Métricas de calidad de software

El presente proyecto se desarrolló con el fin de evaluar la calidad de un software aplicando métricas. Para la elaboración del proyecto se hizo una investigación de los métodos de métricas de calidad de software que se ajusten al problema. Teniendo así un consolidado de estos diagnósticos que nos permitió proponer un sistema mediante el cual se hará mención a la medición del software basado en parámetros dados, entre ellos el número de líneas de código o el volumen de documentación asociada. Se utilizará el término indicadores del software. Según las peticiones de los usuarios finales y el aumento de exigencias frente a los productos de software, es preciso utilizar métricas de calidad de software en la fase de desarrollo entonces, es indispensable nuevos métodos de evaluación que dejen saber las apreciaciones de los usuarios.Trabajo de suficiencia profesiona

Reverse Engineering Heterogeneous Applications

Nowadays a large majority of software systems are built using various technologies that in turn rely on different languages (e.g. Java, XML, SQL etc.). We call such systems heterogeneous applications (HAs). By contrast, we call software systems that are written in one language homogeneous applications. In HAs the information regarding the structure and the behaviour of the system is spread across various components and languages and the interactions between different application elements could be hidden. In this context applying existing reverse engineering and quality assurance techniques developed for homogeneous applications is not enough. These techniques have been created to measure quality or provide information about one aspect of the system and they cannot grasp the complexity of HAs. In this dissertation we present our approach to support the analysis and evolution of HAs based on: (1) a unified first-class description of HAs and, (2) a meta-model that reifies the concept of horizontal and vertical dependencies between application elements at different levels of abstraction. We implemented our approach in two tools, MooseEE and Carrack. The first is an extension of the Moose platform for software and data analysis and contains our unified meta-model for HAs. The latter is an engine to infer derived dependencies that can support the analysis of associations among the heterogeneous elements composing HA. We validate our approach and tools by case studies on industrial and open-source JEAs which demonstrate how we can handle the complexity of such applications and how we can solve problems deriving from their heterogeneous nature

Exploring Government Contractor Experiences Assessing and Reporting Software Development Status

Reports from academic, commercial, and government organizations have documented software-intensive system cost and schedule overruns for decades. These reports have identified lack of management insight into the software development process as one of many contributing factors. Multiple management mechanisms exist. However, these mechanisms do not support the assessment, and subsequent reporting, of software completion status. Additionally, the conceptual framework, based on industry standards, is limited in its relevance to this study due to an emphasis on what is needed while deferring implementation details. The purpose of this phenomenological study was to explore U.S. government contractors\u27 lived experiences of assessing and reporting software completion status with current measurement mechanisms. Twenty program or project managers responded to interview questions targeting positive and challenging experiences with current measurement mechanisms. Qualitative analysis of the experiential data was based on open and axial coding conducted on interview transcripts. Analysis indicated that costly resources are applied to metrics that do not provide the required level of management insight into completion status. These findings have positive social change implications for program managers, project managers, and researchers by documenting the need to develop relevant and cost-efficient status metrics to provide the critical insight required by management to reduce overruns