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Son Cuu Dang

dblp:167/7840 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
—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
Empirical software engineering · 44% Software maintenance and evolution · 44% Software testing · 13%

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

TopicWeightPapersLastEvidence papers
Empirical software engineering
collaborative software development
0.212015
Detecting semantic merge conflicts with variability-aware execution · ESEC/SIGSOFT FSE 2015
Software maintenance and evolution › software merging
semantic conflict detection
0.212015
Detecting semantic merge conflicts with variability-aware execution · ESEC/SIGSOFT FSE 2015
Software testing
test execution
0.112015
Detecting semantic merge conflicts with variability-aware execution · ESEC/SIGSOFT FSE 2015

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

variability-aware execution · 0.2
YearPublicationVenuePosition
2015 Detecting semantic merge conflicts with variability-aware execution
abstract
In collaborative software development, changes made in parallel by multiple developers may conflict. Previous research has shown that conflicts are common and occur as textual conflicts or semantic conflicts, which manifest as build or test failures. With many parallel changes, it is desirable to identify conflicts early and pinpoint the (minimum) set of changes involved. However, the costs of identifying semantic conflicts can be high because tests need to be executed on many merge scenarios. We propose Semex, a novel approach to detect semantic conflicts using variability-aware execution. We encode all parallel changes into a single program, in which "if" statements guard the alternative code fragments. Then, we run the test cases using variability-aware execution, exploring all possible concrete executions of the combined program with regard to all possible merge scenarios, while exploiting similarities among the executions to speed up the process. Variability-aware execution returns a formula describing all failing merge scenarios. In our preliminary experimental study on seven PHP programs with a total of 50 test cases and 19 semantic conflicts, Semex correctly detected all 19 conflicts.
Hung Viet Nguyen, My Huu Nguyen, Son Cuu Dang, Christian Kästner, Tien N. Nguyen
ESEC/SIGSOFT FSE3