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  • How do you raise a Java BigInteger to the power of a BigInteger without doing modular arithmetic?

    - by angstrom91
    I'm doing some large integer computing, and I need to raise a BigInteger to the power of another BigInteger. The .pow() method does what I want, but takes an int value as an argument. The .modPow method takes a BigInteger as an argument, but I do not want an answer congruent to the value I'm trying to compute. My BigInteger exponent is too large to be represented as an int, can someone suggest a way to work around this limitation?

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  • When is the onPreExecute called on an AsyncTask running parallely or concurrently?

    - by Debarshi Dutta
    I am using Android HoneyComb.I need to execute some tasks parallely and I am using AsyncTask's public final AsyncTask executeOnExecutor (Executor exec, Params... params) method.In each separate thread I am computing some values and I need to store then in an ArrayList.I must then sort all the values in the arrayList and then display it in the UI.Now my question is if one of the thread gets completed earlier than the other then will it immediately call the onPostExecute method or onPostExecute method will be called after all the background threads have been completed?MY program implementation depends on what occurs here.

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  • Jave JIT compiler compiles at compile time or runtime ?

    - by Tony
    From wiki: In computing, just-in-time compilation (JIT), also known as dynamic translation, is a technique for improving the runtime performance of a computer program. So I guess JVM has another compiler, not javac, that only compiles bytecode to machine code at runtime, while javac compiles sources to bytecode,is that right?

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  • Wrong root on image_tag

    - by Euwyn
    On my dev setup, the image_tag is mysteriously pointing to my public www server (i.e. computing the image path as http://www.domain.com/images/blah.jpg). Where is this option set?

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  • Windows Azure: Parallelization of the code

    - by veda
    I have some matrix multiplication operation. I want to parallelize the execution of those operations through multiple processors.. This can be done on high performance computing cluster using MPI (Message Passing Interface). Like wise, can I do some parallelization in the cloud using multiple worker roles. Is there any means for doing that.

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  • Getting up to speed on modern architecture

    - by Matt Thrower
    Hi, I don't have any formal qualifications in computer science, rather I taught myself classic ASP back in the days of the dotcom boom and managed to get myself a job and my career developed from there. I was a confident and, I think, pretty good programmer in ASP 3 but as others have observed one of the problems with classic ASP was that it did a very good job of hiding the nitty-gritty of http so you could become quite competent as a programmer on the basis of relatively poor understanding of the technology you were working with. When I changed on to .NET at first I treated it like classic ASP, developing stand-alone applications as individual websites simply because I didn't know any better at the time. I moved jobs at this point and spent the next several years working on a single site whose architecture relied heavily on custom objects: in other words I gained a lot of experience working with .NET as a middle-tier development tool using a quite old-fashioned approach to OO design along the lines of the classic "car" class example that's so often used to teach OO. Breaking down programs into blocks of functionality and basing your classes and methods around that. Although we worked under an Agile approach to manage the work the whole setup was classic client/server stuff. That suited me and I gradually got to grips with .NET and started using it far more in the manner that it should be, and I began to see the power inherent in the technology and precisely why it was so much better than good old ASP 3. In my latest job I have found myself suddenly dropped in at the deep end with two quite young, skilled and very cutting-edge programmers. They've built a site architecture which is modelling along a lot of stuff which is new to me and which, in truth I'm having a lot of trouble understanding. The application is built on a cloud computing model with multi-tenancy and the architecture is all loosely coupled using a lot of interfaces, factories and the like. They use nHibernate a lot too. Shortly after I joined, both these guys left and I'm now supposedly the senior developer on a system whose technology and architecture I don't really understand and I have no-one to ask questions of. Except you, the internet. Frankly I feel like I've been pitched in at the deep end and I'm sinking. I'm not sure if this is because I lack the educational background to understand this stuff, if I'm simply not mathematically minded enough for modern computing (my maths was never great - my approach to design is often to simply debug until it works, then refactor until it looks neat), or whether I've simply been presented with too much of too radical a nature at once. But the only way to find out which it is is to try and learn it. So can anyone suggest some good places to start? Good books, tutorials or blogs? I've found a lot of internet material simply presupposes a level of understanding that I just don't have. Your advice is much appreciated. Help a middle-aged, stuck in the mud developer get enthusastic again! Please!

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  • Is possible to generate constant value during compilation?

    - by AOI Karasu
    I would like my classes to be identified each type by an unique hash code. But I don't want these hashed to be generated every time a method, eg. int GetHashCode(), is invoked during runtime. I'd like to use already generated constants and I was hoping there is a way to make the compiler do some come computing and set these constants. Can it be done using templates? Could you give me some example, if it is possible.

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  • Pi/Infinite Numbers

    - by Ben Shelock
    I'm curious about infinite numbers in computing, in particular pi. For a computer to render a circle it would have to understand pi. But how can it if it is infinite? Am I looking too much into this? Would it just use a rounded value?

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  • Java JIT compiler compiles at compile time or runtime ?

    - by Tony
    From wiki: In computing, just-in-time compilation (JIT), also known as dynamic translation, is a technique for improving the runtime performance of a computer program. So I guess JVM has another compiler, not javac, that only compiles bytecode to machine code at runtime, while javac compiles sources to bytecode,is that right?

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  • take performance as the only criterion for a smal site, which framework should I choose on a shared

    - by john
    Dear friends, I'm trying to set up a small full functional website for a small community on a shared hosting. Scientific computing is quite heavy. Scalability is not important. The only criterion is performance. Which framework would you suggest among the following:(or more) from your list) 1)Ruby on Rails 2) Grails 3) asp.net 4) zend I'm really new to this area, only starting reading some books and googling different blogs...so your expertise is really appreciated! thanks!

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  • C++ Expression Templates

    - by yCalleecharan
    Hi, I currently use C for numerical computations. I've heard that using C++ Expression Templates is better for scientific computing. What are C++ Expression Templates in simple terms? Are there books around that discuss numerical methods/computations using C++ Expression Templates? In what way, C++ Expression Templates are better than using pure C? Thanks a lot

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  • Possible to distribute or parallel process a sequential program?

