Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Marta Han

dblp:275/9419 · DBLP profile ↗
← Back
2ranked-venue papers
0as first author
0since 2021 · last 2020
0009-0006-8774-9170ORCID · corroborated

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

Software engineering, systems software and programming languages · 2

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 · 87% Software maintenance and evolution · 13%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software testing › automated testing
continuous integration testing
0.412020
PerfCI: A Toolchain for Automated Performance Testing during Continuous Integration of Python Projects · ASE 2020
Software testing
performance testing
0.412020
PerfCI: A Toolchain for Automated Performance Testing during Continuous Integration of Python Projects · ASE 2020
Software maintenance and evolution
performance regression
0.112020
PerfCI: A Toolchain for Automated Performance Testing during Continuous Integration of Python Projects · ASE 2020

Methods — techniques the papers use, named apart from their topics

performance analysis framework extension · 0.4
YearPublicationVenuePosition
2020 PerfCI: A Toolchain for Automated Performance Testing during Continuous Integration of Python Projects
abstract
Software performance testing is an essential quality assurance mechanism that can identify optimization opportunities. Automating this process requires strong tool support, especially in the case of Continuous Integration (CI) where tests need to run completely automatically and it is desirable to provide developers with actionable feedback. A lack of existing tools means that performance testing is normally left out of the scope of CI. In this paper, we propose a toolchain - PerfCI - to pave the way for developers to easily set up and carry out automated performance testing under CI. Our toolchain is based on allowing users to (1) specify performance testing tasks, (2) analyze unit tests on a variety of python projects ranging from scripts to full-blown flask-based web services, by extending a performance analysis framework (VyPR) and (3) evaluate performance data to get feedback on the code. We demonstrate the feasibility of our toolchain by using it on a web service running at the Compact Muon Solenoid (CMS) experiment at the world's largest particle physics laboratory --- CERN.
Omar Javed, Joshua Heneage Dawes, Marta Han, Giovanni Franzoni, Andreas Pfeiffer, Giles Reger, Walter Binder
ASE3
2020 Analysing the Performance of Python-Based Web Services with the VyPR Framework
Joshua Heneage Dawes, Marta Han, Omar Javed, Giles Reger, Giovanni Franzoni, Andreas Pfeiffer
RV2