the data has been read into R, a rich set of tools may be used for thorough evaluation.

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  • Using XA Transactions in Coherence-based Applications

    - by jpurdy
    While the costs of XA transactions are well known (e.g. increased data contention, higher latency, significant disk I/O for logging, availability challenges, etc.), in many cases they are the most attractive option for coordinating logical transactions across multiple resources. There are a few common approaches when integrating Coherence into applications via the use of an application server's transaction manager: Use of Coherence as a read-only cache, applying transactions to the underlying database (or any system of record) instead of the cache. Use of TransactionMap interface via the included resource adapter. Use of the new ACID transaction framework, introduced in Coherence 3.6.   Each of these may have significant drawbacks for certain workloads. Using Coherence as a read-only cache is the simplest option. In this approach, the application is responsible for managing both the database and the cache (either within the business logic or via application server hooks). This approach also tends to provide limited benefit for many workloads, particularly those workloads that either have queries (given the complexity of maintaining a fully cached data set in Coherence) or are not read-heavy (where the cost of managing the cache may outweigh the benefits of reading from it). All updates are made synchronously to the database, leaving it as both a source of latency as well as a potential bottleneck. This approach also prevents addressing "hot data" problems (when certain objects are updated by many concurrent transactions) since most database servers offer no facilities for explicitly controlling concurrent updates. Finally, this option tends to be a better fit for key-based access (rather than filter-based access such as queries) since this makes it easier to aggressively invalidate cache entries without worrying about when they will be reloaded. The advantage of this approach is that it allows strong data consistency as long as optimistic concurrency control is used to ensure that database updates are applied correctly regardless of whether the cache contains stale (or even dirty) data. Another benefit of this approach is that it avoids the limitations of Coherence's write-through caching implementation. TransactionMap is generally used when Coherence acts as system of record. TransactionMap is not generally compatible with write-through caching, so it will usually be either used to manage a standalone cache or when the cache is backed by a database via write-behind caching. TransactionMap has some restrictions that may limit its utility, the most significant being: The lock-based concurrency model is relatively inefficient and may introduce significant latency and contention. As an example, in a typical configuration, a transaction that updates 20 cache entries will require roughly 40ms just for lock management (assuming all locks are granted immediately, and excluding validation and writing which will require a similar amount of time). This may be partially mitigated by denormalizing (e.g. combining a parent object and its set of child objects into a single cache entry), at the cost of increasing false contention (e.g. transactions will conflict even when updating different child objects). If the client (application server JVM) fails during the commit phase, locks will be released immediately, and the transaction may be partially committed. In practice, this is usually not as bad as it may sound since the commit phase is usually very short (all locks having been previously acquired). Note that this vulnerability does not exist when a single NamedCache is used and all updates are confined to a single partition (generally implying the use of partition affinity). The unconventional TransactionMap API is cumbersome but manageable. Only a few methods are transactional, primarily get(), put() and remove(). The ACID transactions framework (accessed via the Connection class) provides atomicity guarantees by implementing the NamedCache interface, maintaining its own cache data and transaction logs inside a set of private partitioned caches. This feature may be used as either a local transactional resource or as logging XA resource. However, a lack of database integration precludes the use of this functionality for most applications. A side effect of this is that this feature has not seen significant adoption, meaning that any use of this is subject to the usual headaches associated with being an early adopter (greater chance of bugs and greater risk of hitting an unoptimized code path). As a result, for the moment, we generally recommend against using this feature. In summary, it is possible to use Coherence in XA-oriented applications, and several customers are doing this successfully, but it is not a core usage model for the product, so care should be taken before committing to this path. For most applications, the most robust solution is normally to use Coherence as a read-only cache of the underlying data resources, even if this prevents taking advantage of certain product features.