    - by damigu
    In C++, I've written a mathematical program (for diffusion limited aggregation) where each new point calculated is dependent on all of the preceding points. Is it possible to have such a program work in a parallel or distributed manner to increase computing speed? If so, what type of modifications to the code would I need to look into?

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  • What's the purpose of the rotate instructions (ROL, RCL on x86) ?

    - by lgratian
    I always wondered what's the purpose of the rotate instructions some CPUs have (ROL, RCL on x86, for example). What kind of software makes use of these instructions? I first thought they may be used for encryption/computing hash codes, but these libraries are written usually in C, which doesn't have operators that map to these instructions. Has anybody found an use for them? Why where they added to the instructions set?

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  • C++ variable alias - what's that exactly, and why is it better to turn if off?

    - by Poni
    I've read the essay Surviving the Release Version. Under the "Aliasing bugs" clause it says: You can get tighter code if you tell the compiler that it can assume no aliasing.... I've also read Aliasing (computing). What exactly is a variable alias? I understand it means using a pointer to a variable is an alias, but, how/why does it affect badly, or in other words - why telling the compiler that it can assume no aliasing would get me a "tighter code"

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  • Good resource for studying Database High Availability techniques

    - by Invincible
    Hello Can anybody suggest some good resource/book on Database high availability techniques? Moreover, High-availability of system software like Intrusion Prevention system or Web servers. I am considering high-availability is global term which covers clustring, cloud computing, replication, replica management, distributed synchronization for cluster. Thanks in advance!

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  • Is it faster to compute values in a query, call a Scalar Function (decimal(28,2) datatype) 4 times,

    - by Pulsehead
    I have a handful of queries I need to write in SQL Server 2005. Each Query will be calculating 4 unit cost values based on a handful of (up to 11) fields. Any time I want 1 of these 4 unit cost values, I'll want all 4. Which is quicker? Computing in the SQL Query ((a+b+c+d+e+f+g+h+i)/(j+k)), calling ComputeScalarUnitCost(datapoint.ID) 4 times, or joining to ComputeUnitCostTable(datapoint.ID) one time?

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  • SQL SERVER – SOS_SCHEDULER_YIELD – Wait Type – Day 8 of 28

    - by pinaldave
    This is a very interesting wait type and quite often seen as one of the top wait types. Let us discuss this today. From Book On-Line: Occurs when a task voluntarily yields the scheduler for other tasks to execute. During this wait the task is waiting for its quantum to be renewed. SOS_SCHEDULER_YIELD Explanation: SQL Server has multiple threads, and the basic working methodology for SQL Server is that SQL Server does not let any “runnable” thread to starve. Now let us assume SQL Server OS is very busy running threads on all the scheduler. There are always new threads coming up which are ready to run (in other words, runnable). Thread management of the SQL Server is decided by SQL Server and not the operating system. SQL Server runs on non-preemptive mode most of the time, meaning the threads are co-operative and can let other threads to run from time to time by yielding itself. When any thread yields itself for another thread, it creates this wait. If there are more threads, it clearly indicates that the CPU is under pressure. You can fun the following DMV to see how many runnable task counts there are in your system. SELECT scheduler_id, current_tasks_count, runnable_tasks_count, work_queue_count, pending_disk_io_count FROM sys.dm_os_schedulers WHERE scheduler_id < 255 GO If you notice a two-digit number in runnable_tasks_count continuously for long time (not once in a while), you will know that there is CPU pressure. The two-digit number is usually considered as a bad thing; you can read the description of the above DMV over here. Additionally, there are several other counters (%Processor Time and other processor related counters), through which you can refer to so you can validate CPU pressure along with the method explained above. Reducing SOS_SCHEDULER_YIELD wait: This is the trickiest part of this procedure. As discussed, this particular wait type relates to CPU pressure. Increasing more CPU is the solution in simple terms; however, it is not easy to implement this solution. There are other things that you can consider when this wait type is very high. Here is the query where you can find the most expensive query related to CPU from the cache Note: The query that used lots of resources but is not cached will not be caught here. SELECT SUBSTRING(qt.TEXT, (qs.statement_start_offset/2)+1, ((CASE qs.statement_end_offset WHEN -1 THEN DATALENGTH(qt.TEXT) ELSE qs.statement_end_offset END - qs.statement_start_offset)/2)+1), qs.execution_count, qs.total_logical_reads, qs.last_logical_reads, qs.total_logical_writes, qs.last_logical_writes, qs.total_worker_time, qs.last_worker_time, qs.total_elapsed_time/1000000 total_elapsed_time_in_S, qs.last_elapsed_time/1000000 last_elapsed_time_in_S, qs.last_execution_time, qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) qt CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC -- CPU time You can find the most expensive queries that are utilizing lots of CPU (from the cache) and you can tune them accordingly. Moreover, you can find the longest running query and attempt to tune them if there is any processor offending code. Additionally, pay attention to total_worker_time because if that is also consistently higher, then  the CPU under too much pressure. You can also check perfmon counters of compilations as they tend to use good amount of CPU. Index rebuild is also a CPU intensive process but we should consider that main cause for this query because that is indeed needed on high transactions OLTP system utilized to reduce fragmentations. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • value types in the vm

