Abstract:
In a world of exponentially changing technologies it is the responsibility of the
developers to adapt to that new changes and to the learning curve, especially the novice
developers. Normally novice developers can find it hard to keep up with that learning
curve. One of the hardest sections in learning curves are the fundamental algorithms.
Therefore different types of tools and techniques have been introduced to help with that.
There is no tool or technique to suggest the fundamental algorithms to the novice
developers as they engage with the development which could be used as a method of
helping them to learn. This research looks in-depth to the current alternative solutions
to identify the above mentioned problem factor and to provide a solution.
As per the solution, WhichALGO, a machine learning based algorithm recommendation
system, which is integrated to an IDE as a plugin, helps the novice developers to quickly
adopt and learn the algorithms as they engage in development. It mainly uses the One
Hot Encoding to identify and recommend algorithms.
Different types of testing were conducted and are mentioned in the Testing chapter
while both qualitative and quantitative evaluations are elaborated in the evaluation
chapter. At the end of the desecration the final conclusion of the whole project including
the limitations and future works are mentioned.
