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In object-oriented programming, the iterator pattern is a design pattern in which an iterator is used to traverse a container and access the container's elements. The iterator pattern decouples algorithms from containers; in some cases, algorithms are necessarily container-specific and thus cannot be decoupled.
Specifically, the for loop will call a value's into_iter() method, which returns an iterator that in turn yields the elements to the loop. The for loop (or indeed, any method that consumes the iterator), proceeds until the next() method returns a None value (iterations yielding elements return a Some(T) value, where T is the element type).
Loop unrolling, also known as loop unwinding, is a loop transformation technique that attempts to optimize a program's execution speed at the expense of its binary size, which is an approach known as space–time tradeoff. The transformation can be undertaken manually by the programmer or by an optimizing compiler.
Loop-invariant code consists of statements or expressions that can be moved outside a loop body without affecting the program semantics. Such transformations, called loop-invariant code motion, are performed by some compilers to optimize programs. A loop-invariant code example (in the C programming language) is
foreach is usually used in place of a standard for loop statement. Unlike other for loop constructs, however, foreach loops [1] usually maintain no explicit counter: they essentially say "do this to everything in this set", rather than "do this x times". This avoids potential off-by-one errors and makes code simpler to read.
Loop tiling partitions a loop's iteration space into smaller chunks or blocks, so as to help ensure data used in a loop stays in the cache until it is reused. The partitioning of loop iteration space leads to partitioning of a large array into smaller blocks, thus fitting accessed array elements into cache size, enhancing cache reuse and eliminating cache size requirements.
The boundaries of the polytopes, the data dependencies, and the transformations are often described using systems of constraints, and this approach is often referred to as a constraint-based approach to loop optimization. For example, a single statement within an outer loop ' for i := 0 to n ' and an inner loop ' for j := 0 to i+2 ' is executed ...
In computer science, Luby transform codes (LT codes) are the first class of practical fountain codes that are near-optimal erasure correcting codes. They were invented by Michael Luby in 1998 and published in 2002. [1] Like some other fountain codes, LT codes depend on sparse bipartite graphs to trade reception overhead for encoding and ...