    - by john.rose
    value types in the vm p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} p.p2 {margin: 0.0px 0.0px 14.0px 0.0px; font: 14.0px Times} p.p3 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times} p.p4 {margin: 0.0px 0.0px 15.0px 0.0px; font: 14.0px Times} p.p5 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier} p.p6 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Courier; min-height: 17.0px} p.p7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p8 {margin: 0.0px 0.0px 0.0px 36.0px; text-indent: -36.0px; font: 14.0px Times; min-height: 18.0px} p.p9 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; min-height: 18.0px} p.p10 {margin: 0.0px 0.0px 12.0px 0.0px; font: 14.0px Times; color: #000000} li.li1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times} li.li7 {margin: 0.0px 0.0px 0.0px 0.0px; font: 14.0px Times; min-height: 18.0px} span.s1 {font: 14.0px Courier} span.s2 {color: #000000} span.s3 {font: 14.0px Courier; color: #000000} ol.ol1 {list-style-type: decimal} Or, enduring values for a changing world. Introduction A value type is a data type which, generally speaking, is designed for being passed by value in and out of methods, and stored by value in data structures. The only value types which the Java language directly supports are the eight primitive types. Java indirectly and approximately supports value types, if they are implemented in terms of classes. For example, both Integer and String may be viewed as value types, especially if their usage is restricted to avoid operations appropriate to Object. In this note, we propose a definition of value types in terms of a design pattern for Java classes, accompanied by a set of usage restrictions. We also sketch the relation of such value types to tuple types (which are a JVM-level notion), and point out JVM optimizations that can apply to value types. This note is a thought experiment to extend the JVM’s performance model in support of value types. The demonstration has two phases.  Initially the extension can simply use design patterns, within the current bytecode architecture, and in today’s Java language. But if the performance model is to be realized in practice, it will probably require new JVM bytecode features, changes to the Java language, or both.  We will look at a few possibilities for these new features. An Axiom of Value In the context of the JVM, a value type is a data type equipped with construction, assignment, and equality operations, and a set of typed components, such that, whenever two variables of the value type produce equal corresponding values for their components, the values of the two variables cannot be distinguished by any JVM operation. Here are some corollaries: A value type is immutable, since otherwise a copy could be constructed and the original could be modified in one of its components, allowing the copies to be distinguished. Changing the component of a value type requires construction of a new value. The equals and hashCode operations are strictly component-wise. If a value type is represented by a JVM reference, that reference cannot be successfully synchronized on, and cannot be usefully compared for reference equality. A value type can be viewed in terms of what it doesn’t do. We can say that a value type omits all value-unsafe operations, which could violate the constraints on value types.  These operations, which are ordinarily allowed for Java object types, are pointer equality comparison (the acmp instruction), synchronization (the monitor instructions), all the wait and notify methods of class Object, and non-trivial finalize methods. The clone method is also value-unsafe, although for value types it could be treated as the identity function. Finally, and most importantly, any side effect on an object (however visible) also counts as an value-unsafe operation. A value type may have methods, but such methods must not change the components of the value. It is reasonable and useful to define methods like toString, equals, and hashCode on value types, and also methods which are specifically valuable to users of the value type. Representations of Value Value types have two natural representations in the JVM, unboxed and boxed. An unboxed value consists of the components, as simple variables. For example, the complex number x=(1+2i), in rectangular coordinate form, may be represented in unboxed form by the following pair of variables: /*Complex x = Complex.valueOf(1.0, 2.0):*/ double x_re = 1.0, x_im = 2.0; These variables might be locals, parameters, or fields. Their association as components of a single value is not defined to the JVM. Here is a sample computation which computes the norm of the difference between two complex numbers: double distance(/*Complex x:*/ double x_re, double x_im,         /*Complex y:*/ double y_re, double y_im) {     /*Complex z = x.minus(y):*/     double z_re = x_re - y_re, z_im = x_im - y_im;     /*return z.abs():*/     return Math.sqrt(z_re*z_re + z_im*z_im); } A boxed representation groups component values under a single object reference. The reference is to a ‘wrapper class’ that carries the component values in its fields. (A primitive type can naturally be equated with a trivial value type with just one component of that type. In that view, the wrapper class Integer can serve as a boxed representation of value type int.) The unboxed representation of complex numbers is practical for many uses, but it fails to cover several major use cases: return values, array elements, and generic APIs. The two components of a complex number cannot be directly returned from a Java function, since Java does not support multiple return values. The same story applies to array elements: Java has no ’array of structs’ feature. (Double-length arrays are a possible workaround for complex numbers, but not for value types with heterogeneous components.) By generic APIs I mean both those which use generic types, like Arrays.asList and those which have special case support for primitive types, like String.valueOf and PrintStream.println. Those APIs do not support unboxed values, and offer some problems to boxed values. Any ’real’ JVM type should have a story for returns, arrays, and API interoperability. The basic problem here is that value types fall between primitive types and object types. Value types are clearly more complex than primitive types, and object types are slightly too complicated. Objects are a little bit dangerous to use as value carriers, since object references can be compared for pointer equality, and can be synchronized on. Also, as many Java programmers have observed, there is often a performance cost to using wrapper objects, even on modern JVMs. Even so, wrapper classes are a good starting point for talking about value types. If there were a set of structural rules and restrictions which would prevent value-unsafe operations on value types, wrapper classes would provide a good notation for defining value types. This note attempts to define such rules and restrictions. Let’s Start Coding Now it is time to look at some real code. Here is a definition, written in Java, of a complex number value type. @ValueSafe public final class Complex implements java.io.Serializable {     // immutable component structure:     public final double re, im;     private Complex(double re, double im) {         this.re = re; this.im = im;     }     // interoperability methods:     public String toString() { return "Complex("+re+","+im+")"; }     public List<Double> asList() { return Arrays.asList(re, im); }     public boolean equals(Complex c) {         return re == c.re && im == c.im;     }     public boolean equals(@ValueSafe Object x) {         return x instanceof Complex && equals((Complex) x);     }     public int hashCode() {         return 31*Double.valueOf(re).hashCode()                 + Double.valueOf(im).hashCode();     }     // factory methods:     public static Complex valueOf(double re, double im) {         return new Complex(re, im);     }     public Complex changeRe(double re2) { return valueOf(re2, im); }     public Complex changeIm(double im2) { return valueOf(re, im2); }     public static Complex cast(@ValueSafe Object x) {         return x == null ? ZERO : (Complex) x;     }     // utility methods and constants:     public Complex plus(Complex c)  { return new Complex(re+c.re, im+c.im); }     public Complex minus(Complex c) { return new Complex(re-c.re, im-c.im); }     public double abs() { return Math.sqrt(re*re + im*im); }     public static final Complex PI = valueOf(Math.PI, 0.0);     public static final Complex ZERO = valueOf(0.0, 0.0); } This is not a minimal definition, because it includes some utility methods and other optional parts.  The essential elements are as follows: The class is marked as a value type with an annotation. The class is final, because it does not make sense to create subclasses of value types. The fields of the class are all non-private and final.  (I.e., the type is immutable and structurally transparent.) From the supertype Object, all public non-final methods are overridden. The constructor is private. Beyond these bare essentials, we can observe the following features in this example, which are likely to be typical of all value types: One or more factory methods are responsible for value creation, including a component-wise valueOf method. There are utility methods for complex arithmetic and instance creation, such as plus and changeIm. There are static utility constants, such as PI. The type is serializable, using the default mechanisms. There are methods for converting to and from dynamically typed references, such as asList and cast. The Rules In order to use value types properly, the programmer must avoid value-unsafe operations.  A helpful Java compiler should issue errors (or at least warnings) for code which provably applies value-unsafe operations, and should issue warnings for code which might be correct but does not provably avoid value-unsafe operations.  No such compilers exist today, but to simplify our account here, we will pretend that they do exist. A value-safe type is any class, interface, or type parameter marked with the @ValueSafe annotation, or any subtype of a value-safe type.  If a value-safe class is marked final, it is in fact a value type.  All other value-safe classes must be abstract.  The non-static fields of a value class must be non-public and final, and all its constructors must be private. Under the above rules, a standard interface could be helpful to define value types like Complex.  Here is an example: @ValueSafe public interface ValueType extends java.io.Serializable {     // All methods listed here must get redefined.     // Definitions must be value-safe, which means     // they may depend on component values only.     List<? extends Object> asList();     int hashCode();     boolean equals(@ValueSafe Object c);     String toString(); } //@ValueSafe inherited from supertype: public final class Complex implements ValueType { … The main advantage of such a conventional interface is that (unlike an annotation) it is reified in the runtime type system.  