@inproceedings{Geneves09a,
  author = {Pierre Genevès and Nabil Layaïda and Vincent Quint},
  title = {Identifying Query Incompatibilities with Evolving {XML} Schemas},
  booktitle = {ICFP'09, Proceedings of the 2009 ACM SIGPLAN International
 Conference on Functional Programming},
  location = {Edinburgh, UK},
  pages = {221-230},
  month = aug,
  year = 2009,
  url = {http://wam.inrialpes.fr/publications/2009/types-evolution.pdf},
  url2 = {http://hal.inria.fr/inria-00423058/},
  doi = {http://doi.acm.org/10.1145/1596550.1596583},
  x-proceedings = {yes},
  x-international-audience = {yes},
  abstract = {During the life cycle of an XML application, both schemas 
     and queries may change from one version to another. Schema evolutions
     may affect query results and potentially the validity of produced data.
     Nowadays, a challenge is to assess and accommodate the impact of these
     changes in evolving XML applications. Such questions arise naturally
     in XML static analyzers. These analyzers often rely on decision
     procedures such as inclusion between XML schemas, query containment
     and satisfiability. However, existing decision procedures cannot be
     used directly in this context. The reason is that they are unable to
     distinguish information related to the evolution from information
     corresponding to bugs. This paper proposes a predicate language within
     a logical framework that can be used to make this distinction. 
     We present a system for monitoring the effect of schema evolutions on
     the set of admissible documents and on the results of queries. The
     system is very powerful in analyzing various scenarios where the result
     of a query may not be anymore what was expected. Specifically, the
     system is based on a set of predicates which allow a fine-grained
     analysis for a wide range of forward and backward compatibility issues.
     Moreover, the system can produce counterexamples and witness documents
     which are useful for debugging purposes. The current implementation
     has been tested with realistic use cases, where it allows identifying
     queries that must be reformulated in order to produce the expected
     results across successive schema versions.}
}