Errors were encountered while validating xml schemas speed dating jackson mississippi
We start with a simple case: considering only a subset of the kind of schema information captured in a document-type definition (DTD) in XML 1.0 DTD syntax, we write a logic grammar to represent a schema or DTD and use it to validate a document. We launch a separate call on each to parse them according to the appropriate rule for their datatype.The most conventional-looking part of our grammar is the representation of the content models.
The same technique, of course, can be used to capture and use part of the information in a schema expressed in XML Schema 1.0. A purchase order (being of type purchase Order Type) has a ship-to address, a billing address, possibly a comment, and a list of items.
The patterns illustrated by the purchase-order schema are elaborated to handle various non-DTD constructs: post-schema-validation properties, error handling, substitution groups, xsi:type, and wildcards. The XML Schema processor we sketch below will normally call the parser with an empty list as the final parameter, to require that the entire input sequence be consumed. * * This DCG was generated by a literate programming system; if * maintenance is necessary, make changes to the source (dctgnotes.xml), * not to this output file.
This simple example shows how logic grammars can be applied as representations of schemas, but does not illustrate all aspects of schema validation. If we wish to see how much of the content of an element belongs to the base type, and how much to an extension of the base type, we can call the parser for the base type, with a variable as the final parameter, and the base type will consume as much of the input as it can. We can turn this simple context-free grammar E1 into an attribute grammar by adding parameters to the productions; I will call the attribute grammar E2. */ purchase Order -- Because we get the XML document already in tree form, the top-level rules don't have much work to do.
I show how the definitions and declarations of a schema expressed in XML Schema can be represented using a formal notation developed for writing attribute grammars in Prolog; in follow-on work I expect to provide Prolog equivalents for the validation rules, info-set contributions, and constraints on schemas given in rather formal English prose by [W3C 2001b] and [W3C 2001c]. S = s(np(det(the), n(apple)), vp(v(sings), np(pn(mary)))) Yes ?
If the arguments for formalizing technical specifications are correct, the Prolog representations ought (if they are properly done) to be less ambiguous, more compact, and easier to understand that the formal English of the specification. - Note that in a ‘conventional’ use of DCGs, the user or application will call the grammar just once, at the top level, and the parser itself will generate recursive calls for the nested grammatical constructs (e.g. Note, however, that we can if we wish make calls to any level of the grammar from arbitrary Prolog code.
The two major areas of difficulty have been: Furthermore, changes to the policy of IMS namespace creation and modification would enable the published schemas and implementations using the schemas to be more stable.
The work described below may be regarded, in part, as a test of these propositions.English and French) as a way of exposing ambiguity, vagueness, and misunderstandings early and forcing the working group to achieve greater clarity and precision in their work.If the second language used is a formal language, rather than a second natural language, this practice can have the same advantages, as well as the the added benefit that the resulting specification can be read and understood not only by human readers but also by machines.Whether the Prolog representation is clearer or not is something which individual readers must decide for themselves.The idea of direct interpretation of formal specifications is not new; many textbooks on formal methods or on specific formal methods (Z, the Vienna Development Method VDM, etc.) discuss it at least as an idea. With the guard, this rule can be paraphrased as saying “A noun (an n), has the structure ? Struc = s(np(pn(john)), vp(v(loves), np(pn(mary)))) Yes ? S = s(np(det(the), n(woman)), vp(v(eats), np(det(the), n(apple)))) Yes ? For example, the sample purchase order po1used as an example in [W3C 2001a] looks like this in the format described (I have added white space for legibility; the single quotation marks around some atoms are a way of ensuring that they can be read again by a Prolog implementation and recognized as atoms): [element(' Order, [xmlns:apo=' order Date='1999-10-20'], [element(ship To, [country='US'], [element(name, , ['Alice Smith']), element(street, , ['123 Maple Street']), element(city, , ['Mill Valley']), element(state, , ['CA']), element(zip, , ['90952']) ]), element(bill To, [country='US'], [element(name, , ['Robert Smith']), element(street, , ['8 Oak Avenue']), element(city, , ['Old Town']), element(state, , ['PA']), element(zip, , ['95819']) ]), element(' , ['Hurry, my lawn is going wild!
[Stepney 1993] provides a simple Web-accessible example of the idea: she illustrates the creation of a high-integrity compiler by Animation of a specification is probably easiest if the spec is in a formal language. '] ), element(items, , [element(item, [part Num='872-AA'], [element(product Name, , ['Lawnmower']), element(quantity, , ['1']), element('USPrice', , ['148.95']), element(' , ['Confirm this is electric'] ) ]), element(item, [part Num='926-AA'], [element(product Name, , ['Baby Monitor']), element(quantity, , ['1']), element('USPrice', , ['39.98']), element(ship Date, , ['1999-05-21']) ]) ]) ]) ]When elements and attributes are namespace-qualified, as the purchase Order and comment elements are in this example, the SWI-Prolog parser represents the name as a pair of two atoms, separated by a colon.
Before starting on the schema processor, however, it may be helpful to review the basics of definite-clause grammars and their notation. An element with complex type USAddress has a name, street, city, state, and zip.