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  • WinVerifyTrust API problem

    - by Shayan
    I'm using WinVerifyTrust API in windows XP and I don't want any kind of user interaction. But when I set the WTD_UI_NONE attribute, although it doesn't show any dialog boxes, but it waits for a long time on the files that in fact wanted user interaction (I mean files which without mentioning the NO UI it will ask the user for that file). This is my code: WINTRUST_FILE_INFO FileData; memset(&FileData, 0, sizeof(FileData)); FileData.cbStruct = sizeof(WINTRUST_FILE_INFO); wchar_t fileName[32769]; FileData.pcwszFilePath = fileName; FileData.hFile = NULL; FileData.pgKnownSubject = NULL; /* WVTPolicyGUID specifies the policy to apply on the file WINTRUST_ACTION_GENERIC_VERIFY_V2 policy checks: 1) The certificate used to sign the file chains up to a root certificate located in the trusted root certificate store. This implies that the identity of the publisher has been verified by a certification authority. 2) In cases where user interface is displayed (which this example does not do), WinVerifyTrust will check for whether the end entity certificate is stored in the trusted publisher store, implying that the user trusts content from this publisher. 3) The end entity certificate has sufficient permission to sign code, as indicated by the presence of a code signing EKU or no EKU. */ GUID WVTPolicyGUID = WINTRUST_ACTION_GENERIC_VERIFY_V2; WINTRUST_DATA WinTrustData; // Initialize the WinVerifyTrust input data structure. // Default all fields to 0. memset(&WinTrustData, 0, sizeof(WinTrustData)); WinTrustData.cbStruct = sizeof(WinTrustData); // Use default code signing EKU. WinTrustData.pPolicyCallbackData = NULL; // No data to pass to SIP. WinTrustData.pSIPClientData = NULL; // Disable WVT UI. WinTrustData.dwUIChoice = WTD_UI_NONE; // No revocation checking. WinTrustData.fdwRevocationChecks = WTD_REVOKE_NONE; // Verify an embedded signature on a file. WinTrustData.dwUnionChoice = WTD_CHOICE_FILE; // Default verification. WinTrustData.dwStateAction = 0; // Not applicable for default verification of embedded signature. WinTrustData.hWVTStateData = NULL; // Not used. WinTrustData.pwszURLReference = NULL; // Default. WinTrustData.dwProvFlags = WTD_REVOCATION_CHECK_END_CERT; // This is not applicable if there is no UI because it changes // the UI to accommodate running applications instead of // installing applications. WinTrustData.dwUIContext = 0; // Set pFile. WinTrustData.pFile = &FileData; // WinVerifyTrust verifies signatures as specified by the GUID // and Wintrust_Data. lStatus = WinVerifyTrust( (HWND)INVALID_HANDLE_VALUE, &WVTPolicyGUID, &WinTrustData); printf("%x\n", lStatus);

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  • [C#] Convert string to double with 2 digit after decimal separator

    - by st.stoqnov
    All began with these simple lines of code: string s = "16.9"; double d = Convert.ToDouble(s); d*=100; The result should be 1690.0, but it's not. d is equal to 1689.9999999999998. All I want to do is to round a double to value with 2 digit after decimal separator. Here is my function. private double RoundFloat(double Value) { float sign = (Value < 0) ? -0.01f : 0.01f; if (Math.Abs(Value) < 0.00001) Value = 0; string SVal = Value.ToString(); string DecimalSeparator = System.Globalization.CultureInfo.CurrentCulture.NumberFormat.CurrencyDecimalSeparator; int i = SVal.IndexOf(DecimalSeparator); if (i > 0) { int SRnd; try { // ????? ??????? ????? ???? ?????????? ?????????? SRnd = Convert.ToInt32(SVal.Substring(i + 3, 1)); } catch { SRnd = 0; } if (SVal.Length > i + 3) SVal = SVal.Substring(0, i + 3); //SVal += "00001"; try { double result = (SRnd >= 5) ? Convert.ToDouble(SVal) + sign : Convert.ToDouble(SVal); //result = Math.Round(result, 2); return result; } catch { return 0; } } else { return Value; } But again the same problem, converting from string to double is not working as I want. A workaround to this problem is to concatenate "00001" to the string and then use the Math.Round function (commented in the example above). This double value multiplied to 100 (as integer) is send to a device (cash register) and this values must be correct. I am using VS2005 + .NET CF 2.0 Is there another more "elegant" solution, I am not happy with this one.

