José Luís Ferreira

The importance of retrieval in creative design analogies

Analogy is an important reasoning process in creative design. It enables the generation of new design artifacts using ideas from semantically distant domains. Candidate selection is a crucial process in the generation of creative analogies. Without a good set of candidate sources, the success of subsequent phases can be compromised. Two main types of selection have been identified: semantics-based retrieval and structure-based retrieval. This paper presents an empirical study on the importance of the analogy retrieval strategy in the domain of software design. We argue that both types of selection are important, but they play different roles in the process.

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.

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.

Precompetitive Anxiety and Self-Confidence in Athletes with Disability

This study examined the precompetition temporal patterning of competitive anxiety components in 42 athletes with disability who participated at the national level and at the national trials for the Paralympic Games in a variety of sports. All subjects completed a modified version of the Competitive State Anxiety Inventory-2 which measures intensity and direction of the competitive anxiety response on three occasions before competition (1 wk., 2 hr., and 20 min.). Analysis suggested that for cognitive and somatic dimensions athletes with disabilities show a similar precompetition anxiety response to athletes without disability. However, there appear to be some differences, particularly in the intensity of self-confidence, as athletes with disability reported a reduction of self-confidence just prior to competition.

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.

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 systems 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).

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.

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.

REBUILDER: A CBR Approach to Knowledge Management in Software Design

Knowledge generated during the software development process can be a valuable asset for a software company. But in order to take advantage of this knowledge, the company must be able to store this knowledge for later use, which can be achieved through the use of knowledge management tools. This paper provides an overview of a computational system for management and reuse of software design knowledge. We present a Case-Based Reasoning approach combined with a lexical resource: WordNet. We explain how knowledge management is performed and how is the stored knowledge reused.

MACHINE LEARNING GOES TO THE BANK

This paper describes how the APT system has been applied to loan analysis to generalized and refine the knowledge previously used by an expert system, in order to increase the efficiency and the compactness of the decision rule base. The decision to lend money to industrial companies is a complex and risky activity for financial institutions. They need much expertise to deal with the large amount of information that has to be considered for this process, and the analysis must be carefully done in order to avoid misjudgments that would result in severe losses of unrecoverable credit. An expert system named SPAC had been developed to deal with this task without fulfilling the users expectations. This paper presents the drawbacks of SPACs approach and how APT, an integrated machine learning system, has been used to acquire and refine domain knowledge and general decision rules from basic descriptions of cases provided by SPAC. The learning methodology is detailed, and a complete example of a learning session with APT is given. The final results are then compared with those obtained with SPAC