| |||||||||||||||
PLMMS 2010 : Programming Languages for Mechanized Mathematics Systems | |||||||||||||||
Link: http://dream.inf.ed.ac.uk/events/plmms-2010/ | |||||||||||||||
| |||||||||||||||
Call For Papers | |||||||||||||||
The scope of this workshop is at the intersection of programming languages (PL) and mechanized mathematics systems (MMS). The latter category subsumes present-day computer algebra systems (CAS), interactive proof assistants (PA), and automated theorem provers (ATP), all heading towards fully integrated mechanized mathematical assistants. The program committee welcomes submissions on all aspects of programming languages and mechanised mathematics that meet, but not limited to, the following topics:
Input languages for MMS: all aspects of languages for the user to deploy or extend the system, both algorithmic and declarative. Typical examples are tactic languages such as Ltac in Coq, mathematical proof languages as in Mizar or Isar, and specialized programming languages built into CA systems. Mathematical modeling languages used for programming: the relation of logical descriptions vs. algorithmic content. For instance the logic of ACL2 extends a version of Lisp, that of Coq is close to Haskell, and some portions of HOL are similar to ML and Haskell, while Maple tries to do both simultaneously. Such mathematical languages offer rich specification capabilities, which are rarely available in regular programming languages. How can programming benefit from mathematical concepts, without limiting mathematics to the computational worldview? Programming languages and mathematical specifications: advanced mathematical concepts in programming languages that improve the expressive power of functional specifications, type systems, module systems etc. Programming languages with dependent types are of particular interest here, as is intentionality vs extensionality. Language elements for program verification: specific means built into a language to facilitate correctness proofs using MMS. For example, logical annotations within programs may be turned into verification conditions to be solved in a proof assistant eventually. How can MMS and PL be improved to make verification more convenient and mathematically appealing? |
|