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Mirco Franzago

dblp:145/7675 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2018
0000-0003-4338-7746ORCID · corroborated

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

Software engineering, systems software and programming languages · 2 · 1 first-author

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
2 papers
Requirements engineering and software design · 83% Empirical software engineering · 17%

Topics — the 3 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Requirements engineering and software design
model-driven engineering
0.722018
Collaborative Model-Driven Software Engineering: A Classification Framework and a Research Map · IEEE Trans. Software Eng. 2018
Collaborative model-driven software engineering: a classification framework and a research map · ICSE 2018
Requirements engineering and software design › model-driven engineering
collaborative modeling
0.312018
Collaborative Model-Driven Software Engineering: A Classification Framework and a Research Map · IEEE Trans. Software Eng. 2018
Empirical software engineering › systematic literature review
systematic mapping study
0.112018
Collaborative Model-Driven Software Engineering: A Classification Framework and a Research Map · IEEE Trans. Software Eng. 2018

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

classification framework · 0.7systematic mapping study · 0.3
YearPublicationVenuePosition
2018 Collaborative model-driven software engineering: a classification framework and a research map
abstract
This proposal is about a study we recently published in the IEEE Transaction of Software Engineering journal [4].
Davide Di Ruscio, Mirco Franzago, Henry Muccini, Ivano Malavolta
ICSE2
2018 Collaborative Model-Driven Software Engineering: A Classification Framework and a Research Map
abstract
Context: Collaborative Model-Driven Software Engineering (MDSE) consists of methods and techniques where multiple stakeholders manage, collaborate, and are aware of each others' work on shared models. Objective: Collaborative MDSE is attracting research efforts from different areas, resulting in a variegated scientific body of knowledge. This study aims at identifying, classifying, and understanding existing collaborative MDSE approaches. Method: We designed and conducted a systematic mapping study. Starting from over 3,000 potentially relevant studies, we applied a rigorous selection procedure resulting in 106 selected papers, further clustered into 48 primary studies along a time span of 19 years. We rigorously defined and applied a classification framework and extracted key information from each selected study for subsequent analysis. Results: Our analysis revealed the following main fidings: (i) there is a growing scientific interest on collaborative MDSE in the last years; (ii) multi-view modeling, validation support, reuse, and branching are more rarely covered with respect to other aspects about collaborative MDSE; (iii) different primary studies focus differently on individual dimensions of collaborative MDSE (i.e., model management, collaboration, and communication); (iv) most approaches are language-specific, with a prominence of UML-based approaches; (v) few approaches support the interplay between synchronous and asynchronous collaboration. Conclusion: This study gives a solid foundation for classifying existing and future approaches for collaborative MDSE. Researchers and practitioners can use our results for identifying existing research/technical gaps to attack, better scoping their own contributions, or understanding existing ones.
Mirco Franzago, Davide Di Ruscio, Ivano Malavolta, Henry Muccini
IEEE Trans. Software Eng.1