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  • Book with C programs that have real programming examples.

    - by Siamore
    This is my first question on Stack Overflow, I would like to know about any c programming books that have real programs to introduce real problems as opposed to standard books with examples aimed to teach the language it should be sort of like a challenge with solutions so that concepts like recursion can be used i know that i should find solutions to existing problems to learn the language but this is my first attempt and i find it hard to understand some simple problems so i was hoping for a book with solutions.

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  • Java or C for image processing

    - by its-me
    I am looking in to learning a programming language (take a course) for image analysis and processing. Possibly Bioinformatics too. Which language should I go for? C or Java? Other languages are not an option for me. Also please explain why either of the languages is a better option for my application.

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  • SOA, Empowerment and Continuous Improvement

    - by Tanu Sood
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Rick Beers is Senior Director of Product Management for Oracle Fusion Middleware. Prior to joining Oracle, Rick held a variety of executive operational positions at Corning, Inc. and Bausch & Lomb. With a professional background that includes senior management positions in manufacturing, supply chain and information technology, Rick brings a unique set of experiences to cover the impact that technology can have on business models, processes and organizations. Rick will be hosting the IT Leader Editorial on a regular basis. I met my twin at Open World. We share backgrounds, experiences and even names. I hosted an invitation-only AppAdvantage Leadership Forum with an overcapacity 85 participants: 55 customers, 15 from the Oracle AppAdvantage team and 15 Partners. It was a lively, open and positive discussion of pace layered architectures and Oracle’s AppAdvantage approach to a unified view of Applications and Middleware. Rick Hassman from Pella was one of the customer panelists and during the pre event prep, Rick and I shared backgrounds and found that we had both been plant managers and led ERP deployments prior to leading IT itself. During the panel conversation I explored this with him, discussing the unique perspectives that this provides to CIO’s. He then hit on a point that I wasn’t able to fully appreciate until a week later. First though, some background. The week after the Forum, one of the participants emailed me with the following thoughts: “I am 150% behind this concept……but we are struggling with the concept of web services and the potential use of the Oracle Service Bus technology let alone moving into using the full SOA/BPM/BAM software to extend our JD Edwards application to both integrate and support business processes”. After thinking a bit I responded this way: While I certainly appreciate the degree of change and effort involved, perhaps I could offer the following: One of the underlying principles behind Oracle AppAdvantage is that more often than not, the choice between changing a business process and invasively customizing ERP represents a Hobson's Choice: neither is acceptable. In this case the third option, moving the process out of ERP, is the only acceptable one. Providing this choice typically requires end to end, real time interoperability across applications and/or services. This real time interoperability, to be sustainable over time requires a service oriented architecture. There's just no way around this. SOA adaptation is admittedly tough at the beginning. New skills, new technology and new headaches. But, like any radically new technology, it has a learning curve that drives cost down rather dramatically over time. Tough choices to be sure, but not entirely different than we face with every major technology cycle. Good points of course, but I felt that something was missing. The points were convincing, perhaps even a bit insightful, but they didn’t get at the heart of what Oracle AppAdvantage is focused upon: how the optimization of technology, applications, processes and relationships can change the very way that organizations operate. And then I thought back to the panel discussion with Rick Hassman at Oracle OpenWorld. Rick stressed that Continuous Improvement is a fundamental business strategy at Pella. I remember Continuous Improvement well as I suspect does everyone who was in American manufacturing during the 80’s. Pioneered by W. Edwards Deming in Japan (and still known alternatively as Kaizen), Continuous Improvement sets in place the business culture that we must not become complacent with success and resistant to the ongoing need for change. Many believe that this single handedly drove the renaissance in American manufacturing through the last two decades, which had become complacent during the 70’s and early 80’s. But what exactly does this have to do with SOA? It was Rick’s next point. He drew the connection that moving those business processes that need to continually change over time out of ERP and into edge applications and services enables continuous improvement by empowering people to continually strive for better ways of doing things rather than be being bound by workflows that cannot change. A compelling connection: that SOA, and the overall Oracle AppAdvantage framework of which it is an integral part, can empower people towards continuous improvement in business processes and as a result drive business leadership and business excellence. What better a case for technology innovation?

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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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  • 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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  • NetBeans 6.9 Released

    - by Duncan Mills
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  • Get Ready For C# 4.0!

