{"type":"ScholarlyArticle","title":"The Conceptual Calculus For Automatic Program Understanding","authors":[{"name":"Daniel Goossens","slug":"daniel-goossens","given":"Daniel","family":"Goossens","affiliation":""}],"abstract":"The CAN system for automatic understanding of LISP programs is presented. When applied on a LISP progre~, CAN needs no assertion about what the program is intended to do. CAN's general task is to associate a meaning to a program, from which it is able to diagnose eemantic properties (unused portions of code, undefinitions, underused programs, classes of date for which evaluation of an expression never terminates), and to exhibit deep semantic properties. CAN's underlying theory is the conceptual calculus, based on the clausal form of predicate logic. It involves two main ideas - en induction principle specially adapted to program understanding (as opposed to program veriflcat ion). -An extension of unification to equation solving.","doi":null,"url":"https://ijcai.org/proceedings/1981/189","pdf":"https://ijcai.org/proceedings/1981/0189.pdf","markdown":"https://ijcai.org/proceedings/1981/189.md","bibtex":"https://ijcai.org/proceedings/1981/bibtex/189","volume":{"slug":"1981","title":"Proceedings of the Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1981","url":"https://ijcai.org/proceedings/1981/","year":1981,"location":"Vancouver, British Columbia, Canada","dates":"24-28 August 1981","editors":"Roger C. Schank","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Automatic Programming","track":"Automatic Programming","number":189,"pages":{"first":992,"last":996},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}