Empirical studies on fine-grained feature dependencies

• Ano de defesa: 2015
• Autor(a) principal: Gonzaga Júnior, Iran Rodrigues
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Alagoas; Brasil; Programa de Pós-Graduação em Informática; UFAL
• Palavras-chave em Português: Engenharia de software; Computadores e família; Software engineering; Computers and family; CNPQ::CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO
• Link de acesso: http://www.repositorio.ufal.br/handle/riufal/1724

Maintaining program families is not a trivial task. Developers commonly introduce bugs when they do not consider existing dependencies among features. When such implementations share program elements, such as variables and functions, inadvertently using these elements may result in bugs. In this context, previous work focuses only on the occurrence of intraprocedural dependencies, that is, when features share program elements within a function. But at the same time, we still lack studies investigating dependencies that transcend the boundaries of a function, since these cases might cause bugs as well. Indeed, in this work we bring evidence that variability bugs can also occur due to interprocedural dependencies and global variables. To assess to what extent these different types of feature dependencies exist in practice, we perform an empirical study covering 40 program families of different domains and sizes. Our results show that the intraprocedural and interprocedural feature dependencies are common in practice: 51:44% 17:77% of functions with preprocessor directives have intraprocedural dependencies, while 25:98% 19:99% of all functions have interprocedural dependencies. After studying the feature dependencies occurrence in practice, we perform another empirical study now focusing on finding actual bugs related to feature dependencies. Here we focus on undeclared variables, undeclared functions, unused variables, and unused functions. This study uses 15 systems to answer research questions related to how developers introduce these bugs and their frequency. We detect and confirm 32 variability bugs. The corpus of bugs we gather is a valuable source to ground research on this topic and to help tool developers, so they can provide means in their tools to avoid these problems.