7429772
Experiments on Case-Based Retrieval of Software Designs
Software systems are becoming increasingly complex, demanding for more computational resources and better software development methodologies. The software engineer and the CASE tool must work like a team. For this to happen, the CASE tool must be able to understand the user, and to provide new functionalities, such as flexible retrieval of old designs. We think that Case-Based Reasoning can provide a reasoning framework capable of meeting these demands. One important task that a CASE tool based on Case-Based Reasoning can perform adequately, is the retrieval of relevant designs. These designs can be stored in a case library, central to the software development company, thus enabling knowledge sharing through out the company. In this paper we present an approach to case-based retrieval of software designs, and experimental results achieved with this approach.
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.
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.
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.
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.
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).
12781827
On the influence of GVR in vehicle routing
A comparative study is made between a new evolutionary approach for the Vehicle Routing Problem (VRP) and a standard evolutionary model, based on Path Representation. Genetic Vehicle Representation (GVR) is the new two-level representational scheme designed to deal in an effective way with all the information needed by candidate solutions. Experimental results, obtained from a set of VRP instances, show performance improvements when GVR is used.
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].
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.
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.
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.