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The last decade marked the first real attempt to turn software development into engineering through the concepts of ComponentBased Software Development (CBSD) and Commercial Off-The-Shelf (COTS) components, with the goal of creating high-quality parts that could be joined together to form a functioning system. One of the most critical processes in CBSD is the selection of a set of software components from in-house or external repositories that fulfil some architectural and user-defined requirements. However, there is a lack of quality models and metrics that can help evaluate the quality characteristics of software components during this selection process. This paper presents a set of measures to assess the Usability of software components, and describes the method followed to obtain and validate them. Such a method can be re-used as a pattern for defining and validating measures for further quality characteristics.

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Ontologies are frequently used in the context of software and technology engineering. These can be grouped into two main categories, depending on whether they are used to describe the knowledge of a domain (domain ontologies) or whether they are used as software artifacts in software development processes. This paper presents some experiences and lessons learnt from the effective use of an ontology for Software Measurement, called software measurement ontology (SMO). The SMO was developed some years ago as a result of a thorough analysis of the software measurement domain. Its use as a domain ontology is presented first, a description of how the SMO can serve as a conceptual basis for comparing international standards related to software measurement. Second, the paper describes several examples of the applications of SMO as a software artifact. In particular, we show how the SMO can be instantiated to define a data quality model for Web portals, and also how it can be used to define a Domain-Specific Language (DSL) for measuring software entities. These examples show the significant role that ontologies can play as software artifacts in the realm of model-driven engineering and domain-specific modeling.

The correct representation of the relevant properties of a system is an essential requirement for the effective use and wide adoption of model-based practices in industry. Uncertainty is one of the inherent properties of any measurement or estimation that is obtained in any physical setting; as such, it must be considered when modeling software systems that deal with real data. Although a few modeling languages enable the representation of measurement uncertainty, these aspects are not normally incorporated into their type systems. Therefore, operating with uncertain values and propagating their uncertainty become cumbersome processes, which hinder their realization in real environments. This paper proposes an extension of OCL/UML primitive datatypes that enables the representation of the uncertainty that comes from physical measurements or user estimates into the models, together with an algebra of operations that are defined for the values of these types.

Resumen-La última década ha marcado el primer intento real de convertir el desarrollo software en una ingeniería usando los conceptos de Desarrollo Software Basado en Componentes (DSBC) y de Componentes COTS (Commercial Off-The-Shelf) cuyo objetivo es crear elementos de alta calidad que se puedan ensamblar para construir un sistema funcional. Uno de los procesos críticos dentro del DSBC es la selección de los componentes que, cumpliendo los requisitos de funcionalidad definidos por el usuario, formarán parte del producto final. Sin embargo, existe una falta de modelos de calidad y de medidas que ayuden en la evaluación de las características de calidad de los componentes software durante este proceso de selección. Este trabajo presenta un conjunto de medidas para valorar la Usabilidad de los componentes COTS, y describe el método seguido para obtenerlas y validarlas empíricamente.Palabras clave-Software Metrics, Software Quality.

Uncertainty is an inherent property of any measure or estimation performed in any physical setting, and therefore it needs to be considered when modeling systems that manage real data. Although several modeling languages permit the representation of measurement uncertainty for describing certain system attributes, these aspects are not normally incorporated into their type systems. Thus, operating with uncertain values and propagating uncertainty are normally cumbersome processes, difficult to achieve at the model level. This paper proposes an extension of OCL and UML datatypes to incorporate data uncertainty coming from physical measurements or user estimations into the models, along with the set of operations defined for the values of these types.

This paper provides a comprehensive overview and analysis of research work on how uncertainty is currently represented in software models. The survey presents the definitions and current research status of different proposals for addressing uncertainty modeling, and introduces a classification framework that allows to compare and classify existing proposals, analyse their current status and identify new trends. In addition, we discuss possible future research directions, opportunities and challenges.A fundamental characteristic of software models is their ability to represent the relevant characteristics of the system under study, at the appropriate level of abstraction. Software models were initially conceived to design and develop general Information Technology (IT) systems, such as financial applications, enterprise databases or component-based systems, and have proven to be excellent artefacts for representing the basic structure and