A Pedagogical Framework for Domain-Specific Languages
Abstract
A framework for thinking about domain-specific languages (DSLs) divides them into internal DSLs, external DSLs, and language workbenches. In all cases, it's important to have an explicit semantic model so that they form a veneer over an underlying library. DSLs are valuable for increasing programmer productivity and improving communication with domain experts.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The prominence of auto-doc tools like Sphinx [13] suggests that the problem of gallery maintenance is not as simple as building a new documentation system.
“However, the prominence of auto-doc tools like Sphinx [13] would suggest that this problem is not as simple as building a new documentation system.”
From Considering Visualization Example Galleries (2024) · cites this paper as [13]
The citation lists haven’t been fetched yet
Cited by 27
- Authors
- Fowler, M.
- Affiliations
- Chaitanya Bharathi Institute of Technology (IN)
- Corresponding author
- Fowler, Martin
- Venue
- IEEE Software
- Published
- 2009-07
- Volume
- 26
- Issue
- 4
- Pages
- 13-14
- ISSN
- 0740-7459 (ISSN-L)
- OpenAlex
- W2089057459
- Cited by
- 27
- References
- 0
- Citations by year
- 2024: 1 · 2023: 3 · 2021: 2 · 2020: 2 · 2019: 1 · 2016: 1 · 2014: 3 · 2012: 4
- FWCI
- 15.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Software (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Software › Model-Driven Software Engineering Techniques
- Physical Sciences › Computer Science › Information Systems › Software Engineering Techniques and Practices
- Physical Sciences › Computer Science › Artificial Intelligence › Advanced Software Engineering Methodologies
- Keywords
- domain-specific languages, internal DSL, language workbenches, semantic models, developer productivity, pedagogical framework
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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