Chunmei Pan

dblp:246/5357 · DBLP profile ↗
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1ranked-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 · 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 · 56% Empirical software engineering · 44%

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

TopicWeightPapersLastEvidence papers
Empirical software engineering › software engineering research methodology
industrial case study
0.412019
FinExpert: domain-specific test generation for FinTech systems · ESEC/SIGSOFT FSE 2019
Software testing
test generation
0.412019
FinExpert: domain-specific test generation for FinTech systems · ESEC/SIGSOFT FSE 2019
Software testing
test suite
0.112019
FinExpert: domain-specific test generation for FinTech systems · ESEC/SIGSOFT FSE 2019

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

empirical study · 0.4domain knowledge · 0.4
YearPublicationVenuePosition
2019 FinExpert: domain-specific test generation for FinTech systems
abstract
To assure high quality of software systems, the comprehensiveness of the created test suite and efficiency of the adopted testing process are highly crucial, especially in the FinTech industry, due to a FinTech system’s complicated system logic, mission-critical nature, and large test suite. However, the state of the testing practice in the FinTech industry still heavily relies on manual efforts. Our recent research efforts contributed our previous approach as the first attempt to automate the testing process in China Foreign Exchange Trade System (CFETS) Information Technology Co. Ltd., a subsidiary of China’s Central Bank that provides China’s foreign exchange transactions, and revealed that automating test generation for such complex trading platform could help alleviate some of these manual efforts. In this paper, we investigate further the dilemmas faced in testing the CFETS trading platform, identify the importance of domain knowledge in its testing process, and propose a new approach of domain-specific test generation to further improve the effectiveness and efficiency of our previous approach in industrial settings. We also present findings of our empirical studies of conducting domain-specific testing on subsystems of the CFETS Trading Platform.
Tiancheng Jin, Qingshun Wang, Lihua Xu, Chunmei Pan, Liang Dou 0001, Haifeng Qian, Liang He 0001, Tao Xie 0001
ESEC/SIGSOFT FSE4