Tobias Telge

dblp:375/7061 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0002-6700-6426ORCID · reported

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

Software engineering, systems software and programming languages · 1 · 1 since 2021

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 maintenance and evolution · 83% Requirements engineering and software design · 17%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution › traceability › traceability link recovery
documentation-to-code traceability
0.812024
Recovering Trace Links Between Software Documentation And Code · ICSE 2024
Software maintenance and evolution
traceability
0.812024
Recovering Trace Links Between Software Documentation And Code · ICSE 2024
Software maintenance and evolution › traceability
traceability link recovery
0.812024
Recovering Trace Links Between Software Documentation And Code · ICSE 2024
Requirements engineering and software design › software architecture
architecture documentation
0.212024
Recovering Trace Links Between Software Documentation And Code · ICSE 2024
Requirements engineering and software design
software architecture
0.212024
Recovering Trace Links Between Software Documentation And Code · ICSE 2024
YearPublicationVenuePosition
2024 Recovering Trace Links Between Software Documentation And Code
abstract
Introduction Software development involves creating various artifacts at different levels of abstraction and establishing relationships between them is essential. Traceability link recovery (TLR) automates this process, enhancing software quality by aiding tasks like maintenance and evolution. However, automating TLR is challenging due to semantic gaps resulting from different levels of abstraction. While automated TLR approaches exist for requirements and code, architecture documentation lacks tailored solutions, hindering the preservation of architecture knowledge and design decisions. Methods This paper presents our approach TransArC for TLR between architecture documentation and code, using component-based architecture models as intermediate artifacts to bridge the semantic gap. We create transitive trace links by combining the existing approach ArDoCo for linking architecture documentation to models with our novel approach ArCoTL for linking architecture models to code.
Jan Keim, Sophie Corallo, Dominik Fuchß, Tobias Hey 0001, Tobias Telge, Anne Koziolek
ICSE5