Papers
Topics
Authors
Recent
Detailed Answer
Quick Answer
Concise responses based on abstracts only
Detailed Answer
Well-researched responses based on abstracts and relevant paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses
Gemini 2.5 Flash
Gemini 2.5 Flash 39 tok/s
Gemini 2.5 Pro 49 tok/s Pro
GPT-5 Medium 12 tok/s Pro
GPT-5 High 18 tok/s Pro
GPT-4o 91 tok/s Pro
Kimi K2 191 tok/s Pro
GPT OSS 120B 456 tok/s Pro
Claude Sonnet 4 37 tok/s Pro
2000 character limit reached

Simple and Effective Relation-Based Approaches To XPath and XSLT Type Checking (Technical Report, Bad Honnef 2015) (1905.07362v1)

Published 17 May 2019 in cs.PL

Abstract: XPath is a language for addressing parts of an XML document. We give an abstract interpretation of XPath expressions in terms of relations on document node types. Node-set-related XPath language constructs are mapped straightforwardly onto basic, well-understood and easily computable relational operations. Hence our interpretation gives both extremely concise type-level denotational semantics and a practical analysis tool for the node-set fragment of the XPath 1.0 language. This method is part of the TPath implementation of XPath. XSL-T is a pure functional language for transforming XML documents. For the most common case, the transformation into an XML document, type checking of the transformation code is unfeasible in general, but strongly required in practice. It turned out that the relational approach of TPath can be carried over to check all fragments of the result language, which are contained verbatim in the transformation code. This leads to a technique called "Fragmented Validation" and is part of the txsl implementation of XSL-T.

Citations (1)

Summary

We haven't generated a summary for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.

Lightbulb On Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.