Mahajan, S., Alameer, A., McMinn, P.S. orcid.org/0000-0001-9137-7433 et al. (1 more author) (2017) Automated Repair of Layout Cross Browser Issues Using Search-Based Techniques. In: ISSTA 2017 Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis. International Symposium on Software Testing and Analysis (ISSTA 2017), 10-14 Jul 2017, Santa Barbara, California. ACM , pp. 249-260. ISBN 978-1-4503-5076-1
Abstract
A consistent cross-browser user experience is crucial for the success of a website. Layout Cross Browser Issues (XBIs) can severely undermine a website’s success by causing web pages to render incorrectly in certain browsers, thereby negatively impacting users’ impression of the quality and services that the web page delivers. Existing Cross Browser Testing (XBT) techniques can only detect XBIs in websites. Repairing them is, hitherto, a manual task that is labor intensive and requires significant expertise. Addressing this concern, our paper proposes a technique for automatically repairing layout XBIs in websites using guided search-based techniques. Our empirical evaluation showed that our approach was able to successfully fix 86% of layout XBIs reported for 15 different web pages studied, thereby improving their cross-browser consistency.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © 2017 ACM. This is an author produced version of a paper subsequently published in ISSTA 2017 Proceedings of the 26th ACM SIGSOFT International Symposium on Software Testing and Analysis. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 31 May 2017 09:06 |
Last Modified: | 19 Dec 2022 13:36 |
Published Version: | https://doi.org/10.1145/3092703.3092726 |
Status: | Published |
Publisher: | ACM |
Refereed: | Yes |
Identification Number: | 10.1145/3092703.3092726 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:116990 |