It could appear as an element type or parameter bound, for facilities which are designed to work on value types only.  More broadly, it might assist the JVM to perform dynamic enforcement of the rules for value types. Besides types, the annotation @ValueSafe can mark fields, parameters, local variables, and methods.  (This is redundant when the type is also value-safe, but may be useful when the type is Object or another supertype of a value type.)  Working forward from these annotations, an expression E is defined as value-safe if it satisfies one or more of the following: The type of E is a value-safe type. E names a field, parameter, or local variable whose declaration is marked @ValueSafe. E is a call to a method whose declaration is marked @ValueSafe. E is an assignment to a value-safe variable, field reference, or array reference. E is a cast to a value-safe type from a value-safe expression. E is a conditional expression E0 ? E1 : E2, and both E1 and E2 are value-safe. Assignments to value-safe expressions and initializations of value-safe names must take their values from value-safe expressions. A value-safe expression may not be the subject of a value-unsafe operation.  In particular, it cannot be synchronized on, nor can it be compared with the “==” operator, not even with a null or with another value-safe type. In a program where all of these rules are followed, no value-type value will be subject to a value-unsafe operation.  Thus, the prime axiom of value types will be satisfied, that no two value type will be distinguishable as long as their component values are equal. More Code To illustrate these rules, here are some usage examples for Complex: Complex pi = Complex.valueOf(Math.PI, 0); Complex zero = pi.changeRe(0);  //zero = pi; zero.re = 0; ValueType vtype = pi; @SuppressWarnings("value-unsafe")   Object obj = pi; @ValueSafe Object obj2 = pi; obj2 = new Object();  // ok List<Complex> clist = new ArrayList<Complex>(); clist.add(pi);  // (ok assuming List.add param is @ValueSafe) List<ValueType> vlist = new ArrayList<ValueType>(); vlist.add(pi);  // (ok) List<Object> olist = new ArrayList<Object>(); olist.add(pi);  // warning: "value-unsafe" boolean z = pi.equals(zero); boolean z1 = (pi == zero);  // error: reference comparison on value type boolean z2 = (pi == null);  // error: reference comparison on value type boolean z3 = (pi == obj2);  // error: reference comparison on value type synchronized (pi) { }  // error: synch of value, unpredictable result synchronized (obj2) { }  // unpredictable result Complex qq = pi; qq = null;  // possible NPE; warning: “null-unsafe" qq = (Complex) obj;  // warning: “null-unsafe" qq = Complex.cast(obj);  // OK @SuppressWarnings("null-unsafe")   Complex empty = null;  // possible NPE qq = empty;  // possible NPE (null pollution) The Payoffs It follows from this that either the JVM or the java compiler can replace boxed value-type values with unboxed ones, without affecting normal computations.  Fields and variables of value types can be split into their unboxed components.  Non-static methods on value types can be transformed into static methods which take the components as value parameters. Some common questions arise around this point in any discussion of value types. Why burden the programmer with all these extra rules?  Why not detect programs automagically and perform unboxing transparently?  The answer is that it is easy to break the rules accidently unless they are agreed to by the programmer and enforced.  Automatic unboxing optimizations are tantalizing but (so far) unreachable ideal.  In the current state of the art, it is possible exhibit benchmarks in which automatic unboxing provides the desired effects, but it is not possible to provide a JVM with a performance model that assures the programmer when unboxing will occur.  This is why I’m writing this note, to enlist help from, and provide assurances to, the programmer.  Basically, I’m shooting for a good set of user-supplied “pragmas” to frame the desired optimization. Again, the important thing is that the unboxing must be done reliably, or else programmers will have no reason to work with the extra complexity of the value-safety rules.  There must be a reasonably stable performance model, wherein using a value type has approximately the same performance characteristics as writing the unboxed components as separate Java variables. There are some rough corners to the present scheme.  Since Java fields and array elements are initialized to null, value-type computations which incorporate uninitialized variables can produce null pointer exceptions.  One workaround for this is to require such variables to be null-tested, and the result replaced with a suitable all-zero value of the value type.  That is what the “cast” method does above. Generically typed APIs like List<T> will continue to manipulate boxed values always, at least until we figure out how to do reification of generic type instances.  Use of such APIs will elicit warnings until their type parameters (and/or relevant members) are annotated or typed as value-safe.  Retrofitting List<T> is likely to expose flaws in the present scheme, which we will need to engineer around.  Here are a couple of first approaches: public interface java.util.List<@ValueSafe T> extends Collection<T> { … public interface java.util.List<T extends Object|ValueType> extends Collection<T> { … (The second approach would require disjunctive types, in which value-safety is “contagious” from the constituent types.) With more transformations, the return value types of methods can also be unboxed.  This may require significant bytecode-level transformations, and would work best in the presence of a bytecode representation for multiple value groups, which I have proposed elsewhere under the title “Tuples in the VM”. But for starters, the JVM can apply this transformation under the covers, to internally compiled methods.  This would give a way to express multiple return values and structured return values, which is a significant pain-point for Java programmers, especially those who work with low-level structure types favored by modern vector and graphics processors.  The lack of multiple return values has a strong distorting effect on many Java APIs. Even if the JVM fails to unbox a value, there is still potential benefit to the value type.  Clustered computing systems something have copy operations (serialization or something similar) which apply implicitly to command operands.  When copying JVM objects, it is extremely helpful to know when an object’s identity is important or not.  If an object reference is a copied operand, the system may have to create a proxy handle which points back to the original object, so that side effects are visible.  Proxies must be managed carefully, and this can be expensive.  On the other hand, value types are exactly those types which a JVM can “copy and forget” with no downside. Array types are crucial to bulk data interfaces.  (As data sizes and rates increase, bulk data becomes more important than scalar data, so arrays are definitely accompanying us into the future of computing.)  Value types are very helpful for adding structure to bulk data, so a successful value type mechanism will make it easier for us to express richer forms of bulk data. Unboxing arrays (i.e., arrays containing unboxed values) will provide better cache and memory density, and more direct data movement within clustered or heterogeneous computing systems.  They require the deepest transformations, relative to today’s JVM.  There is an impedance mismatch between value-type arrays and Java’s covariant array typing, so compromises will need to be struck with existing Java semantics.  It is probably worth the effort, since arrays of unboxed value types are inherently more memory-efficient than standard Java arrays, which rely on dependent pointer chains. It may be sufficient to extend the “value-safe” concept to array declarations, and allow low-level transformations to change value-safe array declarations from the standard boxed form into an unboxed tuple-based form.  Such value-safe arrays would not be convertible to Object[] arrays.  Certain connection points, such as Arrays.copyOf and System.arraycopy might need additional input/output combinations, to allow smooth conversion between arrays with boxed and unboxed elements. Alternatively, the correct solution may have to wait until we have enough reification of generic types, and enough operator overloading, to enable an overhaul of Java arrays. Implicit Method Definitions The example of class Complex above may be unattractively complex.  I believe most or all of the elements of the example class are required by the logic of value types. If this is true, a programmer who writes a value type will have to write lots of error-prone boilerplate code.  On the other hand, I think nearly all of the code (except for the domain-specific parts like plus and minus) can be implicitly generated. Java has a rule for implicitly defining a class’s constructor, if no it defines no constructors explicitly.  Likewise, there are rules for providing default access modifiers for interface members.  Because of the highly regular structure of value types, it might be reasonable to perform similar implicit transformations on value types.  Here’s an example of a “highly implicit” definition of a complex number type: public class Complex implements ValueType {  // implicitly final     public double re, im;  // implicitly public final     //implicit methods are defined elementwise from te fields:     //  toString, asList, equals(2), hashCode, valueOf, cast     //optionally, explicit methods (plus, abs, etc.) would go here } In other words, with the right defaults, a simple value type definition can be a one-liner.  The observant reader will have noticed the similarities (and suitable differences) between the explicit methods above and the corresponding methods for List<T>. Another way to abbreviate such a class would be to make an annotation the primary trigger of the functionality, and to add the interface(s) implicitly: public @ValueType class Complex { … // implicitly final, implements ValueType (But to me it seems better to communicate the “magic” via an interface, even if it is rooted in an annotation.) Implicitly Defined Value Types So far we have been working with nominal value types, which is to say that the sequence of typed components is associated with a name and additional methods that convey the intention of the programmer.  A simple ordered pair of floating point numbers can be variously interpreted as (to name a few possibilities) a rectangular or polar complex number or Cartesian point.  The name and the methods convey the intended meaning. But what if we need a truly simple ordered pair of floating point numbers, without any further conceptual baggage?  Perhaps we are writing a method (like “divideAndRemainder”) which naturally returns a pair of numbers instead of a single number.  