Investigation into the use of machine learning to detect memory leaks during continuous integration testing of observatory control software

Benjamin Carpenter; Alastair Borrowman

doi:10.1117/12.3018392

25 July 2024 Investigation into the use of machine learning to detect memory leaks during continuous integration testing of observatory control software

Benjamin Carpenter, Alastair Borrowman

Author Affiliations +

Proceedings Volume 13101, Software and Cyberinfrastructure for Astronomy VIII; 131012P (2024) https://doi.org/10.1117/12.3018392
Event: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

Abstract

During ongoing maintenance and development of software used to control the European Southern Observatory (ESO) Very Large Telescope (VLT), the detection of memory leaks in legacy and newly developed software is of the utmost importance. This paper describes investigations into the development and use of additional test support software using Machine Learning (ML) to determine the presence of memory leaks. The software is implemented to integrate within existing pytest code and is designed to be executed alongside software module nightly tests as part of Continuous Integration (CI) testing. The work’s prime objective is to highlight memory suspicious processes so that memory leaks can be found and fixed before software deployment at the observatory.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Benjamin Carpenter and Alastair Borrowman "Investigation into the use of machine learning to detect memory leaks during continuous integration testing of observatory control software", Proc. SPIE 13101, Software and Cyberinfrastructure for Astronomy VIII, 131012P (25 July 2024); https://doi.org/10.1117/12.3018392

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available