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In my artistic practice, I have defined the term “disorder” to mean a disturbance in established patterns, structures, or balances. I have defined the term “structure” to be an arrangement of constituents that results in a unified whole. I have defined “energy” to mean forces which either activate or are active upon entities. I seek to generate imagery that investigates relationships between disorder, structure, and energy.

We exhibit programs that illustrate the power of Lisp as a language for expressing the design and organization of computational systems. The examples are chosen to highlight the importance of abstraction in program design and to draw attention to the use of procedures to express abstractions.

In this thesis, we study theoretically and empirically the additive abstraction-based heuristics. First we present formal general definitions for abstractions that extend to general additive abstractions. We show that the general definition makes proofs of admissibility, consistency, and additivity easier, by proving that several previous methods for defining abstractions and additivity satisfy three imple conditions. Then we investigate two general methods for defining additive abstractions and run experiments to determine the effectiveness of these methods for two benchmark state spaces: TopSpin and the Pancake puzzle. Third, we propose that the accuracy of the heuristics generated by abstraction can be improved by checking for infeasibility. The theory and experiments demonstrate the approach to detect infeasibility and the application of this technique to different domains. Finally, we explore the applications of additive abstraction-based heuristics in two state spaces with nonuniform edge costs: the Sequential Ordering Problem (SOP) and the weighted Pancake puzzle. We formalize a novel way of generating additive and non-additive heuristics for these state spaces. Furthermore, we investigate the key concepts to generate good additive and non-additive abstractions. Experiments show that compared to some simple alternative heuristics, well chosen abstractions can enhance the quality of suboptimal solutions for large SOP instances and reduce search time for the weighted Pancake problems.

Ce travail porte sur l'application et l'utilisation par Jean Duns Scot de la théorie de l'indifférence de l'essence, issue du péripatétisme arabe, et se donne pour enjeu d'en comprendre le fonctionnement conceptuel. Solution conjointe aux questions de la constitution ontologique des choses, des rapports entre le langage et la réalité et du mode d'appréhension des notions générales dans l'abstraction, la théorie de l'indifférence de l'essence sert de sous-bassement à la métaphysique de Duns Scot. C'est au moyen de cette théorie qu'il est possible, comme le montre cette recherche, de relire certains grands thèmes de la métaphysique scotiste: la théorie de la nature commune et de l'haeccéité, la connaissance abstractive (cognitio abstractiva), et la théorie de la non identité formelle. Le travail tente surtout de dégager le caractère proprement méthodologique de la théorie des trois états de l'essence (triplex status essentiae), répondant à la question du statut de l'essence indifférente, à celle des prédicats d'ordre supérieur et au problème de la séparation dans l'abstraction.

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Many source code tools help software programmers analyze programs as they are being developed, but such tools can no longer be applied once the final programs are shipped to the user. This greatly limits users, security experts, and anyone other than the programmer who wishes to perform additional testing and program analysis. This dissertation is concerned with the development of scalable techniques for statically analyzing binary programs, which can be employed by anyone who has access to the binary. Unfortunately, static binary analysis is often more difficult than static source code analysis because the abstractions that are the basis of source code programs, such as variables, types, functions, and control flow structure, are not explicitly present in binary programs. Previous approaches work around the the lack of abstractions by reasoning about the program at a lower level, but this approach has not scaled as well as equivalent source code techniques that use abstractions. This dissertation investigates an alternative approach to static binary analysis which is called abstraction recovery. The premise of abstraction recovery is that since many binaries are actually compiled from an abstract source language which is more suitable for analysis, the first step of static binary analysis should be to recover such abstractions. Abstraction recovery is shown to be feasible in two real-world applications. First, C abstractions are recovered by a newly developed decompiler. The second application recovers gadget abstractions to automatically generate return-oriented programming (ROP) attacks. Experiments using the decompiler demonstrate that recovering C abstractions improves scalability over low-level analysis, with applications such as verification and detection of buffer overflows seeing an average of 17× improvement. Similarly, gadget abstractions speed up automated ROP attacks by 99×. Though some binary analysis problems do not lend themselves to abstraction recovery because they reason about low-level or syntactic details, abstraction recovery is an attractive alternative to conventional low-level analysis when users are interested in the behavior of the original abstract program from which a binary was compiled, which is often the case.

Thèse (D. en psychologie)--Université du Québec à Montréal, 2005. / En tête du titre: Université du Québec à Montréal. Bibliogr.: f. 107-114. Publié aussi en version électronique.

Thesis (M.S.)--Worcester Polytechnic Institute. / Keywords: Computer science; abstraction quality; quality visualization. Includes bibliographical references (leaves 47-50).