Wrapping the pair of numbers in a nominal type (like “QuotientAndRemainder”) makes as little sense as wrapping a single return value in a nominal type (like “Quotient”).  What we need here are structural value types commonly known as tuples. For the present discussion, let us assign a conventional, JVM-friendly name to tuples, roughly as follows: public class java.lang.tuple.$DD extends java.lang.tuple.Tuple {      double $1, $2; } Here the component names are fixed and all the required methods are defined implicitly.  The supertype is an abstract class which has suitable shared declarations.  The name itself mentions a JVM-style method parameter descriptor, which may be “cracked” to determine the number and types of the component fields. The odd thing about such a tuple type (and structural types in general) is it must be instantiated lazily, in response to linkage requests from one or more classes that need it.  The JVM and/or its class loaders must be prepared to spin a tuple type on demand, given a simple name reference, $xyz, where the xyz is cracked into a series of component types.  (Specifics of naming and name mangling need some tasteful engineering.) Tuples also seem to demand, even more than nominal types, some support from the language.  (This is probably because notations for non-nominal types work best as combinations of punctuation and type names, rather than named constructors like Function3 or Tuple2.)  At a minimum, languages with tuples usually (I think) have some sort of simple bracket notation for creating tuples, and a corresponding pattern-matching syntax (or “destructuring bind”) for taking tuples apart, at least when they are parameter lists.  Designing such a syntax is no simple thing, because it ought to play well with nominal value types, and also with pre-existing Java features, such as method parameter lists, implicit conversions, generic types, and reflection.  That is a task for another day. Other Use Cases Besides complex numbers and simple tuples there are many use cases for value types.  Many tuple-like types have natural value-type representations. These include rational numbers, point locations and pixel colors, and various kinds of dates and addresses. Other types have a variable-length ‘tail’ of internal values. The most common example of this is String, which is (mathematically) a sequence of UTF-16 character values. Similarly, bit vectors, multiple-precision numbers, and polynomials are composed of sequences of values. Such types include, in their representation, a reference to a variable-sized data structure (often an array) which (somehow) represents the sequence of values. The value type may also include ’header’ information. Variable-sized values often have a length distribution which favors short lengths. In that case, the design of the value type can make the first few values in the sequence be direct ’header’ fields of the value type. In the common case where the header is enough to represent the whole value, the tail can be a shared null value, or even just a null reference. Note that the tail need not be an immutable object, as long as the header type encapsulates it well enough. This is the case with String, where the tail is a mutable (but never mutated) character array. Field types and their order must be a globally visible part of the API.  The structure of the value type must be transparent enough to have a globally consistent unboxed representation, so that all callers and callees agree about the type and order of components  that appear as parameters, return types, and array elements.  This is a trade-off between efficiency and encapsulation, which is forced on us when we remove an indirection enjoyed by boxed representations.  A JVM-only transformation would not care about such visibility, but a bytecode transformation would need to take care that (say) the components of complex numbers would not get swapped after a redefinition of Complex and a partial recompile.  Perhaps constant pool references to value types need to declare the field order as assumed by each API user. This brings up the delicate status of private fields in a value type.  It must always be possible to load, store, and copy value types as coordinated groups, and the JVM performs those movements by moving individual scalar values between locals and stack.  If a component field is not public, what is to prevent hostile code from plucking it out of the tuple using a rogue aload or astore instruction?  Nothing but the verifier, so we may need to give it more smarts, so that it treats value types as inseparable groups of stack slots or locals (something like long or double). My initial thought was to make the fields always public, which would make the security problem moot.  But public is not always the right answer; consider the case of String, where the underlying mutable character array must be encapsulated to prevent security holes.  I believe we can win back both sides of the tradeoff, by training the verifier never to split up the components in an unboxed value.  Just as the verifier encapsulates the two halves of a 64-bit primitive, it can encapsulate the the header and body of an unboxed String, so that no code other than that of class String itself can take apart the values. Similar to String, we could build an efficient multi-precision decimal type along these lines: public final class DecimalValue extends ValueType {     protected final long header;     protected private final BigInteger digits;     public DecimalValue valueOf(int value, int scale) {         assert(scale >= 0);         return new DecimalValue(((long)value << 32) + scale, null);     }     public DecimalValue valueOf(long value, int scale) {         if (value == (int) value)             return valueOf((int)value, scale);         return new DecimalValue(-scale, new BigInteger(value));     } } Values of this type would be passed between methods as two machine words. Small values (those with a significand which fits into 32 bits) would be represented without any heap data at all, unless the DecimalValue itself were boxed. (Note the tension between encapsulation and unboxing in this case.  It would be better if the header and digits fields were private, but depending on where the unboxing information must “leak”, it is probably safer to make a public revelation of the internal structure.) Note that, although an array of Complex can be faked with a double-length array of double, there is no easy way to fake an array of unboxed DecimalValues.  (Either an array of boxed values or a transposed pair of homogeneous arrays would be reasonable fallbacks, in a current JVM.)  Getting the full benefit of unboxing and arrays will require some new JVM magic. Although the JVM emphasizes portability, system dependent code will benefit from using machine-level types larger than 64 bits.  For example, the back end of a linear algebra package might benefit from value types like Float4 which map to stock vector types.  This is probably only worthwhile if the unboxing arrays can be packed with such values. More Daydreams A more finely-divided design for dynamic enforcement of value safety could feature separate marker interfaces for each invariant.  An empty marker interface Unsynchronizable could cause suitable exceptions for monitor instructions on objects in marked classes.  More radically, a Interchangeable marker interface could cause JVM primitives that are sensitive to object identity to raise exceptions; the strangest result would be that the acmp instruction would have to be specified as raising an exception. @ValueSafe public interface ValueType extends java.io.Serializable,         Unsynchronizable, Interchangeable { … public class Complex implements ValueType {     // inherits Serializable, Unsynchronizable, Interchangeable, @ValueSafe     … It seems possible that Integer and the other wrapper types could be retro-fitted as value-safe types.  This is a major change, since wrapper objects would be unsynchronizable and their references interchangeable.  It is likely that code which violates value-safety for wrapper types exists but is uncommon.  It is less plausible to retro-fit String, since the prominent operation String.intern is often used with value-unsafe code. We should also reconsider the distinction between boxed and unboxed values in code.  The design presented above obscures that distinction.  As another thought experiment, we could imagine making a first class distinction in the type system between boxed and unboxed representations.  Since only primitive types are named with a lower-case initial letter, we could define that the capitalized version of a value type name always refers to the boxed representation, while the initial lower-case variant always refers to boxed.  For example: complex pi = complex.valueOf(Math.PI, 0); Complex boxPi = pi;  // convert to boxed myList.add(boxPi); complex z = myList.get(0);  // unbox Such a convention could perhaps absorb the current difference between int and Integer, double and Double. It might also allow the programmer to express a helpful distinction among array types. As said above, array types are crucial to bulk data interfaces, but are limited in the JVM.  Extending arrays beyond the present limitations is worth thinking about; for example, the Maxine JVM implementation has a hybrid object/array type.  Something like this which can also accommodate value type components seems worthwhile.  On the other hand, does it make sense for value types to contain short arrays?  And why should random-access arrays be the end of our design process, when bulk data is often sequentially accessed, and it might make sense to have heterogeneous streams of data as the natural “jumbo” data structure.  These considerations must wait for another day and another note. More Work It seems to me that a good sequence for introducing such value types would be as follows: Add the value-safety restrictions to an experimental version of javac. Code some sample applications with value types, including Complex and DecimalValue. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. A staggered roll-out like this would decouple language changes from bytecode changes, which is always a convenient thing. A similar investigation should be applied (concurrently) to array types.  In this case, it seems to me that the starting point is in the JVM: Add an experimental unboxing array data structure to a production JVM, perhaps along the lines of Maxine hybrids.  No bytecode or language support is required at first; everything can be done with encapsulated unsafe operations and/or method handles. Create an experimental JVM which internally unboxes value types but does not require new bytecodes to do so.  Ensure the feasibility of the performance model for the sample applications. Add tuple-like bytecodes (with or without generic type reification) to a major revision of the JVM, and teach the Java compiler to switch in the new bytecodes without code changes. That’s enough musing me for now.  Back to work!

