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devel/Algorithm-Bucketizer-0.13 (Score: 9.2878623E-4)
Distribute sized items to buckets with limited size
Algorithm::Bucketizer distributes items of a defined size into a number of dynamically created buckets, each of them capable of holding items of a defined total size.
devel/Acme-Comment-1.04 (Score: 9.2878623E-4)
Allow multi-line comments which are filtered out
Acme::Comment allows multi-line comments which are filtered out. Unlike the pseudo multi-line comment if (0) {}, the code being commented out need not be syntactically valid.
devel/Algorithm-C3-0.10 (Score: 9.2878623E-4)
Module for merging hierarchies using the C3 algorithm
This module implements the C3 algorithm. I have broken this out into it's own module because I found myself copying and pasting it way too often for various needs. Most of the uses I have for C3 revolve around class building and metamodels, but it could also be used for things like dependency resolution as well since it tends to do such a nice job of preserving local precedence orderings.
devel/Algorithm-Cluster-1.52 (Score: 9.2878623E-4)
Perl interface to C clustering library
This module is an interface to the C Clustering Library, a general purpose library implementing functions for hierarchical clustering (pairwise simple, complete, average, and centroid linkage), along with k-means and k-medians clustering, and 2D self-organizing maps. The library is distributed along with Cluster 3.0, an enhanced version of the famous Cluster program originally written by Michael Eisen while at Stanford University. The C clustering library was written by Michiel de Hoon. This module is a Perl wrapper for the C clustering library for cDNA microarray data, Copyright (C) 2002 Michiel Jan Laurens de Hoon.
devel/Algorithm-Dependency-1.110 (Score: 9.2878623E-4)
Base class for implementing various dependency trees
Algorithm::Dependency is a framework for creating simple read-only dependency hierarchies, where you have a set of items that rely on other items in the set, and require actions on them as well. Despite the most visible of these being software installation systems like the CPAN installer, or debian apt-get, they are useful in other situations. This module intentionally uses implementation-neutral words, to avoid confusion.
devel/Algorithm-BinPack-0.5 (Score: 9.2878623E-4)
Efficiently pack items into bins
Algorithm::BinPack efficiently packs items into bins. The bins are given a maximum size, and items are packed in with as little empty space as possible. An example use would be backing up files to CD, while minimizing the number of discs required.
devel/Algorithm-ChooseSubsets-0.02 (Score: 9.2878623E-4)
Perl algorithm to iterate through subsets of a list
Perl algorithm to iterate through subsets of a list. "Subsets" in this context refers to lists with elements taken from the original list, and in the same order as the elements in the original list. After creating the object, subsequent calls to next() will return the next such list in lexicographic order (where the alphabet is the original list).
devel/Algorithm-IncludeExclude-0.01 (Score: 9.2878623E-4)
Build and evaluate include/exclude lists
Algorithm::IncludeExclude lets you define a tree of include / exclude rules and then allows you to determine the best rule for a given path.
devel/Algorithm-LUHN-1.02 (Score: 9.2878623E-4)
Calculate the Modulus 10 Double Add Double checksum
This module calculates the Modulus 10 Double Add Double checksum, also known as the LUHN Formula. This algorithm is used to verify credit card numbers and Standard & Poor's security identifiers such as CUSIP and CSIN. You can find plenty of information about the algorithm by searching the web for "modulus 10 double add double".
devel/Algorithm-Diff-1.1903 (Score: 9.2878623E-4)
Perl interface to compute differences between two objects
Algorithm::Diff is a perl module that provides an interface to compute the difference between two files, two strings, or any other two lists of things. It uses an intelligent algorithm similar/identical to the one used by classical Unix diff(1). It is guaranteed to find the *smallest possible* set of differences.