98,222 research outputs found
A Game of Attribute Decomposition for Software Architecture Design
Attribute-driven software architecture design aims to provide decision
support by taking into account the quality attributes of softwares. A central
question in this process is: What architecture design best fulfills the
desirable software requirements? To answer this question, a system designer
needs to make tradeoffs among several potentially conflicting quality
attributes. Such decisions are normally ad-hoc and rely heavily on experiences.
We propose a mathematical approach to tackle this problem. Game theory
naturally provides the basic language: Players represent requirements, and
strategies involve setting up coalitions among the players. In this way we
propose a novel model, called decomposition game, for attribute-driven design.
We present its solution concept based on the notion of cohesion and
expansion-freedom and prove that a solution always exists. We then investigate
the computational complexity of obtaining a solution. The game model and the
algorithms may serve as a general framework for providing useful guidance for
software architecture design. We present our results through running examples
and a case study on a real-life software project.Comment: 23 pages, 5 figures, a shorter version to appear at 12th
International Colloquium on Theoretical Aspects of Computing (ICTAC 2015
A foundation for machine learning in design
This paper presents a formalism for considering the issues of learning in design. A foundation for machine learning in design (MLinD) is defined so as to provide answers to basic questions on learning in design, such as, "What types of knowledge can be learnt?", "How does learning occur?", and "When does learning occur?". Five main elements of MLinD are presented as the input knowledge, knowledge transformers, output knowledge, goals/reasons for learning, and learning triggers. Using this foundation, published systems in MLinD were reviewed. The systematic review presents a basis for validating the presented foundation. The paper concludes that there is considerable work to be carried out in order to fully formalize the foundation of MLinD
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Class decomposition for GA-based classifier agents – A Pitt approach
Incremental learning has been widely addressed in the machine learning literature to cope with learning tasks where the learning environment is ever changing or training samples become available over time. However, most research work explores incremental learning with statistical algorithms or neural networks, rather than evolutionary algorithms. The work in this paper employs genetic algorithms (GAs) as basic learning algorithms for incremental learning within one or more classifier agents in a multi-agent environment. Four new approaches with different initialization schemes are proposed. They keep the old solutions and use an “integration” operation to integrate them with new elements to accommodate new attributes, while biased mutation and crossover operations are adopted to further evolve a reinforced solution. The simulation results on benchmark classification data sets show that the proposed approaches can deal with the arrival of new input attributes and integrate them with the original input space. It is also shown that the proposed approaches can be successfully used for incremental learning and improve classification rates as compared to the retraining GA. Possible applications for continuous incremental training and feature selection are also discussed
Developing a labelled object-relational constraint database architecture for the projection operator
Current relational databases have been developed in order to improve the handling of
stored data, however, there are some types of information that have to be analysed for
which no suitable tools are available. These new types of data can be represented and treated
as constraints, allowing a set of data to be represented through equations, inequations
and Boolean combinations of both. To this end, constraint databases were defined and
some prototypes were developed. Since there are aspects that can be improved, we propose
a new architecture called labelled object-relational constraint database (LORCDB). This provides
more expressiveness, since the database is adapted in order to support more types of
data, instead of the data having to be adapted to the database. In this paper, the projection
operator of SQL is extended so that it works with linear and polynomial constraints and
variables of constraints. In order to optimize query evaluation efficiency, some strategies
and algorithms have been used to obtain an efficient query plan.
Most work on constraint databases uses spatiotemporal data as case studies. However,
this paper proposes model-based diagnosis since it is a highly potential research area,
and model-based diagnosis permits more complicated queries than spatiotemporal examples.
Our architecture permits the queries over constraints to be defined over different sets
of variables by using symbolic substitution and elimination of variables.Ministerio de Ciencia y Tecnología DPI2006-15476-C02-0
A Rigorous Approach to Relate Enterprise and Computational Viewpoints
Multiviewpoint approaches allow stakeholders to design a system from stakeholder-specific viewpoints. By this, a separation of concerns is achieved, which makes designs more manageable. However, to construct a consistent multiviewpoint design, the relations between viewpoints must be defined precisely, so that the consistency of designs from these viewpoints can be verified. The goal of this paper is to make the consistency rules between (a slightly adapted version of) the RM-ODP enterprise and computational viewpoints more precise and to make checking the consistency between these viewpoints practically applicable. To achieve this goal, we apply a generic framework for relating viewpoints that includes reusable consistency rules. We implemented the consistency rules in a tool to show their applicability
Automated IDEF3 and IDEF4 systems design specification document
The current design is presented for the automated IDEF3 and IDEF4 tools. The philosophy is described behind the tool designs as well as the conceptual view of the interacting components of the two tools. Finally, a detailed description is presented of the existing designs for the tools using IDEF3 process descriptions and IDEF4 diagrams. In the preparation of these designs, the IDEF3 and IDEF4 methodologies were very effective in defining the structure and operation of the tools. The experience in designing systems in this fashion was very valuable and resulted in future systems being designed in this way. However, the number of IDEF3 and IDEF4 diagrams that were produced using a Macintosh for this document attest to the need for an automated tool to simplify this design process
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