Intelligent Software Tooling for Improving Software Development
- URL: http://arxiv.org/abs/2310.10921v1
- Date: Tue, 17 Oct 2023 01:29:07 GMT
- Title: Intelligent Software Tooling for Improving Software Development
- Authors: Nathan Cooper
- Abstract summary: Deep Learning (DL) has shown huge advancements in automation across many domains, including Software Development processes.
One of the main reasons behind this success is the availability of large datasets such as open-source code available through GitHub or image datasets of mobile Graphical User Interfaces (GUIs) with RICO and ReDRAW to be trained on.
- Score: 3.1763879286782966
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Software has eaten the world with many of the necessities and quality of life
services people use requiring software. Therefore, tools that improve the
software development experience can have a significant impact on the world such
as generating code and test cases, detecting bugs, question and answering,
etc., The success of Deep Learning (DL) over the past decade has shown huge
advancements in automation across many domains, including Software Development
processes. One of the main reasons behind this success is the availability of
large datasets such as open-source code available through GitHub or image
datasets of mobile Graphical User Interfaces (GUIs) with RICO and ReDRAW to be
trained on. Therefore, the central research question my dissertation explores
is: In what ways can the software development process be improved through
leveraging DL techniques on the vast amounts of unstructured software
engineering artifacts?
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