Strict RWS monad.
Inspired by the paper *Functional Programming with Overloading and Higher-Order Polymorphism*, Mark P Jones (http://web.cecs.pdx.edu/~mpj/) Advanced School of Functional Programming, 1995.

Strict state monads.
This module is inspired by the paper *Functional Programming with Overloading and Higher-Order Polymorphism*, Mark P Jones (http://web.cecs.pdx.edu/~mpj/) Advanced School of Functional Programming, 1995.

A monad transformer that combines ReaderT, WriterT and StateT. This version is strict; for a lazy version, see Control.Monad.Trans.RWS.Lazy, which has the same interface.

Strict state monads, passing an updatable state through a computation. See below for examples.
In this version, sequencing of computations is strict. For a lazy version, see Control.Monad.Trans.State.Lazy, which has the same interface.
Some computations may not require the full power of state transformers:
* For a read-only state, see Control.Monad.Trans.Reader.
* To accumulate a value without using it on the way, see Control.Monad.Trans.Writer.

The strict WriterT monad transformer, which adds collection of outputs (such as a count or string output) to a given monad.
This version builds its output strictly; for a lazy version, see Control.Monad.Trans.Writer.Lazy, which has the same interface.
This monad transformer provides only limited access to the output during the computation. For more general access, use Control.Monad.Trans.State instead.

Strict writer monads.
Inspired by the paper *Functional Programming with Overloading and Higher-Order Polymorphism*, Mark P Jones (http://web.cecs.pdx.edu/~mpj/pubs/springschool.html) Advanced School of Functional Programming, 1995.

An efficient implementation of maps from integer keys to values (dictionaries).
API of this module is strict in both the keys and the values. If you need value-lazy maps, use Data.IntMap.Lazy instead. The IntMap type itself is shared between the lazy and strict modules, meaning that the same IntMap value can be passed to functions in both modules (although that is rarely needed).
These modules are intended to be imported qualified, to avoid name clashes with Prelude functions, e.g.
> import Data.IntMap.Strict (IntMap)
> import qualified Data.IntMap.Strict as IntMap
The implementation is based on *big-endian patricia trees*. This data structure performs especially well on binary operations like union and intersection. However, my benchmarks show that it is also (much) faster on insertions and deletions when compared to a generic size-balanced map implementation (see Data.Map).
* Chris Okasaki and Andy Gill, "*Fast Mergeable Integer Maps*", Workshop on ML, September 1998, pages 77-86, http://citeseer.ist.psu.edu/okasaki98fast.html
* D.R. Morrison, "/PATRICIA -- Practical Algorithm To Retrieve Information Coded In Alphanumeric/", Journal of the ACM, 15(4), October 1968, pages 514-534.
Operation comments contain the operation time complexity in the Big-O notation http://en.wikipedia.org/wiki/Big_O_notation. Many operations have a worst-case complexity of *O(min(n,W))*. This means that the operation can become linear in the number of elements with a maximum of *W* -- the number of bits in an Int (32 or 64).
Be aware that the Functor, Traversable and Data instances are the same as for the Data.IntMap.Lazy module, so if they are used on strict maps, the resulting maps will be lazy.

An efficient implementation of ordered maps from keys to values (dictionaries).
API of this module is strict in both the keys and the values. If you need value-lazy maps, use Data.Map.Lazy instead. The Map type is shared between the lazy and strict modules, meaning that the same Map value can be passed to functions in both modules (although that is rarely needed).
These modules are intended to be imported qualified, to avoid name clashes with Prelude functions, e.g.
> import qualified Data.Map.Strict as Map
The implementation of Map is based on *size balanced* binary trees (or trees of *bounded balance*) as described by:
* Stephen Adams, "*Efficient sets: a balancing act*", Journal of Functional Programming 3(4):553-562, October 1993, http://www.swiss.ai.mit.edu/~adams/BB/.
* J. Nievergelt and E.M. Reingold, "*Binary search trees of bounded balance*", SIAM journal of computing 2(1), March 1973.
Note that the implementation is *left-biased* -- the elements of a first argument are always preferred to the second, for example in union or insert.
Operation comments contain the operation time complexity in the Big-O notation (http://en.wikipedia.org/wiki/Big_O_notation).
Be aware that the Functor, Traversable and Data instances are the same as for the Data.Map.Lazy module, so if they are used on strict maps, the resulting maps will be lazy.

Produces XHTML 1.0 Strict.

strictBufferOp is the BufferOp definition over ByteStrings, the non-lazy kind.

Throw a UnicodeException if decoding fails.

Throw a UnicodeException if encoding fails.

Check the invariant strictly.