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  • Inversion of control in Unity?

    - by user3206275
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  • VDC Research Webcast: Engineering Business Value in the IoT with Java 8

    - by tangelucci
    Date: Thursday, June 19, 2014 Time: 9:30 AM PDT, 12:30 PM EDT, 17:30 GMT The growth of the Internet of Things (IoT) opens up new service-driven opportunities, delivering increased efficiencies, better customer value, and improved quality of life. Realizing the full potential of the Internet of Things requires that we change how we view and build devices. These next-generation systems provide the core foundation of the services, rapidly transforming data to information to value. From healthcare to building control systems to vehicle telematic systems, the IoT focuses on how conneted devices can become more intelligent, enhance interoperability with other devices, systems and services, and drive timely decisions while delivering real business return for all. Join this webcast to learn about: Driving both revenue opportunities and operational efficiencies for the IoT value chain Leveraging Java to make devices more secure How Java can help overcome resource gaps around intelligent connected devices Suggestions on how to better manage fragmentation in embedded devices Register here: http://event.on24.com/r.htm?e=793757&s=1&k=4EA8426D0D31C60A2EDB139635FF75AB

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  • Visual Studio 2010 and .NET 4 Released

    - by ScottGu
    The final release of Visual Studio 2010 and .NET 4 is now available. Download and Install Today MSDN subscribers, as well as WebsiteSpark/BizSpark/DreamSpark members, can now download the final releases of Visual Studio 2010 and TFS 2010 through the MSDN subscribers download center.  If you are not an MSDN Subscriber, you can download free 90-day trial editions of Visual Studio 2010.  Or you can can download the free Visual Studio express editions of Visual Web Developer 2010, Visual Basic 2010, Visual C# 2010 and Visual C++.  These express editions are available completely for free (and never time out).  If you are looking for an easy way to setup a new machine for web-development you can automate installing ASP.NET 4, ASP.NET MVC 2, IIS, SQL Server Express and Visual Web Developer 2010 Express really quickly with the Microsoft Web Platform Installer (just click the install button on the page). What is new with VS 2010 and .NET 4 Today’s release is a big one – and brings with it a ton of new feature and capabilities. One of the things we tried hard to focus on with this release was to invest heavily in making existing applications, projects and developer experiences better.  What this means is that you don’t need to read 1000+ page books or spend time learning major new concepts in order to take advantage of the release.  There are literally thousands of improvements (both big and small) that make you more productive and successful without having to learn big new concepts in order to start using them.  Below is just a small sampling of some of the improvements with this release: Visual Studio 2010 IDE  Visual Studio 2010 now supports multiple-monitors (enabling much better use of screen real-estate).  It has new code Intellisense support that makes it easier to find and use classes and methods. It has improved code navigation support for searching code-bases and seeing how code is called and used.  It has new code visualization support that allows you to see the relationships across projects and classes within projects, as well as to automatically generate sequence diagrams to chart execution flow.  The editor now supports HTML and JavaScript snippet support as well as improved JavaScript intellisense. The VS 2010 Debugger and Profiling support is now much, much richer and enables new features like Intellitrace (aka Historical Debugging), debugging of Crash/Dump files, and better parallel debugging.  VS 2010’s multi-targeting support is now much richer, and enables you to use VS 2010 to target .NET 2, .NET 3, .NET 3.5 and .NET 4 applications.  And the infamous Add Reference dialog now loads much faster. TFS 2010 is now easy to setup (you can now install the server in under 10 minutes) and enables great source-control, bug/work-item tracking, and continuous integration support.  Testing (both automated and manual) is now much, much richer.  And VS 2010 Premium and Ultimate provide much richer architecture and design tooling support. VB and C# Language Features VB and C# in VS 2010 both contain a bunch of new features and capabilities.  VB adds new support for automatic properties, collection initializers, and implicit line continuation support among many other features.  C# adds support for optional parameters and named arguments, a new dynamic keyword, co-variance and contra-variance, and among many other features. ASP.NET 4 and ASP.NET MVC 2 With ASP.NET 4, Web Forms controls now render clean, semantically correct, and CSS friendly HTML markup. Built-in URL routing functionality allows you to expose clean, search engine friendly, URLs and increase the traffic to your Website.  ViewState within applications can now be more easily controlled and made smaller.  ASP.NET Dynamic Data support has been expanded.  More controls, including rich charting and data controls, are now built-into ASP.NET 4 and enable you to build applications even faster.  New starter project templates now make it easier to get going with new projects.  SEO enhancements make it easier to drive traffic to your public facing sites.  