Educational demonstration of building simple algorithms under good practices development (cross-building, unit testing, ...)

Simple-Hybesis-Algorithms

You can find a fork repository adding algorithm logging features (used for visualization) and its documentation here:

CMake - Cross-Building

The building relies on CMake, an Open-Source system that allows to easily build cross-platform applications by generating native makefiles (cf. http://www.cmake.org/cmake/resources/software.html).

Getting Started

Build using CMake-GUI:

Run CMake-GUI
Select source/target directory
Click on Configure the project
Click on Generate the Solution files
Open the solution file (if MSVC) and build or use make command.

Build in Command-Line (UNIX):

mkdir Simple-Hybesis-Algorithms-Build (Create Build directory)
cd Simple-Hybesis-Algorithms-Build    (Open build director)
ccmake ../Simple-Hybesis-Algorithms   (Configure the make given Source repository)
make                                  (Make command, use -j parameter to use multi-core)

Doxygen Documentation & CMake

Use the CMake **'BUILD_DOC'** (default to true) option to automatically setup Documentation Generation with doxygen.

Please find the last generated documentation here: http://michaeljeulin-l.com/Projects/SHAC/Doc/

GTest - Unit Testing & CMake

Use the CMake **'BUILD_TESTING'** (default to true) option to automatically setup Unit Testing with google test. It allows to very quickly get set up with C++ and google test:

Clone GTest via GIT
Setup the Unit Testings
Compile GTest at build time

Running Unit Tests (UTs)

E.g. to manually run the 'TestBasicBinary' Unit Test (using GTest):

Simple-Hybesis-Algorithms-Build/Modules/Search/Testing/Debug/TestBinary.exe  (Win)
./Simple-Hybesis-Algorithms-Build/Modules/Search/Testing/Debug/TestBinary    (UNIX)

Current Algorithms - Data Structures

Combinatory

Combinations: Compute all possible combinations of elements containing within the sequence.
Intersection: Compute the intersection of two sequences keeping duplicate keys distinct.
IsInterleaved: Determine whether or not a sequence is the interleave of the two others.
Permutations: Compute all possible permutations of elements containing within the sequence.

Data Structures

BinarySearchTree: Binary Search Tree, Ordered Tree or Sorted Binary Tree divides all its sub-trees into two segments: left sub-tree and right sub-tree.

Search

Binary Search: Iteratively proceed a dichotomous search, within a sorted sequence, on the first occurrence of the key.
Kth Smallest / Biggest element - Order Statitstics: Find the kth smallest/biggest element.
Maximal/Minimal Distance: Identify the two elements of the sequence that give the maximal/minimal distance.
Maximal/Minimal M Elements: Retrieve the m maximal/minimal values sorted in respectively decreasing increasing order.
Maximal/Minimal Sub-Sequence: Identify the sub-sequence with the maximum/minimum sum. One of the problem resolved by this algorithm is: "Given an array of gains/losses over time, find the period that represents the best/worst cumulative gain."

Sort

Bubble Sort: Sometimes referred to as sinking sort: proceed an in-place bubble-sort on the elements.
MergeInplace: Functor that proceeds a in place merge of two sequences of elements.
MergeSort: John von Neumann in 1945: Proceed merge-sort on the elements whether using an in-place strategy or using a buffer.
MergeWithBuffer: Functor that proceeds a merge of two sequences of elements using a buffer to improve time computation.
Partition-Exchange: Proceed an in-place partitioning on the elements.
Quick Sort - Partition-Exchange Sort: Proceed an in-place quick-sort on the elements.
Raddix Sort - LSD: Proceed the Least Significant Digit Raddix sort, a non-comparative integer sorting algorithm.