747260
Using CBR for Automation of Software Design Patterns
Software design patterns are used in software engineering as a way to improve and maintain software systems. Patterns are abstract solutions to problem categories, and they describe why, how, and when can a pattern be applied. Their description is based on natural language, which makes the automation of design patterns a difficult task. In this paper we present an approach for automation of design pattern application. We focus on the selection of what pattern to apply, and where to apply it. We follow a Case-Based Reasoning approach, providing a complete framework for pattern application. In our approach cases describe situations for application of patterns.
5517190
A Model for Creativity in Creature Generation
This paper brings a proposal and general specification of a new project that aims to apply Conceptual Blending (Fauconnier and Turner 1998) as a process of creature generation in games. The project we describe is based on Divago (Pereira and Cardoso, 2003 and should be able to bring novelty among creatures that populate a game. Moreover, it is expected to extend these capabilities to other objects in a game, towards a very dynamic environment. Since this is a work in progress, we provide the first preliminary results or experimental examples and try to provide the reader with a clear image of the framework to be followed.
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.
9759378
Noun Sense Disambiguation with WordNet for Software Design Retrieval
Natural language understanding can be used to improve the usability of intelligent Computer Aided Software Engineering (CASE) tools. For a software designer it can be helpful in two ways: a broad range of natural language terms in the naming of software objects, attributes and methods can be used; and the system is able to understand the meaning of these terms so that it could use them in reasoning mechanisms like information retrieval. But, the problem of word sense disambiguation is an obstacle to the development of computational systems that can fully understand natural language. In order to deal with this problem, this paper presents a word sense disambiguation method and how it is integrated with a CASE tool.
11245975
Experiments with free concept generation in Divago
This paper presents a set of experiments we carried out with, Divago, a system that is an attempt to implement our ideas towards a computational model of creativity. It is expected to be able to generate novel concepts out of previous knowledge. Here we show its behaviour with a large dataset constructed independently by other researchers consisting of over 170 nouns (for a project named C^3). Each noun is represented with a syntax that is equivalent to the one adopted for Divago. We apply a two step experimentation procedure, which starts by ''training'' the system with ''preferred outcomes'' and then allowing it to do free generation, constrained by the pragmatic goal of a given query. We evaluate the results and make a short discussion regarding well-defined criteria of novelty and usefulness. We also present a comparison with a similar experiment done with C^3.
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).
43376763
An Artificial Life Model for Information Retrieval in a Distributed Environment
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.
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].
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.
35936505
Finding Manufacturing Expertise Using Ontologies and Cooperative Agents
The new product development process, in its early phases, congregates knowledge from diverse domains and sources, spread among specialists that usually are not aware of each other’s research interests. This work presents a tool designed to make the establishment of new communities or teams easier. The tool organizes their informal vocabulary into formal domain categories, in order to correlate them, and advises its users of potential networks they could belong to. An approach based on ontologies and machine learning is used to structure and make knowledge acquisition / retrieval, together with agents that cooperate and coordinate the access to the knowledge. The tool automatically updates its knowledge base relieving the user from tasks she/he is unfamiliar with. Initial experiments demonstrated the potential of this kind of tool. A test case is being developed encompassing members of a scientific network in the manufacturing area. Results will be analyzed envisaging its broader use and application to different knowledge domains.