18713951
Using CBR for Semantic Analysis of Software Specifications
Helping software designers in their task implies the development of tools with intelligent capabilities. One such capability is the integration of natural language understanding in CASE tools, thus improving the designer/tool communication. In this paper, we present a CBR approach for the generation of UML class diagrams from natural language text. This approach is implemented in a CASE tool, with the goal of helping the software designer create the first system model. We describe the natural language conversion module and give an overview of the tool in which it is integrated. Experimental results for retrieval and adaptation mechanisms are also presented.
15250271
Evaluation of Case-Based Maintenance Strategies in Software Design
CBR applications running in real domains can easily reach thousands of cases, which are stored in the case library. Retrieval times can increase greatly if the retrieval algorithm can not cope with such an amount of cases. Redundancy can also be a problem, focusing retrieval alternatives in a very restricted search space. Basically, the system's performance starts to degrade with the increase of the case-base size. Case-base maintenance allows CBR systems to deal with this problem, mainly through the use of case selection criteria. In this paper we present an experimental study about several case-base maintenance policies developed till now. We adapted and implemented these policies to a CBR system for software reuse and design, testing the applicability of these policies to cases with a complex representation (combination of tree and graph representations).
17691694
Case-Based Adaptation for UML Diagram Reuse
In this paper we present an approach to software design reuse based on Case-Based Adaptation. We show how this approach is integrated in a CASE tool suggesting solutions to the software designer. This approach generates new UML designs based on previous ones, which are stored in a central repository. Two different strategies are described and evaluated experimentally.
12511763
Modelling Divergent Production: A multi-domain approach
1 Departamento de Engenharia Informática Universidade de Coimbra Abstract This paper presents an ongoing Ph.D. work on the area of Cognitive Modelling and, more specifically, about computational applications of theories of creativity. Without making claims to psychological views or results related to the mentioned theories, this work is concerned with a search for “different” solutions in a heterogeneous knowledge base composed of structures from a variety of domains. These structures and work upon them, in addition to a computational model of creative production, which is derived from the theory of divergent production [4], form the basis of this work. Its first applicational goal is to implement a system that generates musical ideas recurring to high-level abstractions from other domains (visual arts, story plots, architecture). Part of this has already been implemented and first results obtained. The overall architecture is described in the present paper.
11219736
Combining Case-Based Reasoning and Analogical Reasoning in Software Design
Designers use several types of knowledge and reasoning mechanisms during the creation of new artefacts. In order to cope with this cognitive characteristic of design, an intelligent design tool able to help a designer must integrate several reasoning mechanisms and knowledge formats. Case-based reasoning and analogical reasoning are usually considered as two distinct mechanisms, though they are also considered to be in the same cognitive axis, case-based reasoning being in one extreme, and analogy in the other. Both are important reasoning mechanisms in the generation of new designs, but they both reflect different ways of exploring the design space. In this paper we present a way of combining both techniques, showing how it was integrated in an intelligent software design tool. Experimental results are presented and discussed, showing the advantages and limitations of this approach.
11200577
Plans as Structured Networks of Hierarchically and Temporally Related Case Pieces
This paper describes a representation of plan cases as a structured set of goals and actions. These goals and actions are the unit pieces that form a case. These case pieces are related each other by hierarchical and temporal links (explanations) forming a tree-like network. We give importance not just to explicit links, i.e., links between case pieces which are concretely known, but also to implicit ones, i.e., possibly unknown links between case pieces. Each case piece is explained by antecedent links and explains other case pieces by consequent links. The retrieval of a case piece is mainly guided by its links and by its surrounding case pieces. Our concept of case piece usefulness is briefly explained. We discuss the benefit of reusing and directly accessing small case pieces from multiple cases for improving the Case-Based Reasoning (CBR) systems' capability and efficiency to solve problems. We explain the importance of stepwise refinement in plan cases and also the role that temporal representation can take in the meaningful and coherent construction of planning problem solutions.
9947181
The Influence of Learning in the Evolution of Busy Beavers
The goal of this research is to study how individual learning interacts with an evolutionary algorithm in its search for good candidates for the Busy Beaver problem. Two learning models, designed to act as local search procedures, are proposed. Experimental results show that local search methods that are able to perform several modifications in the structure of an individual in each learning step provide an important advantage. Some insight about the role that evolution and learning play during search is also presented.
16874859
Linear Logic for Meaning Assembly
Semantic theories of natural language associate meanings with utterances by providing meanings for lexical items and rules for determining the meaning of larger units given the meanings of their parts. Meanings are often assumed to combine via function application, which works well when constituent structure trees are used to guide semantic composition. However, we believe that the functional structure of Lexical-Functional Grammar is best used to provide the syntactic information necessary for constraining derivations of meaning in a cross-linguistically uniform format. It has been difficult, however, to reconcile this approach with the combination of meanings by function application. In contrast to compositional approaches, we present a deductive approach to assembling meanings, based on reasoning with constraints, which meshes well with the unordered nature of information in the functional structure. Our use of linear logic as a `glue' for assembling meanings allows for a coherent treatment of the LFG requirements of completeness and coherence as well as of modification and quantification.
8238424
GVR: A New Genetic Representation for the Vehicle Routing Problem
In this paper we analyse a new evolutionary approach to the vehicle routing problem. We present Genetic Vehicle Representation (GVR), a two-level representational scheme designed to deal in an effective way with all the information that candidate solutions must encode. Experimental results show that this method is both effective and robust, allowing the discovery of new best solutions for some well-known benchmarks.
8920330
On the Evolution of Evolutionary Algorithms
In this paper we discuss the evolution of several components of a traditional Evolutionary Algorithm, such as genotype to phenotype mappings and genetic operators, presenting a formalized description of how this can be attained. We then focus on the evolution of mapping functions, for which we present experimental results achieved with a meta-evolutionary scheme.
18592363
Evolving Golomb Rulers
A Golomb Ruler is defined as a ruler that has marks unevenly spaced at integer locations in such a way that the distance between any two marks is unique. Unlike usual rulers, they have the ability to measure more discrete measures than the number of marks they possess. Although the definition of a Golomb Ruler does not place any restriction on the length of the ruler, researchers are usually interested in rulers with minimum length. An Optimal Golomb Ruler (OGR) is defined as the shortest length ruler for a given number of marks [1].