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Ilya Zorin

dblp:225/1680 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 2Artificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software testing · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing
search-based software testing
0.412019
Some challenges for software testing research (invited talk paper) · ISSTA 2019
YearPublicationVenuePosition
2019 Some challenges for software testing research (invited talk paper)
abstract
This paper outlines 4 open challenges for Software Testing in general and Search Based Software Testing in particular, arising from our experience with the Sapienz System Deployment at Facebook. The challenges may also apply more generally, thereby representing opportunities for the research community to further benefit from the growing interest in automated test design in industry.
Nadia Alshahwan, Andrea Ciancone, Mark Harman, Yue Jia 0001, Ke Mao, Alexandru Marginean, Alexander Mols, Hila Peleg, Federica Sarro, Ilya Zorin
ISSTA10
2018 Deploying Search Based Software Engineering with Sapienz at Facebook
abstract
We describe the deployment of the Sapienz Search Based Software Engineering (SBSE) testing system. Sapienz has been deployed in production at Facebook since September 2017 to design test cases, localise and triage crashes to developers and to monitor their fixes. Since then, running in fully continuous integration within Facebook’s production development process, Sapienz has been testing Facebook’s Android app, which consists of millions of lines of code and is used daily by hundreds of millions of people around the globe. We continue to build on the Sapienz infrastructure, extending it to provide other software engineering services, applying it to other apps and platforms, and hope this will yield further industrial interest in and uptake of SBSE (and hybridisations of SBSE) as a result. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
Nadia Alshahwan, Xinbo Gao 0002, Mark Harman, Yue Jia 0001, Ke Mao, Alexander Mols, Taijin Tei, Ilya Zorin
SSBSE8