And web.config files are now clean and simple. ASP.NET MVC 2 is now built-into VS 2010 and ASP.NET 4, and provides a great way to build web sites and applications using a model-view-controller based pattern. ASP.NET MVC 2 adds features to easily enable client and server validation logic, provides new strongly-typed HTML and UI-scaffolding helper methods.  It also enables more modular/reusable applications.  The new <%: %> syntax in ASP.NET makes it easier to HTML encode output.  Visual Studio 2010 also now includes better tooling support for unit testing and TDD.  In particular, “Consume first intellisense” and “generate from usage" support within VS 2010 make it easier to write your unit tests first, and then drive your implementation from them. Deploying ASP.NET applications gets a lot easier with this release. You can now publish your Websites and applications to a staging or production server from within Visual Studio itself. Visual Studio 2010 makes it easy to transfer all your files, code, configuration, database schema and data in one complete package. VS 2010 also makes it easy to manage separate web.config configuration files settings depending upon whether you are in debug, release, staging or production modes. WPF 4 and Silverlight 4 WPF 4 includes a ton of new improvements and capabilities including more built-in controls, richer graphics features (cached composition, pixel shader 3 support, layoutrounding, and animation easing functions), a much improved text stack (with crisper text rendering, custom dictionary support, and selection and caret brush options).  WPF 4 also includes a bunch of support to enable you to take advantage of new Windows 7 features – including multi-touch and Windows 7 shell integration. Silverlight 4 will launch this week as well.  You can watch my Silverlight 4 launch keynote streamed live Tuesday (April 13th) at 8am Pacific Time.  Silverlight 4 includes a ton of new capabilities – including a bunch for making it possible to build great business applications and out of the browser applications.  I’ll be doing a separate blog post later this week (once it is live on the web) that talks more about its capabilities. Visual Studio 2010 now includes great tooling support for both WPF and Silverlight.  The new VS 2010 WPF and Silverlight designer makes it much easier to build client applications as well as build great line of business solutions, as well as integrate and bind with data.  Tooling support for Silverlight 4 with the final release of Visual Studio 2010 will be available when Silverlight 4 releases to the web this week. SharePoint and Azure Visual Studio 2010 now includes built-in support for building SharePoint applications.  You can now create, edit, build, and debug SharePoint applications directly within Visual Studio 2010.  You can also now use SharePoint with TFS 2010. Support for creating Azure-hosted applications is also now included with VS 2010 – allowing you to build ASP.NET and WCF based applications and host them within the cloud. Data Access Data access has a lot of improvements coming to it with .NET 4.  Entity Framework 4 includes a ton of new features and capabilities – including support for model first and POCO development, default support for lazy loading, built-in support for pluralization/singularization of table/property names within the VS 2010 designer, full support for all the LINQ operators, the ability to optionally expose foreign keys on model objects (useful for some stateless web scenarios), disconnected API support to better handle N-Tier and stateless web scenarios, and T4 template customization support within VS 2010 to allow you to customize and automate how code is generated for you by the data designer.  In addition to improvements with the Entity Framework, LINQ to SQL with .NET 4 also includes a bunch of nice improvements.  WCF and Workflow WCF includes a bunch of great new capabilities – including better REST, activation and configuration support.  WCF Data Services (formerly known as Astoria) and WCF RIA Services also now enable you to easily expose and work with data from remote clients. Windows Workflow is now much faster, includes flowchart services, and now makes it easier to make custom services than before.  More details can be found here. CLR and Core .NET Library Improvements .NET 4 includes the new CLR 4 engine – which includes a lot of nice performance and feature improvements.  CLR 4 engine now runs side-by-side in-process with older versions of the CLR – allowing you to use two different versions of .NET within the same process.  It also includes improved COM interop support.  The .NET 4 base class libraries (BCL) include a bunch of nice additions and refinements.  In particular, the .NET 4 BCL now includes new parallel programming support that makes it much easier to build applications that take advantage of multiple CPUs and cores on a computer.  This work dove-tails nicely with the new VS 2010 parallel debugger (making it much easier to debug parallel applications), as well as the new F# functional language support now included in the VS 2010 IDE.  .NET 4 also now also has the Dynamic Language Runtime (DLR) library built-in – which makes it easier to use dynamic language functionality with .NET.  MEF – a really cool library that enables rich extensibility – is also now built-into .NET 4 and included as part of the base class libraries.  .NET 4 Client Profile The download size of the .NET 4 redist is now much smaller than it was before (the x86 full .NET 4 package is about 36MB).  