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  • Is this simple XOR encrypted communication absolutely secure?

    - by user3123061
    Say Alice have 4GB USB flash memory and Peter also have 4GB USB flash memory. They once meet and save on both of memories two files named alice_to_peter.key (2GB) and peter_to_alice.key (2GB) which is randomly generated bits. Then they never meet again and communicate electronicaly. Alice also maintains variable called alice_pointer and Peter maintains variable called peter_pointer which is both initially set to zero. Then when Alice needs to send message to Peter they do: encrypted_message_to_peter[n] = message_to_peter[n] XOR alice_to_peter.key[alice_pointer + n] Where n i n-th byte of message. Then alice_pointer is attached at begining of the encrypted message and (alice_pointer + encrypted message) is sent to Peter and then alice_pointer is incremented by length of message (and for maximum security can be used part of key erased) Peter receives encrypted_message, reads alice_pointer stored at beginning of message and do this: message_to_peter[n] = encrypted_message_to_peter[n] XOR alice_to_peter.key[alice_pointer + n] And for maximum security after reading of message also erases used part of key. - EDIT: In fact this step with this simple algorithm (without integrity check and authentication) decreases security, see Paulo Ebermann post below. When Peter needs to send message to Alice they do analogical steps with peter_to_alice.key and with peter_pointer. With this trivial schema they can send for next 50 years each day 2GB / (50 * 365) = cca 115kB of encrypted data in both directions. If they need more data to send, they simple use larger memory for keys for example with today 2TB harddiscs (1TB keys) is possible to exchange next 50years 60MB/day ! (thats practicaly lots of data for example with using compression its more than hour of high quality voice communication) It Seems to me there is no way for attacker to read encrypted message without keys even if they have infinitely fast computer. because even with infinitely fast computer with brute force they get ever possible message that can fit to length of message, but this is astronomical amount of messages and attacker dont know which of them is actual message. I am right? Is this communication schema really absolutely secure? And if its secure, has this communication method its own name? (I mean XOR encryption is well-known, but whats name of this concrete practical application with use large memories at both communication sides for keys? I am humbly expecting that this application has been invented someone before me :-) ) Note: If its absolutely secure then its amazing because with today low cost large memories it is practicaly much cheeper way of secure communication than expensive quantum cryptography and with equivalent security! EDIT: I think it will be more and more practical in future with lower a lower cost of memories. It can solve secure communication forever. Today you have no certainty if someone succesfuly atack to existing ciphers one year later and make its often expensive implementations unsecure. In many cases before comunication exist step where communicating sides meets personaly, thats time to generate large keys. I think its perfect for military communication for example for communication with submarines which can have installed harddrive with large keys and military central can have harddrive for each submarine they have. It can be also practical in everyday life for example for control your bank account because when you create your account you meet with bank etc.