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  • iPhone App IDs and Provisioning... Does App ID get used instead of provisioning ID if I decide to us

    - by Jann
    This is a question that has been bugging me for a while. I started my app (now submitted -- not yet approved) not wishing to get into the mess that is APNS (Push). I did the following: iPhone Developer Center: Provisioning Portal-Provisioning: Then I created a Development and a Distribution Provisioning Profile. I installed both in XCode. Everything hunky dory. The Development profile scares me a bit by expiring so soon (90 days) but I can remove it from the iPhone(s) and sign it with a new one later. I tested using the Development profile, and later to submitted it by signing it with the Distribution profile. I then uploaded the Distribution profile-signed app to iTunesConnect (app store). Okay, I understand that much. Now, what I don't understand is this: Now that I understand the theories and methods behind how Push works, I am wishing to add it to my app. I already went under: iPhone Developer Center: Provisioning Portal-App IDs: and created a Development Provisioning Profile and Distribution Provisioning Profile there (push & in-app purchase enabled). Here is where it gets confusing to me. All the books and docs I have read say that I have to sign the app with this "App ID" provisioning profile (push-enabled) from now on. Does that mean I no longer ever use the previously created provisioning profiles? If I were to import these "App ID" provisioning profiles into Xcode they will exist alongside my previously generated "non-push" profiles. ~/Library/Mobile Devices/Provisioning Profiles now has 2 files. One Devel and one Distrib. It will now have 4 even though for this app I will not use the "non-push" anymore right? (actually, since they are locked by using bundle-codes and app ids i will never use it again if all of my further versions of this app use Push?) Confused. Can anyone enlighten me? Why not use the "App ID" profiles in the first place for everyone -- even if you are not gonna use push? Would keep it simpler. Should I only generate "Push Enabled" profiles from now on -- even if i am not sure I am gonna use push (or for that matter in-app purchase)? Please give me some insight. I do not wanna do this wrong. Thanks! Jann

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  • VS 2010 Profiling Problem with Signed Assemblies

    - by Binder
    I have a website that uses AjaxControlToolkit.dll and Log4Net.dll; When I try to run the performance profiling tool in VS 2010 on it it gives me the following warnings "AjaxControlToolkit.dll is signed and instrumenting it will invalidate its signature. If you proceed without a post-instrument event to re-sign the binary it may not load correctly". Now, if I choose the option to continue without re-signing the profiling starts but the assembly doesn't load and gives an ASP.NET exception.

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  • two's complement, why the name "two"

    - by lenatis
    i know unsigned,two's complement, ones' complement and sign magnitude, and the difference between these, but what i'm curious about is: why it's called two's(or ones') complement, so is there a more generalize N's complement? in which way did these genius deduce such a natural way to represent negative numbers?

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  • .Net/C# - Pros and cons using the GAC

    - by Adi barad
    Hi Guys, I would like to hear your opinion regarding the benefits of disadvantages of using the GAC in .Net applications. To me, it looks more professional to sign & register the application dlls in the GAC. It's more secure, helps with backward compatibility, side by side installations and easy to reference for end-users. But I want to hear the other side as well. Thank you very much, Adi Barda

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  • SQL 2008 R2 login/network issue

