Formal methods using text to specify abstract data types (ADTs) are powerful, but they require great effort and a high level of expertise. Visual programming languages present an alternative way of programming but are limited to building small programs. This research presents an approach for specifying ADTs using a combination of text and visual objects. Furthermore, it presents two algorithms to map those specifications into imperative code. DataLab, a computer program for the MacintoshTM computer, is an implementation model for this approach. DataLab consists of two major components: a graphical editor and a source code generator. The graphical editor allows the user to build a specification consisting of an interface part and an implementation part for each ADT. The interface of the ADT is specified textually in a window that is part of the graphical editor. The implementation part of the ADT includes the operations, which are specified in Data Lab as a set of "Condition/Action" transformations. These transformations describe the behavior of the operations and are built by selecting graphical objects from a palette and placing them on the screen. The source code generator takes the specification of the ADT as an input and generates an encapsulated Pascal code. It consists of two algorithms: the first maps the specification into its semantics, and the second maps the semantics into Pascal modules. / Graduation date: 1990

The eXtensible Markup Language (XML) has become the standard format for data exchange on the Internet, providing interoperability between different business applications. Such wide use results in large volumes of heterogeneous XML data, i.e., XML documents conforming to different schemas. Although schemas are important in many business applications, they are often missing in XML documents. In this thesis, we present a suite of algorithms that are effective in extracting schema information from a large collection of XML documents. We propose using the cost of NFA simulation to compute the Minimum Length Description to rank the inferred schema. We also studied using frequencies of the sample inputs to improve the precision of the schema extraction. Furthermore, we propose an evaluation framework to quantify the quality of the extracted schema. Experimental studies are conducted on various data sets to demonstrate the efficiency and efficacy of our approach.

This thesis develops a semiunification-based type inference procedure for the rank 2 fragment of System F, with an emphasis on practical considerations for the adoption of such a procedure into existing programming languages. Current semiunification-based rank 2 inference procedures (notably that of Kfoury and Wells) are limited in several ways, which hinder their use in real-world settings. First of all, the translation from an instance of the type inference problem to an instance of the semiunification problem (SUP) is indirect; in particular, because of a series of source-level transformations that take place before translation, the translation is not syntax-directed. As a result, type errors discovered during the semiunification process cannot be cleanly translated back to specific subexpressions of the source program that caused the error. Also, because the rank 2 fragment of System F lacks a principal types property, an inference procedure cannot output a single type that encompasses all of a given term's derivable types. The procedure must therefore either rely on user assistance to produce the right type, or simply choose arbitrarily one of the given term's possible types. The algorithm of Kfoury and Wells in particular makes degenerate type assumptions in the absence of user assistance, and consequently produces types that are of no practical use. We build up our system in stages; we begin by improving the SUP translation. Whereas termination for the Kfoury-Wells rank 2 inference procedure is assured by translating terms into instances of the acyclic semiunification problem (a decidable subset of SUP, which is undecidable in general), we formulate and target the R-acyclic semiunification problem---a larger decidable subset of SUP that facilitates a more concise translation from source terms. We next eliminate the source-level transformation of terms, in order to formulate a truly syntax-directed translation from a source term to a set of SUP-like constraints. In doing so, we find that even the full SUP itself is not sufficiently equipped to support such a translation. We formulate USUP, a superset of SUP that incorporates a new class of identifier we call an unknown. We formulate decidable subsets of USUP, and then formulate a truly syntax-directed translation from source terms into USUP, with guaranteed termination. Finally, to address the principal types problem, we introduce a notation for types in which we allow a particular class of variable to stand for type constructors, rather than ordinary types (an idea based on the so-called third-order lambda-calculus). We show that, with third-order types we can not only output large sets of useful types for a given term, without programmer assistance, but the types we output also generalize over more System F types than any type within System F itself can do, and still be a valid type for the source term. Thus, our system increases opportunities for separate compilation and code reuse beyond any existing system of which we are aware. Our system is sound, though incomplete in certain well-characterized ways, despite which our system performs exactly as one would hope on a variety of examples, which we illustrate in this thesis.