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  • Feynman's inbox

    - by user12607414
    Here is Richard Feynman writing on the ease of criticizing theories, and the difficulty of forming them: The problem is not just to say something might be wrong, but to replace it by something — and that is not so easy. As soon as any really definite idea is substituted it becomes almost immediately apparent that it does not work. The second difficulty is that there is an infinite number of possibilities of these simple types. It is something like this. You are sitting working very hard, you have worked for a long time trying to open a safe. Then some Joe comes along who knows nothing about what you are doing, except that you are trying to open the safe. He says ‘Why don’t you try the combination 10:20:30?’ Because you are busy, you have tried a lot of things, maybe you have already tried 10:20:30. Maybe you know already that the middle number is 32 not 20. Maybe you know as a matter of fact that it is a five digit combination… So please do not send me any letters trying to tell me how the thing is going to work. I read them — I always read them to make sure that I have not already thought of what is suggested — but it takes too long to answer them, because they are usually in the class ‘try 10:20:30’. (“Seeking New Laws”, page 161 in The Character of Physical Law.) As a sometime designer (and longtime critic) of widely used computer systems, I have seen similar difficulties appear when anyone undertakes to publicly design a piece of software that may be used by many thousands of customers. (I have been on both sides of the fence, of course.) The design possibilities are endless, but the deep design problems are usually hidden beneath a mass of superfluous detail. The sheer numbers can be daunting. Even if only one customer out of a thousand feels a need to express a passionately held idea, it can take a long time to read all the mail. And it is a fact of life that many of those strong suggestions are only weakly supported by reason or evidence. Opinions are plentiful, but substantive research is time-consuming, and hence rare. A related phenomenon commonly seen with software is bike-shedding, where interlocutors focus on surface details like naming and syntax… or (come to think of it) like lock combinations. On the other hand, software is easier than quantum physics, and the population of people able to make substantial suggestions about software systems is several orders of magnitude bigger than Feynman’s circle of colleagues. My own work would be poorer without contributions — sometimes unsolicited, sometimes passionately urged on me — from the open source community. If a Nobel prize winner thought it was worthwhile to read his mail on the faint chance of learning a good idea, I am certainly not going to throw mine away. (In case anyone is still reading this, and is wondering what provoked a meditation on the quality of one’s inbox contents, I’ll simply point out that the volume has been very high, for many months, on the Lambda-Dev mailing list, where the next version of the Java language is being discussed. Bravo to those of my colleagues who are surfing that wave.) I started this note thinking there was an odd parallel between the life of the physicist and that of a software designer. On second thought, I’ll bet that is the story for anybody who works in public on something requiring special training. (And that would be pretty much anything worth doing.) In any case, Feynman saw it clearly and said it well.

