Machine Learning for Programming Languages

Jenni, Raphael (2022) Machine Learning for Programming Languages. Masters thesis, OST Ostschweizer Fachhochschule.

[thumbnail of Raphael Jenni_18514_assignsubmission_file_MachineLearningForProgrammingLanguages.pdf] Text
Raphael Jenni_18514_assignsubmission_file_MachineLearningForProgrammingLanguages.pdf - Supplemental Material

Download (2MB)

Abstract

Artificial Intelligence, or more precisely deep learning, has become a trending topic in the broad public and software engineering circles. Some exciting technologies have arisen from it, such as voice assistants or language translation services. Also, programmatically understanding source code and supporting the developer in writing better code have been a topic for a while. In recent times, a push toward combining these two fields has been made.
For a software engineer coming from the world of tackling a
problem with the help of algorithms with a predictable outcome, deep learning can be rather challenging to grasp. This paper aims to bring a software engineer or a programming language researcher up to speed on the current state of deep learning and show the possibilities of such technologies. All this, in an easily digestible manner for someone without any profound knowledge about deep learning.

Item Type: Thesis (Masters)
Subjects: Metatags > IFS (Institute for Software)
Divisions: Master of Advanced Studies in Software Engineering
Depositing User: Stud. I
Contributors:
Contribution
Name
Email
Thesis advisor
Mehta, Farhad
UNSPECIFIED
Date Deposited: 19 Sep 2022 07:39
Last Modified: 19 Sep 2022 07:39
URI: https://eprints.ost.ch/id/eprint/1068

Actions (login required)

View Item
View Item