Dualna natura programów komputerowych

The paper is devoted to the discussion on ontological status of the computerprograms. The most popular conceptions are presented and critically discussed:programs as concrete abstractions, as quasi-particular objects (similar to musicalpieces), as mathematical objects (of different kinds), and finally – programas digital pattern. Advantages and disadvantages of those approachesare pointed out and some possible solutions are proposed.The paper is devoted to the discussion on ontological status of the computerprograms. The most popular conceptions are presented and critically discussed:programs as concrete abstractions, as quasi-particular objects (similar to musicalpieces), as mathematical objects (of different kinds), and finally – programas digital pattern. Advantages and disadvantages of those approachesare pointed out and some possible solutions are proposed

Extended ML: Past, present and future

An overview of past, present and future work on the Extended ML formal program development framework is given, with emphasis on two topics of current active research: the semantics of the Extended ML specification language, and tools to support formal program development

Higher-Order Horn Clauses

A generalization of Horn clauses to a higher-order logic is described and examined as a basis for logic programming. In qualitative terms, these higher-order Horn clauses are obtained from the first-order ones by replacing first-order terms with simply typed λ-terms and by permitting quantification over all occurrences of function symbols and some occurrences of predicate symbols. Several proof-theoretic results concerning these extended clauses are presented. One result shows that although the substitutions for predicate variables can be quite complex in general, the substitutions necessary in the context of higher-order Horn clauses are tightly constrained. This observation is used to show that these higher-order formulas can specify computations in a fashion similar to first-order Horn clauses. A complete theorem proving procedure is also described for the extension. This procedure is obtained by interweaving higher-order unification with backchaining and goal reductions, and constitutes a higher-order generalization of SLD-resolution. These results have a practical realization in the higher-order logic programming language called λProlog

Analyzing decision making in software design

A model is given for the analysis of rationality in design decision making. We define a formal means for answering the query, To what extent has a designer, on a particular occasion, using an explicit definition of 'good', decided rationally?A decision rationality classification scheme is proposed. This scheme incorporates non-compensatory decision analysis techniques (dominance and conjunctive cut-off) as well as compensatory techniques (simple and hierarchical additive weighting, linear assignment, concordance, and displaced ideal). A formal definition of design decision is derived by extending the Lehman, Stenning, Turski transformational model of the software design process. Their view of artifact specification mappings between linguistic systems is extended to include the concomitant effect of the mapping on resource expenditure.A formal specification for decision control knowledge is defined. This representation is the union of that knowledge required to support the various decision analysis techniques. Presumed to operationalize a designer's goals, the knowledge representation scheme includes five levels:1. Each objective expresses some relevant design concern for an artifact and/or resource characteristic.2. Each criterion expresses some relevant decomposition of a superior objective or criterion.3. Each attribute expresses the bottom-most decomposition for a superior criterion. Each attribute may have a weight indicating its relative contribution to its superior criterion.4. For each attribute, a value function expresses the designer's preference ordering over observed performance for an attribute.5. For each attribute, an observation channel describes an observer independent metric over some specification (either resource or artifact) rendered in some linguistic system and a procedure for application of that metric.Our model is applied to problems in Structured Design and conceptual data modeling. We argue that a comprehensive design history must include not only the transformations applied but also the rationale used in deciding their application. This rationale must include decision control knowledge governing both artifact (product) and resource (process) facets of design decision making. The principal contribution of this work is that the opacity of the decision intensive aspects of design are reduced thereby taking a necessary step for increasing the efficiency and effectiveness of software development

System building : estudio etnográfico de los proyectos de investigación de la School of Computer Science de Carnegie Mellon University, un "computer-intensive campus" norteamericano