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  • High Resolution Timeouts

    - by user12607257
    The default resolution of application timers and timeouts is now 1 msec in Solaris 11.1, down from 10 msec in previous releases. This improves out-of-the-box performance of polling and event based applications, such as ticker applications, and even the Oracle rdbms log writer. More on that in a moment. As a simple example, the poll() system call takes a timeout argument in units of msec: System Calls poll(2) NAME poll - input/output multiplexing SYNOPSIS int poll(struct pollfd fds[], nfds_t nfds, int timeout); In Solaris 11, a call to poll(NULL,0,1) returns in 10 msec, because even though a 1 msec interval is requested, the implementation rounds to the system clock resolution of 10 msec. In Solaris 11.1, this call returns in 1 msec. In specification lawyer terms, the resolution of CLOCK_REALTIME, introduced by POSIX.1b real time extensions, is now 1 msec. The function clock_getres(CLOCK_REALTIME,&res) returns 1 msec, and any library calls whose man page explicitly mention CLOCK_REALTIME, such as nanosleep(), are subject to the new resolution. Additionally, many legacy functions that pre-date POSIX.1b and do not explicitly mention a clock domain, such as poll(), are subject to the new resolution. Here is a fairly comprehensive list: nanosleep pthread_mutex_timedlock pthread_mutex_reltimedlock_np pthread_rwlock_timedrdlock pthread_rwlock_reltimedrdlock_np pthread_rwlock_timedwrlock pthread_rwlock_reltimedwrlock_np mq_timedreceive mq_reltimedreceive_np mq_timedsend mq_reltimedsend_np sem_timedwait sem_reltimedwait_np poll select pselect _lwp_cond_timedwait _lwp_cond_reltimedwait semtimedop sigtimedwait aiowait aio_waitn aio_suspend port_get port_getn cond_timedwait cond_reltimedwait setitimer (ITIMER_REAL) misc rpc calls, misc ldap calls This change in resolution was made feasible because we made the implementation of timeouts more efficient a few years back when we re-architected the callout subsystem of Solaris. Previously, timeouts were tested and expired by the kernel's clock thread which ran 100 times per second, yielding a resolution of 10 msec. This did not scale, as timeouts could be posted by every CPU, but were expired by only a single thread. The resolution could be changed by setting hires_tick=1 in /etc/system, but this caused the clock thread to run at 1000 Hz, which made the potential scalability problem worse. Given enough CPUs posting enough timeouts, the clock thread could be a performance bottleneck. We fixed that by re-implementing the timeout as a per-CPU timer interrupt (using the cyclic subsystem, for those familiar with Solaris internals). This decoupled the clock thread frequency from timeout resolution, and allowed us to improve default timeout resolution without adding CPU overhead in the clock thread. Here are some exceptions for which the default resolution is still 10 msec. The thread scheduler's time quantum is 10 msec by default, because preemption is driven by the clock thread (plus helper threads for scalability). See for example dispadmin, priocntl, fx_dptbl, rt_dptbl, and ts_dptbl. This may be changed using hires_tick. The resolution of the clock_t data type, primarily used in DDI functions, is 10 msec. It may be changed using hires_tick. These functions are only used by developers writing kernel modules. A few functions that pre-date POSIX CLOCK_REALTIME mention _SC_CLK_TCK, CLK_TCK, "system clock", or no clock domain. These functions are still driven by the clock thread, and their resolution is 10 msec. They include alarm, pcsample, times, clock, and setitimer for ITIMER_VIRTUAL and ITIMER_PROF. Their resolution may be changed using hires_tick. Now back to the database. How does this help the Oracle log writer? Foreground processes post a redo record to the log writer, which releases them after the redo has committed. When a large number of foregrounds are waiting, the release step can slow down the log writer, so under heavy load, the foregrounds switch to a mode where they poll for completion. This scales better because every foreground can poll independently, but at the cost of waiting the minimum polling interval. That was 10 msec, but is now 1 msec in Solaris 11.1, so the foregrounds process transactions faster under load. Pretty cool.

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  • Designer serialization persistence problem in .NET, Windows Forms

    - by Jules
    ETA: I have a similar, smaller, problem here which, I suspect, is related to this problem. I have a class which has a readonly property that holds a collection of components (* not quite, see below). At design time, it's possible to select from the components on the design surface to add to the collection. (Think imagelist, but instead of selecting one, you can select as many as you want.) As a test, I inherit from button and attach my class to it as a property. The persistence problem occurs when I add a component,to the collection, from the design surface after I have added my button to the form. The best way to demonstrate this is to show you the designer generated code: Private Sub InitializeComponent() Dim Provider1 As WindowsApplication1.Provider = New WindowsApplication1.Provider Me.MyComponent2 = New WindowsApplication1.MyComponent Me.MyComponent1 = New WindowsApplication1.MyComponent Me.MyButton1 = New WindowsApplication1.MyButton Me.MyComponent3 = New WindowsApplication1.MyComponent Me.SuspendLayout() ' 'MyButton1 ' Me.MyButton1.ProviderCollection.Add(Me.MyButton1.InternalProvider) Me.MyButton1.ProviderCollection.Add(Me.MyComponent1.Provider) Me.MyButton1.ProviderCollection.Add(Me.MyComponent2.Provider) Me.MyButton1.ProviderCollection.Add(Provider1) //Wrong should be Me.MyComponent3.Provider ' 'Form1 ' Me.Controls.Add(Me.MyButton1) End Sub Friend WithEvents MyComponent1 As WindowsApplication1.MyComponent Friend WithEvents MyComponent2 As WindowsApplication1.MyComponent Friend WithEvents MyButton1 As WindowsApplication1.MyButton Friend WithEvents MyComponent3 As WindowsApplication1.MyComponent End Class As you can see from the code, the collection is not actually a collection of the components, but a collection of a property, 'Provider', from the components. It looks like the problem is occurring because MyComponent3 is created after MyButton. However, in my opinion, this should not make any difference - by the time the serializer comes to add the provider property of MyComponent3, it's already created. Note: You may wonder, why I'm not using AddRange to persist the collection. The reason for this is that if I do, the behaviour changes and none of the items will persist correctly. The designer will create local fields - like Provider1 - for each item in the collection. However if I add another collection to the class which holds the actual MyComponents and persist this, then, somehow, the AddRange method persists correctly in ProviderCollection! There seems to be some kind of quantum double slit experiment going down in code dom. How can I solve this problem?

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