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Software development methods are usually not applied by the book. Companies are under pressure to continuously deploy software products that meet market needs and stakeholders' requests. To implement efficient and effective development processes, companies utilize multiple frameworks, methods and practices, and combine these into hybrid methods. A common combination contains a rich management framework to organize and steer projects complemented with a number of smaller practices providing the development teams with tools to complete their tasks. In this paper, based on 732 data points collected through an international survey, we study the software development process use in practice. Our results show that 76.8% of the companies implement hybrid methods. Company size as well as the strategy in devising and evolving hybrid methods affect the suitability of the chosen process to reach company or project goals. Our findings show that companies that combine planned improvement programs with process evolution can increase their process' suitability by up to 5%., Conference, 10 pages, 4 figures, 10 tables

Context: Although various success stories of model-based approaches are reported in literature, there is still a significant resistance to model-based development in many software organizations because the UML is perceived to be expensive and not necessarily cost-effective. It is also important to gather empirical evidence in which context and under which conditions the UML makes or does not make a practical difference. Objective: Our objective is to provide empirical evidence as to which UML diagrams are more helpful during software maintenance: Forward Designed (FD) UML diagrams or Reverse Engineered (RE) UML diagrams. Method: We carried out a family of experiments which consisted of one experiment and two replications with a total of 169 Computer Science undergraduate students. Results: The individual data analysis and the meta-analysis conducted on the whole family, show a tendency in favor of FD diagrams and are significantly different as regards the effectiveness and efficiency of the subjects who participated and played the role of maintainers. The analysis of the qualitative data, collected using a post-experiment survey, reveals that the subjects did not consider RE diagrams helpful. Conclusions: Our findings show that there are some objective results (descriptive statistics or statistical tests) related to the maintenance effectiveness and efficiency in favor of the use of FD UML diagrams during software maintenance. Subjective opinions also lead us to recommend the use of UML diagrams (especially class diagrams) created during the design phase for software maintenance because they improve the understanding of the system in comparison with RE diagrams. Nevertheless, we can only assume that these results are valid in the context of Computer Science undergraduate students when working with small systems related to well-known domains, and other contexts should be explored in order to reaffirm the results in an industrial context by carrying out replications with professionals. Ministerio de Economía y Competitividad TIN2012-37493-C03-01

This paper presents the results of an empirical study aiming at comparing the support provided by ER and UML class diagrams during maintenance of data models. We performed one controlled experiment and two replications that focused on comprehension activities (the first activity in the maintenance process) and another controlled experiment on modification activities related to the implementation of given change requests. The results achieved were analyzed at a fine-grained level aiming at comparing the support given by each single building block of the two notations. Such an analysis is used to identify weaknesses (i.e., building blocks not easy to comprehend) in a notation and/or can justify the need of preferring ER or UML for data modeling. The analysis revealed that the UML class diagrams generally provided a better support for both comprehension and modification activities performed on data models as compared to ER diagrams. Nevertheless, the former has some weaknesses related to three building blocks, i.e., multi-value attribute, composite attribute, and weak entity. These findings suggest that an extension of UML class diagrams should be considered to overcome these weaknesses and improve the support provided by UML class diagrams during maintenance of data models.

[EN] Context: The conventional wisdom states that stereotypes are used to clarify or extend the meaning of model elements and consequently should be helpful in comprehending the diagram semantics. Objective: The main goal of this work is to present a family of experiments that we have carried out to investigate whether the use of stereotypes improves the comprehension of UML sequence diagrams. Method: The family of experiments consists of an experiment and two replications carried out with 78, 29 and 36 undergraduate Computer Science students, respectively. The comprehension of UML sequence diagrams with and without stereotypes was analyzed from three different perspectives borrowed from the Cognitive Theory of Multimedia Learning (CTML): semantic comprehension, retention and transfer. In addition, we carried out a meta-analysis study to integrate the different data samples. Results: The statistical analysis and meta-analysis of the data obtained from each experiment separately indicates that the use of the proposed stereotypes helps improving the comprehension of the diagrams, especially when the subjects are not familiar with the domain. Conclusions: The set of stereotypes presented in this work seem to be helpful for a better comprehension of UML sequence diagrams, especially with not well-known domains. Although further research is necessary for strengthening these results, introducing these stereotypes both in academia and industry could be an interesting practice for checking the validity of the results, This research is part of the following projects: "MEDUSAS (IDI-20090557)" and "Proyecto Integrado ORIGIN (IDI-2010043(1-5))" financed by CDTI and FEDER; "ECCOO (TRA2009_0074)", "MAGO/PEGASO (TIN2009-13718)" and "MULTIPLE (TIN2009-13838)" financed by MICINN; MECCA (PI12109-0075-8394) and IMPACTUM (PEII11-0330-4414) financed by JCCM and CALIMO funded by the Generalitat Valenciana.

Numerous methods and techniques have been proposed for requirements modeling, although very few have had widespread use in practice. One drawback of requirements modeling methods is that they lack proper empirical evaluations. This means that there is a need for evaluation methods that consider both the theoretical and practical aspects of this type of methods and techniques. In this paper, we present a method for evaluating the quality of requirements modeling methods based on user perceptions. The evaluation method consists of a theoretical model that explains the relevant dimensions of quality for requirements modeling methods, along with a practical instrument with which to measure these quality dimensions. Basically, it allows us to predict the acceptance of a particular requirements modeling method in practice, based on the effort of applying the method, the quality of the requirements artifacts produced, and the user perceptions with regard to the quality of the method. The paper also presents an empirical test of the proposed method for evaluating a Rational Unified Process (RUP) extension for requirements modeling. That test was carried out through a family of experiments conducted with students and practitioners and provides evidence of the usefulness of the evaluation method proposed. © 2011 Elsevier Inc. All rights reserved., This research has been funded by the following projects: MULTIPLE (MICINN TIN2009-13838), MEDUSAS (CDTI-MICINN and FEDER IDI-20090557), ORIGIN (CDTI-MICINN and FEDER IDI-2010043(1-5)), PEGASO/MAGO (MICINN and FEDER, TIN2009-13718-C02-01), EECCOO (MICINN TRA2009_0074), MECCA (JCMM PII2109-0075-8394) and IMPACTUM (JCCM PEII11-0330-4414).

International audience; MOF and OCL are commonly used for metamodeling: MOF to model the domain structure, and OCL for the well-formedness rules. Thus, metamodelers have to master both formalisms and understand how to articulate them in order to build metamodels that accurately capture domain knowledge. A systematic empirical analysis of the conjunct use of MOF and OCL in existing metamodels could help metamodelers un- derstand how to use these formalisms. However, existing metamodels usually present anomalies that prevent automatic analysis without prior fixing. In particular, it often happens that both parts of the metamodel (MOF and OCL) are inconsistent. In this paper, we propose a process for analyzing metamodels and we report on the pre-processing phase we went through on 52 metamodels in order to get them ready for automatic empirical analysis.