Modularity is a means of managing product complexity by arranging components into hierarchical independent subassemblies of common purpose. It offers advantages to manufacturers and producers and is assumed to benefit users as well. The producers have received most of the focus, however. Designers must be able to ensure the needs of both parties are being met but too little is known about users' responses to modular designs and the designer's role in handling modularity. This thesis demonstrates that modularity has an impact on users. The research specifically focused on aspects of modularity available to users. It consisted of three phases: a review of existing literature, an interview phase, and a survey phase. The interview phase elicited common terms for discussing modularity in consumer products. The survey tested the traits that emerged. Both phases used object pairs with similar purpose but differing in degree of modularity. During the interview phase, participants were shown pictures of eight pairs of objects and asked questions about their use and maintenance. They were then asked to generate a series of word pairs, opposing descriptors that could be used to distinguish the two variants. The most commonly occurring pairs were transformed into survey questions. The survey used the same set of object pairs, each accompanied by descriptive phrases built around the traits elicited from the interviews. Survey participants were asked to identify which of the two variants was best described by each phrase and the strength of that association. The responses indicated that modularity generally increases users' perceptions of complexity, presence of replaceable parts, and versatility. Modularity also diminished perceptions of durability, ease of maintenance, and ease of use. Investigation of object groupings, both predefined and emergent in the data, revealed additional context sensitive relationships. Several traits also demonstrated strong correlations with each other. Establishing these relationships is necessary to convert assumptions into knowns before research can continue. This thesis offers designers insight into the expectations surrounding modular design. As manufacturers continue to push modular design, designers will need to understand its impact on end users to ensure the needs of all stakeholders are being met.

No description available.

Compilers are among the most widely-studied pieces of software; and, modularizing these valuable artifacts is a recurring theme in research. However, modularization of cross-cutting concerns in compilers is not yet well explored. Even today, implementation of one compiler concern scatters across and tangles with the implementation of several other concerns, thereby leading to a mismatch between different compiler modules and the operations they represent. Essentially, current compiler implementations fail to explicitly identify the control dependencies of different phases, and separately characterize the actions to execute during those phases. As a result, information about their program-execution path remains non-intuitive: it stays hidden within the program structure and cuts-across several phase implementations. Consequently, this makes compiler designs and artifacts difficult to comprehend, maintain and reuse. Such limitations occur primarily as a result of the inability of mainstream object-oriented languages, such as Java, to organize the cross-cutting concerns into clean modular units.<p> This thesis demonstrates how such modularity-issues in compilers can be addressed with the help of a relatively new, yet powerful programming paradigm called aspect-oriented programming.

My dissertation applies philosophical analysis to the problem of how we should cognitively characterize brain activity. Let us distinguish between high-level cognitive functions—e.g. decision-making, face recognition—and the lower-level computational operations that are carried out by discrete regions of the brain. One can assume that cognitive functions are assembled from interactions between relatively autonomous computational operations carried out by discrete brain regions. My thesis, stated very broadly, is that in order to be effective, the decomposition of a cognitive function into a set of interactions between localized computational operations may need to be specified domain-neutrally, and not in terms of a particular informational domain or stimulus class. Jerry Fodor’s influential work on modularity has sparked an industry of research that is based on the idea that the mind is, to a large extent, a configuration of domain-specific and relatively autonomous cognitive mechanisms, or modules. My treatment indicates how this modular approach must be modified in order successfully to decompose domain-specific cognitive functions into localizable computational operations. I proceed in two steps. First, I provide an analysis of the kinds of inferences that are used by cognitive scientists to postulate the existence of cognitive modules; I call these the modularity inferences. I offer a new characterization of these inferences, and argue that they can, and do, operate in three distinct modes in cognitive scientific research. Second, I present a general approach to the decomposition of a cognitive function into localizable computational operations. According to this approach, which I call the working zone approach, the contribution of a distinct brain region to a cognitive function is specified in terms of the type of operations that this region performs, and not in terms of a particular informational domain. I demonstrate the value of this approach in several research contexts within the cognitive sciences.

Compilers are among the most widely-studied pieces of software; and, modularizing these valuable artifacts is a recurring theme in research. However, modularization of cross-cutting concerns in compilers is not yet well explored. Even today, implementation of one compiler concern scatters across and tangles with the implementation of several other concerns, thereby leading to a mismatch between different compiler modules and the operations they represent. Essentially, current compiler implementations fail to explicitly identify the control dependencies of different phases, and separately characterize the actions to execute during those phases. As a result, information about their program-execution path remains non-intuitive: it stays hidden within the program structure and cuts-across several phase implementations. Consequently, this makes compiler designs and artifacts difficult to comprehend, maintain and reuse. Such limitations occur primarily as a result of the inability of mainstream object-oriented languages, such as Java, to organize the cross-cutting concerns into clean modular units.<p> This thesis demonstrates how such modularity-issues in compilers can be addressed with the help of a relatively new, yet powerful programming paradigm called aspect-oriented programming.

No description available.

My dissertation applies philosophical analysis to the problem of how we should cognitively characterize brain activity. Let us distinguish between high-level cognitive functions—e.g. decision-making, face recognition—and the lower-level computational operations that are carried out by discrete regions of the brain. One can assume that cognitive functions are assembled from interactions between relatively autonomous computational operations carried out by discrete brain regions. My thesis, stated very broadly, is that in order to be effective, the decomposition of a cognitive function into a set of interactions between localized computational operations may need to be specified domain-neutrally, and not in terms of a particular informational domain or stimulus class. Jerry Fodor’s influential work on modularity has sparked an industry of research that is based on the idea that the mind is, to a large extent, a configuration of domain-specific and relatively autonomous cognitive mechanisms, or modules. My treatment indicates how this modular approach must be modified in order successfully to decompose domain-specific cognitive functions into localizable computational operations. I proceed in two steps. First, I provide an analysis of the kinds of inferences that are used by cognitive scientists to postulate the existence of cognitive modules; I call these the modularity inferences. I offer a new characterization of these inferences, and argue that they can, and do, operate in three distinct modes in cognitive scientific research. Second, I present a general approach to the decomposition of a cognitive function into localizable computational operations. According to this approach, which I call the working zone approach, the contribution of a distinct brain region to a cognitive function is specified in terms of the type of operations that this region performs, and not in terms of a particular informational domain. I demonstrate the value of this approach in several research contexts within the cognitive sciences.

No description available.

Thesis (M.S.)--University of Missouri-Columbia, 2004. / Typescript. Includes bibliographical references (leaves 97-99). Also available on the Internet.

Thesis (Ph.D.)--University of Central Florida, 2008. / Adviser: Annie S. Wu. Includes bibliographical references (p. 139-146).