LINQ Is Not Quick

Let me just say that I am not particularly a fan of either microbenchmarks or premature optimization. I also feel that LINQ extensions are a fine addition to the .NET standard library. The LINQ query syntax is also an integral part of the C# and F# languages.

That being said, there's an interesting and revealing tale to be told about the performance of LINQ to Objects.

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Lazy sequences and streams

Functional languages have the notion of lazy sequences, which are an abstraction of infinite sequences that are stored using a small, finite amount of memory. It would be wasteful to realize an entire infinite sequence before even using it. The basic idea is to only call the function that generates the sequence when needed, and cache the results. With lazy sequences, you don't blow the stack and the elements in the sequence are not recalculated everytime.

Let's look at how the two most popular and functional JVM languages handle lazy sequences.

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The WebBrowser nightmare

I recently had to use the WebBrowser .NET component in a project. The control is essentially Internet Explorer embedded in a UserControl component. Although the facilities for JavaScript interoperability and DOM manipualtion are pretty great, the control fails to meet simpler needs.

To override keyboard input handing in the control, we need to set the WebBrowserShortcutsEnabled property to false and handle the PreviewKeyDown event.

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Abstract and parameterized types

Scala supports both abstract and parameterized types, which are essentially revamped generics (in Java) or templates (in C++).

First off, methods can be parameterized, in order to abstract a generic type which can be used by it. The apply method in companion objects is the best place to start. Here's an example from the implementation of the List class in the Scala library.

object List {

  // ...

  def apply[A](xs: A*): List[A] = xs.toList
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