We also now have a .NET 4 Client Profile package which is a pure sub-set of the full .NET that can be used to streamline client application installs. C++ VS 2010 includes a bunch of great improvements for C++ development.  This includes better C++ Intellisense support, MSBuild support for projects, improved parallel debugging and profiler support, MFC improvements, and a number of language features and compiler optimizations. My VS 2010 and .NET 4 Blog Series I’ve been cranking away on a blog series the last few months that highlights many of the new VS 2010 and .NET 4 improvements.  The good news is that I have about 20 in-depth posts already written.  The bad news (for me) is that I have about 200 more to go until I’m done!  I’m going to try and keep adding a few more each week over the next few months to discuss the new improvements and how best to take advantage of them. Below is a list of the already written ones that you can check out today: Clean Web.Config Files Starter Project Templates Multi-targeting Multiple Monitor Support New Code Focused Web Profile Option HTML / ASP.NET / JavaScript Code Snippets Auto-Start ASP.NET Applications URL Routing with ASP.NET 4 Web Forms Searching and Navigating Code in VS 2010 VS 2010 Code Intellisense Improvements WPF 4 Add Reference Dialog Improvements SEO Improvements with ASP.NET 4 Output Cache Extensibility with ASP.NET 4 Built-in Charting Controls for ASP.NET and Windows Forms Cleaner HTML Markup with ASP.NET 4 - Client IDs Optional Parameters and Named Arguments in C# 4 - and a cool scenarios with ASP.NET MVC 2 Automatic Properties, Collection Initializers and Implicit Line Continuation Support with VB 2010 New <%: %> Syntax for HTML Encoding Output using ASP.NET 4 JavaScript Intellisense Improvements with VS 2010 Stay tuned to my blog as I post more.  Also check out this page which links to a bunch of great articles and videos done by others. VS 2010 Installation Notes If you have installed a previous version of VS 2010 on your machine (either the beta or the RC) you must first uninstall it before installing the final VS 2010 release.  I also recommend uninstalling .NET 4 betas (including both the client and full .NET 4 installs) as well as the other installs that come with VS 2010 (e.g. ASP.NET MVC 2 preview builds, etc).  The uninstalls of the betas/RCs will clean up all the old state on your machine – after which you can install the final VS 2010 version and should have everything just work (this is what I’ve done on all of my machines and I haven’t had any problems). The VS 2010 and .NET 4 installs add a bunch of new managed assemblies to your machine.  Some of these will be “NGEN’d” to native code during the actual install process (making them run fast).  To avoid adding too much time to VS setup, though, we don’t NGEN all assemblies immediately – and instead will NGEN the rest in the background when your machine is idle.  Until it finishes NGENing the assemblies they will be JIT’d to native code the first time they are used in a process – which for large assemblies can sometimes cause a slight performance hit. If you run into this you can manually force all assemblies to be NGEN’d to native code immediately (and not just wait till the machine is idle) by launching the Visual Studio command line prompt from the Windows Start Menu (Microsoft Visual Studio 2010->Visual Studio Tools->Visual Studio Command Prompt).  Within the command prompt type “Ngen executequeueditems” – this will cause everything to be NGEN’d immediately. How to Buy Visual Studio 2010 You can can download and use the free Visual Studio express editions of Visual Web Developer 2010, Visual Basic 2010, Visual C# 2010 and Visual C++.  These express editions are available completely for free (and never time out). You can buy a new copy of VS 2010 Professional that includes a 1 year subscription to MSDN Essentials for $799.  MSDN Essentials includes a developer license of Windows 7 Ultimate, Windows Server 2008 R2 Enterprise, SQL Server 2008 DataCenter R2, and 20 hours of Azure hosting time.  Subscribers also have access to MSDN’s Online Concierge, and Priority Support in MSDN Forums. Upgrade prices from previous releases of Visual Studio are also available.  Existing Visual Studio 2005/2008 Standard customers can upgrade to Visual Studio 2010 Professional for a special $299 retail price until October.  You can take advantage of this VS Standard->Professional upgrade promotion here. Web developers who build applications for others, and who are either independent developers or who work for companies with less than 10 employees, can also optionally take advantage of the Microsoft WebSiteSpark program.  This program gives you three copies of Visual Studio 2010 Professional, 1 copy of Expression Studio, and 4 CPU licenses of both Windows 2008 R2 Web Server and SQL 2008 Web Edition that you can use to both develop and deploy applications with at no cost for 3 years.  At the end of the 3 years there is no obligation to buy anything.  You can sign-up for WebSiteSpark today in under 5 minutes – and immediately have access to the products to download. Summary Today’s release is a big one – and has a bunch of improvements for pretty much every developer.  Thank you everyone who provided feedback, suggestions and reported bugs throughout the development process – we couldn’t have delivered it without you.  Hope this helps, Scott P.S. In addition to blogging, I am also now using Twitter for quick updates and to share links. Follow me at: twitter.com/scottgu