Esta tesis consiste en una etnografía de la cultura informática de investigación de la Carnegie Mellon University, desarrollada mediante un trabajo de campo de dos años en la School of Computer Science de dicha universidad entre 1990 y 1993. Un equipo de dos antropológos, Arcadio Rojo y un servidor, dirigidos por la profesora Maria Jesus Buxó, catedrática de Antropología Cultural de la Universidad de Barcelona, y asesorados por el profesor Ángel Jordán, catedratico de Electronic Engineer en la CMU y en esa época Rector de dicha universidad, desarrollamos sendas tesis doctorales dentro del proyecto de investigación «Ciencias del diseño, nuevas tecnologías y tradición cultural», acordado entre la UB y la CMU con el apoyo económico del Departament de la Presidència de la Generalitat de Catalunya y del Centro Divulgador de Informática del gobierno catalán. En concreto esta tesis se centra en el estudio de los proyectos de investigación de los «computer scientists» de esa universidad. Desde los años 60s esta escuela ha mantenido el liderazgo en la investigación en computer science en los USA. Esta investigación ha sido y continua siendo inspirada en las «ciencias del diseño» de Herbert, Simon, professor de psicologia cognitiva y de Inteligencia Artificial de dicho campus. Esta investigación ha creado un sistema de conocimiento organizado, esto es, una cultura diferente al resto de culturas acadèmicas tradicionales tanto científicas como ingenieras. Su conocimiento basado en el diseño es característico de la denominada «high tech». Su origen está en el sistema de investigación para la defensa desarrollada durante la II GM y posteriormente donde a través de proyectos como el Manhattan Engineering District los científicos y ingenieros trabajaron mano a mano hasta fusionar sus conocimientos, dando lugar a las «sciences of the artificial». Turing, von Neumann, Shannon, o el propio Simon, son los «científicos del diseño» que dieron lugar a este nuevo sistema de conocimiento que se ha prolongado hasta nuestros dias y que compite y se diferencia del sistema de conocimiento organizado clasico de los sistemas de Ciencia_Tecnologia_Industria. El modelo de CMU esta basado en High Tech_Defensa. En tanto que conocimiento socialmente compartido, la SCS de CMU no funciona como una facultad universitaria típica. Su modelo de investigación está financiado desde los años 60 fundamentalmente por DARPA, la agencia del Departament de Defensa de los USA encargada de la investigación de frontera. Es por lo tanto un modelo de «mission-driven research», diferente del clásico modelo de investigacion de la NSF, establecido por Vanevar Bush tras la II GM. Finalmente, la etnografía realizada alimenta una nueva disciplina antropológica que la Dra. Buxó i el Dr. Jordán denominan tecnoantropologia: "el estudio de la tecnología como un sistema cultural. Ello significa el análisis del contexto social (producción, consumo, recursos humanos, redes de colaboración,...) así como el conocimiento cultural (ciencia, ideología, sentido común...) donde esta tecnología es construída (industria, sociedad, instituciones...) y su feedback sobre nuevas pautas de adaptación social y de innovación de conocimiento. Desde un punto de vista prospectivo, la tecnoantropología elabora los sistemas expertos de conocimiento desde los cuales el diseño cultural puede ser realizado para la innovación de la productividad y la calidad del trabajo humano en la industria, corporaciones e instituciones de investigación y de enseñanza.By content analysis of interviews and written projects gathered in the community, this study seeks to understand the kinds of cultural knowledge that support a computer science culture and their differences with other kinds of cultural knowledge. It also attempts to analyze the meanings of this culture in an American high technology university. This study is based on two year fieldwork at Carnegie Mellon University in 1990-1991 as part of a research project between technologists at CMU and anthropologists from University of Barcelona. Carnegie Mellon has built a kind of high technology university, or computer university, based on a core research knowledge in computer science and technology. As a result of that context the term "science" has a different meaning in this community from that in the natural and social sciences. "Computer Science" at the SCS-CMU primarily means the creation of knowledge about what kind of computer system the researcher can design and how he can build it. This new research model is redefining what knowledge means in an advanced information society. In 1988 the Computer Science and Technology Board, a section of the National Research Council, in a rapport called " The National Challenge in Computer Science and Technology" said: " Since computer science is an artificial science (Simon 1981) theoretical computer science plays a very different role within computer science than, say, theoretical physics plays within physics. Theoretical physics seeks to understand the physical universe, which exists independently.Theoretical computer scientists seek to understand all possible architectures or algorithms, which computer scientists create themselves." This change in the cultural meaning of a key cultural knowledge of Western civilization, scientific knowledge, could have enormous consequences in the next future. We are changing from a natural scientific vision of the world, the world as a “natural order", to a technological one in which the world is conceived as a man-made machine, as an artifact

