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Ha Duy Trung

dblp:81/9655 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2011
—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
Requirements engineering and software design · 77% Software maintenance and evolution · 23%

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

TopicWeightPapersLastEvidence papers
Requirements engineering and software design › model-driven engineering
model-driven development
0.112011
Flexible generators for software reuse and evolution · ICSE 2011
Software maintenance and evolution
software evolution
0.012011
Flexible generators for software reuse and evolution · ICSE 2011

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

variability techniques · 0.1manual modification weaving · 0.1
YearPublicationVenuePosition
2011 Flexible generators for software reuse and evolution
abstract
Developers tend to use models and generators during initial development, but often abandon them later in software evolution and reuse. One reason for that is that code generated from models (e.g., UML) is often manually modified, and changes cannot be easily propagated back to models. Once models become out of sync with code, any future re-generation of code overrides manual modifications. We propose a flexible generator solution that alleviates the above problem. The idea is to let developers weave arbitrary manual modifications into the generation process, rather than modify already generated code. A flexible generator stores specifications of manual modifications in executable form, so that weaving can be automatically re-done any time code is regenerated from modified models. In that way, models and manual modification can evolve independently but in sync with each other, and the generated code never gets directly changed. As a proof of concept, we have already built a flexible generator prototype by a merger of conventional generation system and variability technique to handle manual modifications. We believe a flexible generator approach alleviates an important problem that hinders wide spread adoption of MDD in software practice.
Stan Jarzabek, Ha Duy Trung
ICSE2