This thesis develops a semiunification-based type inference procedure for the rank 2 fragment of System F, with an emphasis on practical considerations for the adoption of such a procedure into existing programming languages. Current semiunification-based rank 2 inference procedures (notably that of Kfoury and Wells) are limited in several ways, which hinder their use in real-world settings. First of all, the translation from an instance of the type inference problem to an instance of the semiunification problem (SUP) is indirect; in particular, because of a series of source-level transformations that take place before translation, the translation is not syntax-directed. As a result, type errors discovered during the semiunification process cannot be cleanly translated back to specific subexpressions of the source program that caused the error. Also, because the rank 2 fragment of System F lacks a principal types property, an inference procedure cannot output a single type that encompasses all of a given term's derivable types. The procedure must therefore either rely on user assistance to produce the right type, or simply choose arbitrarily one of the given term's possible types. The algorithm of Kfoury and Wells in particular makes degenerate type assumptions in the absence of user assistance, and consequently produces types that are of no practical use. We build up our system in stages; we begin by improving the SUP translation. Whereas termination for the Kfoury-Wells rank 2 inference procedure is assured by translating terms into instances of the acyclic semiunification problem (a decidable subset of SUP, which is undecidable in general), we formulate and target the R-acyclic semiunification problem---a larger decidable subset of SUP that facilitates a more concise translation from source terms. We next eliminate the source-level transformation of terms, in order to formulate a truly syntax-directed translation from a source term to a set of SUP-like constraints. In doing so, we find that even the full SUP itself is not sufficiently equipped to support such a translation. We formulate USUP, a superset of SUP that incorporates a new class of identifier we call an unknown. We formulate decidable subsets of USUP, and then formulate a truly syntax-directed translation from source terms into USUP, with guaranteed termination. Finally, to address the principal types problem, we introduce a notation for types in which we allow a particular class of variable to stand for type constructors, rather than ordinary types (an idea based on the so-called third-order lambda-calculus). We show that, with third-order types we can not only output large sets of useful types for a given term, without programmer assistance, but the types we output also generalize over more System F types than any type within System F itself can do, and still be a valid type for the source term. Thus, our system increases opportunities for separate compilation and code reuse beyond any existing system of which we are aware. Our system is sound, though incomplete in certain well-characterized ways, despite which our system performs exactly as one would hope on a variety of examples, which we illustrate in this thesis.

Establishing the termination of programs is a fundamental problem in the field of software verification. For transformational programs, termination is used to extend partial correctness to total correctness. For reactive systems, termination reasoning is used to establish liveness properties. In the context of theorem proving, termination is used to establish the consistency of definitional axioms and to automate proofs by induction. Of course, termination is an undecidable problem, as Turing himself proved. However, the question remains: how automatic can a general termination analysis be in practice? In this dissertation, we develop two new general frameworks for reasoning about termination and demonstrate their effectiveness in automating the task of proving termination in the domain of applicative first-order functional languages. The foundation of the first framework is the development of the first known complete set of algorithms for ordinal arithmetic over an ordinal notation. We provide algorithms for ordinal ordering ($<$), addition, subtraction, multiplication, and exponentiation on the ordinals up to epsilon-naught. We prove correctness and complexity results for each algorithm. We also create a library for automating arithmetic reasoning over epsilon-naught in the ACL2 theorem proving system. This ordinal library enables new termination proofs that were previously not possible in previous versions of ACL2. The foundation of the second framework is an algorithm for fully automating termination reasoning with no user assistance. This algorithm uses a combination of theorem proving and static analysis to create a Calling Context Graph (CCG), a novel abstraction that captures the looping behavior of the program. Calling Context Measures (CCMs) are then used to prove that no infinite path through the CCG can be an actual computation of the program. We implement this algorithm in the ACL2, and empirically evaluate its effectiveness on the regression suite, a collection of over 11,000 user-defined functions from a wide variety of applications.

Ce travail porte sur la production de code séquentiel à partir du langage flot de données synchrone Lustre. La difficulté essentielle provient de l'aspect déclaratif du langage. En effet, il n'y a pas d'instruction de contrôle dans le langage Lustre ; toute la structure de contrôle du code objet doit donc être synthétisée par le compilateur. Cette synthèse consiste à construire un automate fini en simulant exhaustivement le comportement des variables booléennes du programme. Le code produit est particulièrement rapide ; en effet, la plupart des calculs booléens sont effectués une fois pour toute dès la compilation. En contrepartie, l'aspect exhaustif de cette démarche provoque parfois une véritable explosion de la taille du code. Ce problème peut être dû à la complexité intrinsèque du programme source ; il faut dans ce cas chercher un compromis entre rapidité et taille mémoire. Mais l'explosion peut être causée par la méthode de construction, qui produit très souvent des automates non minimaux ; nous avons donc étudié et développé un algorithme original qui construit à coup sûr des automates minimaux. Cet algorithme fait appel à de nombreuses manipulations symboliques de fonctions booléennes, que nous avons pu implémenter efficacement grâce à une représentation basée sur les graphes binaires de décision.

Thesis (M.Sc.(Computer Science))--University of Pretoria, 2008. / Includes bibliographical references (leaves 99-116).

Thesis (M.S.)--University of Pennsylvania, 1981. / "May 1981." Includes bibliographical references.

Thesis (M. Sc.)--University of Canterbury, 2009. / Typescript (photocopy). Includes bibliographical references (leaves 82-93). Also available via the World Wide Web.

Thesis (Ph. D.)--Florida State University, 2003. / Advisor: Dr. Gordon Erlebacher, Florida State University, College of Arts and Sciences, Dept. of Computer Science. Title and description from dissertation home page (viewed Apr. 8, 2004). Includes bibliographical references.