Percorrer por autor "Fernandéz de Vega, Francisco"
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- An evolutionary approach for performing structural unit-testing on third-party object-oriented Java softwarePublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Fernandéz de Vega, FranciscoEvolutionary Testing is an emerging methodology for automatically generating high quality test data. The focus of this paper is on presenting an approach for generating test cases for the unit-testing of object-oriented programs, with basis on the information provided by the structural analysis and interpretation of Java bytecode and on the dynamic execution of the instrumented test object. The rationale for working at the bytecode level is that even when the source code is unavailable, insight can still be obtained and used to guide the search-based test case generation process. Test cases are represented using the Strongly Typed Genetic Programming paradigm, which effectively mimics the polymorphic relationships, inheritance dependences and method argument constraints of object-oriented programs.
- Automatic evolution of programs for procedural generation of terrains for video games: accessibility and edge length constraintsPublication . Frade, Miguel; Fernandéz de Vega, Francisco; Cotta, CarlosNowadays the video game industry is facing a big challenge: keep costs under control as games become bigger and more complex. Creation of game content, such as character models, maps, levels, textures, sound effects and so on, represent a big slice of total game production cost. Hence, the video game industry is increasingly turning to procedural content generation to amplify the cost-effectiveness of the efforts of video game designers. However, procedural methods for automated content generation are difficult to create and parametrize. In this work we study a Genetic Programming based procedural content technique to generate procedural terrains that do not require parametrization, thus, allowing to save time and help reducing production costs. Generated procedural terrains present aesthetic appeal; however, unlike most techniques involving aesthetic, our approach does not require a human to perform the evaluation. Instead, the search is guided by the weighted sum of two morphological metrics: terrain accessibility and obstacle edge length. The combination of the two metrics allowed us to find a wide range of fit terrains that present more scattered obstacles in different locations, than our previous approach with a single metric. Procedural terrains produced by this technique are already in use in a real video game.
- Breeding terrains with genetic terrain programming: the evolution of terrain generatorsPublication . Frade, Miguel; Fernandéz de Vega, Francisco; Cotta, CarlosAlthough a number of terrain generation techniques have been proposed during the last few years, all of them have some key constraints. Modelling techniques depend highly upon designer’s skills, time, and effort to obtain acceptable results, and cannot be used to automatically generate terrains. The simpler methods allow only a narrow variety of terrain types and offer little control on the outcome terrain. The Genetic Terrain Programming technique, based on evolutionary design with Genetic Programming, allows designers to evolve terrains according to their aesthetic feelings or desired features. This technique evolves Terrain Programmes (TPs) that are capable of generating a family of terrains—different terrains that consistently present the same morphological characteristics. This paper presents a study about the persistence of morphological characteristics of terrains generated with different resolutions by a given TP. Results show that it is possible to use low resolutions during the evolutionary phase without compromising the outcome, and that terrain macrofeatures are scale invariant.
- eCrash: a framework for performing evolutionary testing on third-party Java componentsPublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Fernandéz de Vega, FranciscoThe focus of this paper is on presenting a tool for generating test data by employing evolutionary search techniques, with basis on the information provided by the structural analysis and interpretation of the Java bytecode of third-party Java components, and on the dynamic execution of the instrumented test object. The main objective of this approach is that of evolving a set of test cases that yields full structural code coverage of the test object. Such a test set can be used for effectively performing the testing activity, providing confidence in the quality and robustness of the test object. The rationale of working at the bytecode level is that even when the source code is unavailable structural testing requirements can still be derived, and used to assess the quality of a test set and to guide the evolutionary search towards reaching specific test goals.
- Genetic terrain programming: an aesthetic approach to terrain generationPublication . Frade, Miguel; Fernandéz de Vega, Francisco; Cotta, CarlosNowadays there are a wide range of techniques for terrain generation, but are focused on providing realistic terrains often neglecting the aesthetic appeal. The Genetic Terrain Programming technique, based on evolutionary design with Genetic Programming, allows designers to evolve terrains according to their aesthetic feelings or desired features. This technique evolves TPs (Terrain Programmes) that are capable of generating different terrains, but consistently with the same features. This paper presents a study about the perseverance of terrain features of the TPs across different LODs (Levels Of Detail). Results showed it is possible to use low LODs during the evolutionary phase without compromising results and the terrain features generated by a TPs are scale invariant.