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  • CodePlex Daily Summary for Friday, April 02, 2010

    CodePlex Daily Summary for Friday, April 02, 2010New ProjectsAE.Remoting: An alternative means of remoting for .NET to allow for intuitive usage and easy implementation into existing code.animated-smoke-modeling: This is an implementation or a demo of our method to model animated smokes. ASP.NET Google Maps: Extensible and easy to use, this is ASP.NET Google Maps Control. Drag & Drop and is ready to go. You can configure map style, add a PushPin using t...CartPatches able to see: CartPatches able to see youCodemix Cms: Codemix CmsDo the right thing - The Simple TodoManager: A simple Todo Manager which lets you focus on your daily most important tasks/todos. So do the right thing.....at your home, in your office, in you...Fast Console: Fast Console is a simple xml programming language. This may be a really good starting language as there are printing, variables and as soon as poss...Graphing Calculator in Silverlight: This was initially an effort to port a WPF graphing calculator written by Bob Brown (Microsoft) into Silverlight but soon after it became necessary...InformationVSTS: This application allows you to have all informations on VSTS installed. It also lets you know the server of BUILD and project.La Ranisima: La Ranisima is an open source "Space Invaders" alike game totally written in DHTML (JavaScript, CSS and HTML) that uses keyboard. This cross-platfo...La villa del seis: La villa del seis is a multiplatform point-and-click graphical adventure. Also, you can play it like a text adventure (interactive fiction) on a te...LParse: LParse is a monadic parser combinator library, similar to Haskell’s Parsec. It allows you create parsers on C# language. All parsers are first-clas...Manage Recents File/Project VS2005/2008: Clear Recents Files and Projects, and Clear Broken Links of Recents Files and Projects for VS2005 and VS2008. Developed in Visual Studio 2008 SP...Mavention: Mavention makes SharePoint work for you.MixMail: MixMailMixScrum: mixScrumMixTemplate: MixTemplate.NepomucenoBR Regex Learning Tool: This is a simple program designed to help people to study regular expressions.Pruebas: Pruebas is an open source game mix of text adventure and RPG written in Microsoft QBasic (under MS-DOS 6.22) that uses keyboard. Runs natively unde...Python Design by Contract: Simple to use invariants, pre- and postconditions which use some of the new metaprogramming features in Python 3.Rubik Cube's 3D Silverlight 3.0 Animated Solution: Rubik Cube's Silverlight 3.0 Animated Solution is a 3D presentation of Rubik Cube in range of up to 7x7x7 size with full functionality and an anima...Seminarka: Seminarka - ko treba znat šta je zna!SENAC 2010 - Projeto Integrador 2 (Material de Apoio): Material utilizado para apoiar os alunos da disciplina de Projeto integrador 2. O tema são sistemas web utilizando ASP.NET, com C# e banco de da...SENAC CG2010: Contém código apresentado em sala de aula para a disciplina de CG, 5ºBSI NoturnoSistema de facturación: Sistema de facturación desarrollado en C# para la clase de programación 3.SmartFront - WPF and Silverlight Toolkit: SmartFront is a framework piece which allow to quickly building Smart Client application in WPF and in Silverlight. This framework uses existing s...Solar 1: This is the ASP.NET MVC engine based on Oxite and used for 32planets.net.TemporalSQL: SQL Patterns - tables, queries, and functions - to design a temporal database. TFunkOrderSystem: The Funkalistic Blueprint and Items order management systemTribe.Cache: Tribe.Cache is a simple dictionary cache (persistent dictionary) written