System building : estudio etnográfico de los proyectos de investigación de la School of Computer Science de Carnegie Mellon University, un "computer-intensive campus" norteamericano

[spa] Esta tesis consiste en una etnografía de la cultura informática de investigación de la Carnegie Mellon University, desarrollada mediante un trabajo de campo de dos años en la School of Computer Science de dicha universidad entre 1990 y 1993. Un equipo de dos antropológos, Arcadio Rojo y un servidor, dirigidos por la profesora Maria Jesus Buxó, catedrática de Antropología Cultural de la Universidad de Barcelona, y asesorados por el profesor Ángel Jordán, catedratico de Electronic Engineer en la CMU y en esa época Rector de dicha universidad, desarrollamos sendas tesis doctorales dentro del proyecto de investigación «Ciencias del diseño, nuevas tecnologías y tradición cultural», acordado entre la UB y la CMU con el apoyo económico del Departament de la Presidència de la Generalitat de Catalunya y del Centro Divulgador de Informática del gobierno catalán. En concreto esta tesis se centra en el estudio de los proyectos de investigación de los «computer scientists» de esa universidad. Desde los años 60s esta escuela ha mantenido el liderazgo en la investigación en computer science en los USA. Esta investigación ha sido y continua siendo inspirada en las «ciencias del diseño» de Herbert, Simon, professor de psicologia cognitiva y de Inteligencia Artificial de dicho campus. Esta investigación ha creado un sistema de conocimiento organizado, esto es, una cultura diferente al resto de culturas acadèmicas tradicionales tanto científicas como ingenieras. Su conocimiento basado en el diseño es característico de la denominada «high tech». Su origen está en el sistema de investigación para la defensa desarrollada durante la II GM y posteriormente donde a través de proyectos como el Manhattan Engineering District los científicos y ingenieros trabajaron mano a mano hasta fusionar sus conocimientos, dando lugar a las «sciences of the artificial». Turing, von Neumann, Shannon, o el propio Simon, son los «científicos del diseño» que dieron lugar a este nuevo sistema de conocimiento que se ha prolongado hasta nuestros dias y que compite y se diferencia del sistema de conocimiento organizado clasico de los sistemas de Ciencia_Tecnologia_Industria. El modelo de CMU esta basado en High Tech_Defensa. En tanto que conocimiento socialmente compartido, la SCS de CMU no funciona como una facultad universitaria típica. Su modelo de investigación está financiado desde los años 60 fundamentalmente por DARPA, la agencia del Departament de Defensa de los USA encargada de la investigación de frontera. Es por lo tanto un modelo de «mission-driven research», diferente del clásico modelo de investigacion de la NSF, establecido por Vanevar Bush tras la II GM. Finalmente, la etnografía realizada alimenta una nueva disciplina antropológica que la Dra. Buxó i el Dr. Jordán denominan tecnoantropologia: "el estudio de la tecnología como un sistema cultural. Ello significa el análisis del contexto social (producción, consumo, recursos humanos, redes de colaboración,...) así como el conocimiento cultural (ciencia, ideología, sentido común...) donde esta tecnología es construída (industria, sociedad, instituciones...) y su feedback sobre nuevas pautas de adaptación social y de innovación de conocimiento. Desde un punto de vista prospectivo, la tecnoantropología elabora los sistemas expertos de conocimiento desde los cuales el diseño cultural puede ser realizado para la innovación de la productividad y la calidad del trabajo humano en la industria, corporaciones e instituciones de investigación y de enseñanza.[eng] By content analysis of interviews and written projects gathered in the community, this study seeks to understand the kinds of cultural knowledge that support a computer science culture and their differences with other kinds of cultural knowledge. It also attempts to analyze the meanings of this culture in an American high technology university. This study is based on two year fieldwork at Carnegie Mellon University in 1990-1991 as part of a research project between technologists at CMU and anthropologists from University of Barcelona. Carnegie Mellon has built a kind of high technology university, or computer university, based on a core research knowledge in computer science and technology. As a result of that context the term "science" has a different meaning in this community from that in the natural and social sciences. "Computer Science" at the SCS-CMU primarily means the creation of knowledge about what kind of computer system the researcher can design and how he can build it. This new research model is redefining what knowledge means in an advanced information society. In 1988 the Computer Science and Technology Board, a section of the National Research Council, in a rapport called " The National Challenge in Computer Science and Technology" said: " Since computer science is an artificial science (Simon 1981) theoretical computer science plays a very different role within computer science than, say, theoretical physics plays within physics. Theoretical physics seeks to understand the physical universe, which exists independently.Theoretical computer scientists seek to understand all possible architectures or algorithms, which computer scientists create themselves." This change in the cultural meaning of a key cultural knowledge of Western civilization, scientific knowledge, could have enormous consequences in the next future. We are changing from a natural scientific vision of the world, the world as a “natural order", to a technological one in which the world is conceived as a man-made machine, as an artifact

