Depuração de programas baseada em cobertura de integração

Souza, Higor Amario de

doi:10.11606/d.100.2012.tde-08032013-162246

Cited by 1 publication

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“…Eles são calculados em geral com base nas frequências de execução de comandos nos casos de testes. Quanto maior for o número de vezes que um componente for executado por casos de teste que falharam, maioré a probabilidade do defeito estar presente nele (SOUZA, 2012).…”

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Visualização de informação de depuração: uma avaliação experimental

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Debugging is the task of locating and fixing defects in a program. Despite the research effort in debugging, especially in recent years, this task is still carried out in the same way since the 60s when the first symbolic debuggers were introduced. Spectrum-Based Fault Localization (SFL) is a promising debugging technique due to it is relative low execution cost. SFL pinpoints the most suspicious program elements by ranking lines, methods, classes and packages with greater suspicious values. Recently, visualization techniques have been proposed to represent the suspicious values of program elements. However, none of them have been introduced at industrial settings and the use of symbolic debuggers is still prevalent. This dissertation assessed the effectiveness, efficiency and usability of two debugging tools, called and CodeForest and Jaguar, in real environments. Jaguar presents the most suspicious elements of a program in a list sorted by suspicious values. CodeForest receives lists of suspicious classes, methods and blocks (set of statements executed in sequence) to build a three-dimensional cacti forest representing the program inspected. In CodeForest, classes are represented as cacti, methods as branches and blocks as thorns of a branch. In both tools, the program elements receive colors that vary according to the suspicious values. The basic question answered at the end of this research is whether debugging information when displayed as a visual metaphor improve the effectiveness, efficiency and usability during fault localization. The effectiveness and efficiency were assessed, respectively, by the tool's ability to direct the developer to the faulty method or line and the time spent to locate them. The tools' usability was evaluated using the Technology Acceptance Model (TAM). The results show that Jaguar is more effective, efficient and presented greater usability than CodeForest; however, the statistical effect size is insignificant for effectiveness and efficiency and low for usability.

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Visualização de informação de depuração: uma avaliação experimental

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Depuração de programas baseada em cobertura de integração

Cited by 1 publication

References 34 publications

Visualização de informação de depuração: uma avaliação experimental

Visualização de informação de depuração: uma avaliação experimental

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