- GenTP: uma ferramenta interactiva para a geração artificial de terrenosPublication . Frade, Miguel; Fernandéz de Vega, Francisco; Cotta, CarlosActualmente existe uma grande variedade de técnicas de geração artificial de terrenos. No entanto todas elas estão focadas em fornecer terrenos de aspecto realista, negligenciando por vezes a estética e a criatividade. Este artigo apresenta uma ferramenta interactiva para a geração artificial de terrenos, designada GenTP, inspirada nos sistemas de arte evolutiva com programação genética. Esta ferramenta permite aos designers evoluir TPs (Terrain Programs) de acordo com o seu sentido estético ou características desejadas. Os TPs, o produto desta ferramenta, geram terrenos diferentes a cada execução, mas sempre coerentes nas sua características morfológicas.
- Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic MaskPublication . Miragaia, Rolando; Reis, Gustavo; Fernandéz de Vega, Francisco; Chávez, FranciscoPiano notes recognition, or pitch estimation of piano notes has been a popular research topic for many years, and is still investigated nowadays. It is a fundamental task during the process of automatic music transcription (extracting the musical score from an acoustic signal). We take advantage of Cartesian Genetic Programming (CGP) to evolve mathematical functions that act as independent classifiers for piano notes. These classifiers are then used to identify the presence of piano notes in polyphonic audio signals. This paper describes our technique and the latest improvements made in our research. The main feature is the introduction of spectral harmonic masks in the binarization process for measuring the fitness values that has allowed to improve the classification rate: 10% in the F-measure mean result. Our system architecture is also described to show the feasibility of its parallelization, which will reduce the computing time.
- A strategy for evaluating feasible and unfeasible test cases for the evolutionary testing of object-oriented softwarePublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Fernandéz de Vega, FranciscoEvolutionary Testing is an emerging methodology for automatically producing high quality test data. The focus of our on-going work is precisely on generating test data for the structural unit-testing of object-oriented Java programs. The primary objective is that of efficiently guiding the search process towards the definition of a test set that achieves full structural coverage of the test object. However, the state problem of object-oriented programs requires specifying carefully fine-tuned methodologies that promote the traversal of problematic structures and difficult control-flow paths - which often involves the generation of complex and intricate test cases, that define elaborate state scenarios. This paper proposes a methodology for evaluating the quality of both feasible and unfeasible test cases - i.e., those that are effectively completed and terminate with a call to the method under test, and those that abort prematurely because a runtime exception is thrown during test case execution. With our approach, unfeasible test cases are considered at certain stages of the evolutionary search, promoting diversity and enhancing the possibility of achieving full coverage.
- Strongly-typed genetic programming and purity analysis: input domain reduction for evolutionary testing problemsPublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Fernandéz de Vega, FranciscoSearch-based test case generation for object-oriented software is hindered by the size of the search space, which encompasses the arguments to the implicit and explicit parameters of the test object's public methods. The performance of this type of search problems can be enhanced by the definition of adequate Input Domain Reduction strategies. The focus of our on-going work is on employing evolutionary algorithms for generating test data for the structural unit-testing of Java programs. Test cases are represented and evolved using the Strongly-Typed Genetic Programming paradigm; Purity Analysis is particularly useful in this situation because it provides a means to automatically identify and remove Function Set entries that do not contribute to the definition of interesting test scenarios.
- Using dynamic analysis of Java bytecode for evolutionary object-oriented unit testingPublication . Ribeiro, José Carlos Bregieiro; Zenha-Rela, Mário Alberto; Fernandéz de Vega, FranciscoThe focus of this paper is on presenting a methodology for generating and optimizing test data by employing evolutionary search techniques, with basis on the information provided by the analysis and interpretation of Java bytecode and on the dynamic execution of the instrumented test object. The main reason to work at the bytecode level is that even when the source code is unavailable, structural testing requirements can still be derived and used to assess the quality of a given test set and to guide the evolutionary search towards reaching specific test goals. Java bytecode retains enough high-level information about the original source code for an underlying model for program representation to be built. The observations required to select or generate test data are obtained by employing dynamic analysis techniques – i.e. by instrumenting, tracing and analysing Java bytecode.