Avaliando a robustez e manutenibilidade do comportamento excepcional de aplicações C#

• Autor(a) principal: Sousa Neto, Eliezio Soares de
• Data de Publicação: 2014
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFRN
• Texto Completo: https://repositorio.ufrn.br/jspui/handle/123456789/18103
• topic: Sistemas de Software. Qualidade. Tratamento de exceções. Mecanismos de tratamento de exceções. Robustez. Manutenibilidade.; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO::SISTEMAS DE COMPUTACAO

Mainstream programming languages provide built-in exception handling mechanisms to support robust and maintainable implementation of exception handling in software systems. Most of these modern languages, such as C#, Ruby, Python and many others, are often claimed to have more appropriated exception handling mechanisms. They reduce programming constraints on exception handling to favor agile changes in the source code. These languages provide what we call maintenance-driven exception handling mechanisms. It is expected that the adoption of these mechanisms improve software maintainability without hindering software robustness. However, there is still little empirical knowledge about the impact that adopting these mechanisms have on software robustness. This work addresses this gap by conducting an empirical study aimed at understanding the relationship between changes in C# programs and their robustness. In particular, we evaluated how changes in the normal and exceptional code were related to exception handling faults. We applied a change impact analysis and a control flow analysis in 100 versions of 16 C# programs. The results showed that: (i) most of the problems hindering software robustness in those programs are caused by changes in the normal code, (ii) many potential faults were introduced even when improving exception handling in C# code, and (iii) faults are often facilitated by the maintenance-driven flexibility of the exception handling mechanism. Moreover, we present a series of change scenarios that decrease the program robustness