in C# which is easy to implement and use.tstProject: Testing ProjectUDC indexes parser: UDC (Universal Decimal Classification) indexes parserWebAssert: A test assertion library to assist in writing automated tests against websites. Allows for assertion of HTML validity, etc. Initially has support f...Words Via Subtitle: Words Via Subtitle makes it easier for English Learners to learn new words that appears in TV shows or movies. You'll no longer have to look up the...x5s - a cross site scripting (XSS) testing tool: x5s aims to be a specialized testing tool which assists penetration testers in finding cross-site scripting hot-spots. By auto-injecting token valu...XNA Shooter Engine: The XNA Shooter Engine is a game engine for XNA designed specifically with first-person-shooter-style games in mind. It's being developed for an as...我的开发集: for my study .net csharpNew ReleasesAppFabric Caching Admin Tool: AppFabric Caching Admin Tool 1.1: System Requirements:.NET 4.0 RC AppFabric Caching Beta2 Test On:Win 7 (64x) Note: Must run as Administrator !!!ASP.NET Google Maps: ASP.NET Google Maps 0.1b: Project Description Extensible and easy to use, this is ASP.NET Bing Maps Control. Drag & Drop and is ready to go. You can configure map style, add...AutoFixture: Version 1.0.9 (RC1): This is Release Candidate 1 of AutoFixture 1.1. This release contains no known bugs. Compared to AutoFixture 1.0, it fixes some bugs that were dis...Camlex.NET: Camlex.NET 2.0: Camlex.NET 2.0 release New features Search by field id Support for native System.Guid type for values Search by lookup id and lookup value D...CloudCache - Distributed Cache Tier with Azure: v1.0.0.1: New Release on April 1st 2010 No this is not April fools a new release has made it's way out. Below are the changes: Removed dependency on Azure S...DigitallyCreated Utilities: DigitallyCreated Utilities v1.0.1: This release is the v1.0.1 version of DigitallyCreated Utilities. This update is highly recommended for all users of v1.0.0 as it fixes a critical ...Fast Console: Fast Console Alpha: Fast Console is an easy to use and learn programming language. Code example is found in the file TestFile.xml When you've written your code just sa...Free Silverlight & WPF Chart Control - Visifire: Visifire SL and WPF Charts 3.0.6 beta Released: Hi, This release contains following enhancements. * Zooming feature has been enhanced with the new functionality of ZoomRectangle. Now, users...Graphing Calculator in Silverlight: 1.0.1: Graphing Calculator for Silverlight is written entirely in C# and is based on the Silverlight 3 release. I will soon release the full documentation...Home Access Plus+: v3.2.0.1: v3.2.0.1 Release Change Log: Fixed: Issue with & ampersand File Changes: ~/bin/CHS Extranet.dll ~/bin/CHS Extranet.pdb ~/Scripts/viewmode.jsIcarus Scene Engine: Icarus Professional 2 Alpha 2 v 1.10.329.913: Alpha release 2 of Icarus Professional. This release includes: IcarusX: The ActiveX-based browser control for rendering IPX projects online. Icaru...Line Counter: 1.5.2: The Line Counter is a tool to calculate lines of your code files. The tool was written in .NET 2.0. Line Counter 1.5.2 Added General Code Counter ...ManagedCv: ManagedCv v0.0.0.1: Win32Mavention: Mavention Simple Menu: SharePoint 2010 ships with a menu control that allows you to render a site menu using semantic markup. Using the Mavention Simple Menu you can do t...MDownloader: MDownloader-0.15.10.57200: Fixed uploading.com links detection; Fixed downloading from uploading.com; Fixed downloading from load.to; Fixed detecting incompatible sources;MixMail: V1: MixMailMixTemplate: v1: releaseMvcPager: MvcPager 1.3 for ASP.NET MVC 1.0: MvcPager 1.3 for ASP.NET MVC 1.0 compiled assembly files and demo projectsMvcPager: MvcPager 1.3 for ASP.NET MVC 2.0: MvcPager 1.3 for ASP.NET MVC 2.0 compiled assembly and demo projectsMvcUnity - ASP.NET MVC Dependency Injection: 2.1 Source Code: Drop 2.1 Source CodeNepomucenoBR Regex Learning Tool: NepomucenoBR Regex Learning Tool v0.1 alpha: This is the first version of this application. If you find any bug, please contact me at http://www.nepomucenobr.com.brNepomucenoBR Regex Learning Tool: NepomucenoBR Regex Learning Tool v0.1 source-code: This is the first version of this application. If you find any bug, please contact me at http://www.nepomucenobr.com.brocculo: occulo 0.2 binaries: Release build binaries instead of debug, should now work for other users. Fixed bit rotation and output filename bugs.occulo: occulo 0.2 source: Second source release. See binary release for changes.Python Design by Contract: v0.1: This is the inital release. I think it is working fine.SharePoint Labs: SPLab5002A-FRA-Level200: SPLab5002A-FRA-Level200 This SharePoint Lab will teach you how to modify CAML schema to have IntelliSense on Feature's GUID. Lab Language : French ...SharePoint Labs: SPLab5003A-FRA-Level100: SPLab5003A-FRA-Level100 This SharePoint Lab will teach you how to manually create a Feature, how to brand a Feature and how to incorporate ressourc...SharePoint Labs: SPLab5004A-FRA-Level100: SPLab5004A-FRA-Level100 This SharePoint Lab will teach you how to create a Feature within Visual Studio, how to brand it, how to incorporate ressou...SharePoint Labs: SPLab5005A-FRA-Level100: SPLab5005A-FRA-Level100 This SharePoint Lab will teach you how to create a Feature within Visual Studio, how to brand it, how to incorporate ressou...SSIS ReportGeneratorTask: Version 1.53: Some bugfixes to version 1.52 beta Server Report properties can be displayed. Snapshots can be created. Screenshots of the planned version 1.53 ca...TemporalSQL: April 2010: Initial set of prototypes demonstrating temporal patterns, queries, and functions in SQL ServerTortoiseHg: TortoiseHg 1.0.1: TortoiseHg 1.0.1 is a bug fix release. We recommend all users upgrade to this release. http://bitbucket.org/tortoisehg/stable/wiki/ReleaseNotes#t...Tribe.Cache: Tribe.Cache Alpha: Functional Alpha Release - Do not use in productionTS3QueryLib.Net: TS3QueryLib.Net Version 0.21.15.0: Changelog Added class "ServerListItemBase" which is used in the new method "GetServerListShort" of QueryRunner class. (Change of Beta 21) Added ...UDC indexes parser: Runtime Binary Alpha 1: First alpha versionVisual Studio DSite: Text To Binary (Visual C++ 2008): A simple c program that can convert text to binary. Source code only.x5s - a cross site scripting (XSS) testing tool: x5s 1.0 beta: PLACEHOLDER (coming soon)XNA Shooter Engine: GDK Tools 0.1.0.0: This is a small, very early release of the GDK Tools. The only included tool is Input Map Editor.XPath Visualizer: XPathVisualizer v1.2: Last updated 1 April 2010. This is not a joke! includes new features: Ctrl-S shortcut key for Saving the XML file Ctrl-F shortcut for re-form...すとれおじさん(仮): すとれおじさん β 0.01: とりあえず公開のバージョンです。 中途半端な機能がいっぱいあります。Most Popular ProjectsRawrWBFS ManagerASP.NET Ajax LibraryMicrosoft SQL Server Product Samples: DatabaseSilverlight ToolkitAJAX Control ToolkitWindows Presentation Foundation (WPF)ASP.NETLiveUpload to FacebookMicrosoft SQL Server Community & SamplesMost Active ProjectsRawrGraffiti CMSBase Class LibrariesjQuery Library for SharePoint Web ServicesBlogEngine.NETMicrosoft Biology FoundationN2 CMSLINQ to TwitterManaged Extensibility FrameworkFarseer Physics Engine

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