    - by martinjd
    I have a Windows Server 2008 R2 new clean install , not a VM, that I have added to a Windows Server 2003 based domain using my account which has domain admin rights. The domain functional level is 2003. I performed a clean install of SQL Server 2008 R2 using my account which has domain admin rights. The installation completed without any errors. I logged into SSMS locally and attempted to add another domain account by clicking Search, Advanced and finding the user in the domain. When I return to the "Dialog - New" window and click OK I receive the following error: Create failed for Login 'Domain\User'. (Microsoft.SqlServer.Smo) An exception occurred while executing a Transact-SQL statement or batch. (Microsoft.SqlServer.ConnectionInfo) Windows NT user or group 'Domain\User' not found. Check the name again. (Microsoft SQL Server, Error: 15401) I have verified that the firewall is off, tried adding a different domain user, tried using SA to add a user, installed the hotfix for KB 976494 and verified that the Local Security Policy for Domain Member: Digitally encrypt or sign secure channel Domain Member: Digitally encrypt secure channel Domain Member: Digitally sign secure channel are disabled none of which have made a difference. I can RDP to a Server 2003 server running SQL 2008 and add the same domain user without issue. Also if I try to connect with SSMS to the sql server from another system on the domain using my account I get the following error: Login failed. The login is from an untrusted domain and cannot be used with Windows authentication. (Microsoft SQL Server, Error: 18452) and on the database server I see the following in the security event log: An account failed to log on. Subject: Security ID: NULL SID Account Name: - Account Domain: - Logon ID: 0x0 Logon Type: 3 Account For Which Logon Failed: Security ID: NULL SID Account Name: myUserName Account Domain: MYDOMAIN Failure Information: Failure Reason: An Error occured during Logon. Status: 0xc000018d Sub Status: 0x0 Process Information: Caller Process ID: 0x0 Caller Process Name: - Network Information: Workstation Name: MYWKS Source Network Address: - Source Port: - Detailed Authentication Information: Logon Process: NtLmSsp Authentication Package: NTLM Transited Services: - Package Name (NTLM only): - Key Length: 0 I am sure that the "NULL SID" has some significant meaning but have no idea at this point what the issue could be.

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  • .submit() doesn't work with Firefox and Greasemonkey...

    - by Shady
    I'm trying to make an auto login script and I'm stuck on the submit part... The source of the submit form from the website is <input type="submit" value="Sign In" class="signin" id="sumbitLogin"> and I'm trying document.getElementById("sumbitLogin").submit(); if I set an Attribute, for example the value, it changes just fine... How can I solve it?

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  • DC: Mac Developer vs iPhone Developer

    - by Khou
    http://developer.apple.com/programs/ so whats the difference between Mac Developer and iPhone Developer membership? If you signup to Mac Developer you can download the iPhone SDK anyways? so why would you sign to iphone developer?

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  • Visual Sourcesafe, sharing: commits to wrong location

    - by Snake
    I have a project under my management. It has the following structure: $/Code/MainSolution $/Code/Branches I want to branch the MainSolution in $/Code/Branches So I do it, (it works perfectly), I set a working folder for that project and do a 'get latest'. But when I open that solution in Visual Studio 2005 it identifies every file as new (+ sign in front of the file) and when I commit it it goes to $/Data/NameOfTheBranch Why does it do that? Why doesn't it follow MY rules?

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  • How to re codesign iPhone app binary ?

    - by CodeFlakes
    I'd like to send a binary to a client without the source code. How can here sign the app for distribution on it's own name without recompiling everything (since he does not have the source code) I'm not talking about adhoc distribution. I've tried to codesign -f with another distribution profile but itunes connect refuses it.

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  • Decimal point issue on cocoa app

    - by Manuel Rocha
    I there, I'm trying making my first cocoa app, but I'm having problems with float numbers because of the regional settings. If I write on the TextBox the float number 1.2 I only can get the number 1, but If I write on the same TextBox the same float number but this time with the ',' sign instead (1,2) I can get the right float value. How can I bypass the regional settings? Kind Regards, Manuel Rocha

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  • Jquery Count up Animation?

    - by Wes
    I have a a counter that needs to count up from $0 to $10,000 in x seconds (most likely 3 seconds). Just straight text, kind of like a millisecond countdown timer, but upwards and with a dollar sign. I'd rather not use a bulky plugin as this just needs to loop through 1-10,00 in x seconds and update every 100ms or so. I'm stuck at creating the loop that will update, where should I start?

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  • SQLCMD Syntax error when running script that runs fine in management studio

    - by Troy
    When I run the this select '$(''test'')' in SQL Management Studio 2008 it returns $('test') When I run sqlcmd -S SERVER -E -d DATABASE -q "select "$(''test'')" on the command line it returns Sqlcmd: Error: Syntax error at line 1 near command '''. If I remove the dollar sign it works. Is the "$" a special character? Is this a sqlcmd bug? How can I change the script to get the desired result.

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