Intelligent services are becoming increasingly more pervasive; application developers want to leverage the latest advances in areas
such as computer vision to provide new services and products to
users, and large technology firms enable this via RESTful APIs.
While such APIs promise an easy-to-integrate on-demand machine
intelligence, their current design, documentation and developer interface hides much of the underlying machine learning techniques
that power them. Such APIs look and feel like conventional APIs
but abstract away data-driven probabilistic behaviour—the implications of a developer treating these APIs in the same way as other,
traditional cloud services, such as cloud storage, is of concern. The
objective of this study is to determine the various pain-points developers face when implementing systems that rely on the most
mature of these intelligent services, specifically those that provide
computer vision. We use Stack Overflow to mine indications of the
frustrations that developers appear to face when using computer
vision services, classifying their questions against two recent classification taxonomies (documentation-related and general questions).
We find that, unlike mature fields like mobile development, there
is a contrast in the types of questions asked by developers. These
indicate a shallow understanding of the underlying technology that
empower such systems. We discuss several implications of these
findings via the lens of learning taxonomies to suggest how the
software engineering community can improve these services and
comment on the nature by which developers use them.
History
Pagination
1584-1596
Location
Seoul, South Korea
Start date
2020-06-27
End date
2020-07-19
ISSN
0270-5257
ISBN-13
9781450371216
Language
eng
Notes
This conference was originally scheduled to be held in Seoul, South Korea, however due the 2020 Covid Pandemic, it was held online
Publication classification
E1 Full written paper - refereed
Editor/Contributor(s)
[Unknown]
Title of proceedings
ICSE 2020 : Proceedings of the 2020 ACM/IEEE 42nd International Conference on Software Engineering
Event
Software engineering. International conference (42nd : 2020 : Online from Seoul, South Korea)