Feb. 15, 2023, 2:18 a.m. | Owura Asare, Meiyappan Nagappan, N. Asokan

cs.CR updates on arXiv.org arxiv.org

Several advances in deep learning have been successfully applied to the
software development process. Of recent interest is the use of neural language
models to build tools, such as Copilot, that assist in writing code. In this
paper we perform a comparative empirical analysis of Copilot-generated code
from a security perspective. The aim of this study is to determine if Copilot
is as bad as human developers - we investigate whether Copilot is just as
likely to introduce the same …

aim analysis bad build code copilot deep learning development development process generated github humans interest language language models perspective process security software software development study tools vulnerabilities writing

SOC 2 Manager, Audit and Certification

@ Deloitte | US and CA Multiple Locations

Director, Cybersecurity - Governance, Risk and Compliance (GRC)

@ Stanley Black & Decker | New Britain CT USA - 1000 Stanley Dr

Information Security Risk Metrics Lead

@ Live Nation Entertainment | Work At Home-Connecticut

IT Product Owner - Enterprise DevSec Platform (d/f/m)

@ Airbus | Hamburg - Finkenwerder

Senior Information Security Specialist

@ Arthur Grand Technologies Inc | Arlington, VA, United States

Information Security Controls SME

@ Sword | Aberdeen, Scotland, United Kingdom