[2403.01359] ModelWriter: Text & Model-Synchronized Document Engineering Platform
Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Software Engineering

arXiv:2403.01359 (cs)
[Submitted on 3 Mar 2024]

Title:ModelWriter: Text & Model-Synchronized Document Engineering Platform

Authors:Ferhat Erata, Claire Gardent, Bikash Gyawali, Anastasia Shimorina, Yvan Lussaud, Bedir Tekinerdogan, Geylani Kardas, Anne Monceaux
View PDF HTML (experimental)
Abstract:The ModelWriter platform provides a generic framework for automated traceability analysis. In this paper, we demonstrate how this framework can be used to trace the consistency and completeness of technical documents that consist of a set of System Installation Design Principles used by Airbus to ensure the correctness of aircraft system installation. We show in particular, how the platform allows the integration of two types of reasoning: reasoning about the meaning of text using semantic parsing and description logic theorem proving; and reasoning about document structure using first-order relational logic and finite model finding for traceability analysis.
Comments: Published in: 2017 32nd IEEE/ACM International Conference on Automated Software Engineering (ASE)
Subjects: Software Engineering (cs.SE); Computation and Language (cs.CL)
Cite as: arXiv:2403.01359 [cs.SE]
  (or arXiv:2403.01359v1 [cs.SE] for this version)
  https://doi.org/10.48550/arXiv.2403.01359
Related DOI: https://doi.org/10.1109/ASE.2017.8115703

Submission history

From: Ferhat Erata [view email]
[v1] Sun, 3 Mar 2024 01:26:12 UTC (3,225 KB)
Full-text links:

Access Paper:

view license
Current browse context:
cs.SE
< prev   |   next >
new | recent | 2024-03
Change to browse by:
cs
cs.CL

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)