Methods for construction and analysis of computational models in systems biology: applications to the modelling of the heat shock response and the self-assembly of intermediate filaments

Systems biology is a new, emerging and rapidly developing, multidisciplinary research field that aims to study biochemical and biological systems from a holistic perspective, with the goal of providing a comprehensive, system- level understanding of cellular behaviour. In this way, it addresses one of the greatest challenges faced by contemporary biology, which is to compre- hend the function of complex biological systems. Systems biology combines various methods that originate from scientific disciplines such as molecu- lar biology, chemistry, engineering sciences, mathematics, computer science and systems theory. Systems biology, unlike “traditional” biology, focuses on high-level concepts such as: network, component, robustness, efficiency, control, regulation, hierarchical design, synchronization, concurrency, and many others. The very terminology of systems biology is “foreign” to “tra- ditional” biology, marks its drastic shift in the research paradigm and it indicates close linkage of systems biology to computer science. One of the basic tools utilized in systems biology is the mathematical modelling of life processes tightly linked to experimental practice. The stud- ies contained in this thesis revolve around a number of challenges commonly encountered in the computational modelling in systems biology. The re- search comprises of the development and application of a broad range of methods originating in the fields of computer science and mathematics for construction and analysis of computational models in systems biology. In particular, the performed research is setup in the context of two biolog- ical phenomena chosen as modelling case studies: 1) the eukaryotic heat shock response and 2) the in vitro self-assembly of intermediate filaments, one of the main constituents of the cytoskeleton. The range of presented approaches spans from heuristic, through numerical and statistical to ana- lytical methods applied in the effort to formally describe and analyse the two biological processes. We notice however, that although applied to cer- tain case studies, the presented methods are not limited to them and can be utilized in the analysis of other biological mechanisms as well as com- plex systems in general. The full range of developed and applied modelling techniques as well as model analysis methodologies constitutes a rich mod- elling framework. Moreover, the presentation of the developed methods, their application to the two case studies and the discussions concerning their potentials and limitations point to the difficulties and challenges one encounters in computational modelling of biological systems. The problems of model identifiability, model comparison, model refinement, model inte- gration and extension, choice of the proper modelling framework and level of abstraction, or the choice of the proper scope of the model run through this thesis

First steps towards inferential programming

Computer Science Departmen