Context: Replication plays an important role in experimental disciplines. There are still many uncertain-ties about how to proceed with replications of SE experiments. Should replicators reuse the baseline experiment materials? How much liaison should there be among the original and replicating experiment-ers, if any? What elements of the experimental configuration can be changed for the experiment to be considered a replication rather than a new experiment? Objective: To improve our understanding of SE experiment replication, in this work we propose a classi-fication which is intend to provide experimenters with guidance about what types of replication they can perform. Method: The research approach followed is structured according to the following activities: (1) a litera-ture review of experiment replication in SE and in other disciplines, (2) identification of typical elements that compose an experimental configuration, (3) identification of different replications purposes and (4) development of a classification of experiment replications for SE. Results: We propose a classification of replications which provides experimenters in SE with guidance about what changes can they make in a replication and, based on these, what verification purposes such a replication can serve. The proposed classification helped to accommodate opposing views within a broader framework, it is capable of accounting for less similar replications to more similar ones regarding the baseline experiment. Conclusion: The aim of replication is to verify results, but different types of replication serve special ver-ification purposes and afford different degrees of change. Each replication type helps to discover partic-ular experimental conditions that might influence the results. The proposed classification can be used to identify changes in a replication and, based on these, understand the level of verification.

Context: Families of experiments (i.e., groups of experiments with the same goal) are on the rise in Software Engineering (SE). Selecting unsuitable aggregation techniques to analyze families may undermine their potential to provide in-depth insights from experiments' results. Objectives: Identifying the techniques used to aggregate experiments' results within families in SE. Raising awareness of the importance of applying suitable aggregation techniques to reach reliable conclusions within families. Method: We conduct a systematic mapping study (SMS) to identify the aggregation techniques used to analyze families of experiments in SE. We outline the advantages and disadvantages of each aggregation technique according to mature experimental disciplines such as medicine and pharmacology. We provide preliminary recommendations to analyze and report families of experiments in view of families' common limitations with regard to joint data analysis. Results: Several aggregation techniques have been used to analyze SE families of experiments, including Narrative synthesis, Aggregated Data (AD), Individual Participant Data (IPD) mega-trial or stratified, and Aggregation of p-values. The rationale used to select aggregation techniques is rarely discussed within families. Families of experiments are commonly analyzed with unsuitable aggregation techniques according to the literature of mature experimental disciplines. Conclusion: Data analysis' reporting practices should be improved to increase the reliability and transparency of joint results. AD and IPD stratified appear to be suitable to analyze SE families of experiments.

Experiment replication is a key component of the scientific paradigm. The purpose of replication is to verify previously observed findings. Although some Software Engineering (SE) experiments have been replicated, yet, there is still disagreement about how replications should be run in our field. With the aim of gaining a better understanding of how replications are carried out, this paper examines different replication types in other scientific disciplines. We believe that by analysing the replication types proposed in other disciplines it is possible to clarify some of the question marks still hanging over experimental SE replication.

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Software regression testing techniques verify previous functionalities each time software modifications occur or new characteristics are added. With the aim of gaining a better understanding of this subject, in this work we present a survey of software regression testing techniques applied in the last 15 years; taking into account its application domain, kind of metrics they use, its application strategies and the phase of the software development process where they are applied. From an outcome of 460 papers, a set of 25 papers describing the use of 31 software testing regression techniques were identified. Results of this survey suggest that at the time of applying a regression testing techniques, metrics like cost and fault detection efficiency are the most relevant. Most of the techniques were assessed with instrumented programs (experimental cases) under academic settings. Conversely, we observe a minimum set of software regression techniques applied in industrial settings, mainly, under corrective and maintenance approaches. Finally, we observe a trend using some regression techniques under agile approaches.

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Resumen-Este trabajo presenta la aplicación de un protocolo para revisiones sistemáticas de Ingeniería de Software. En este artículo el protocolo es utilizado como un modelo formal aplicado a la búsqueda de publicaciones relacionadas con las adaptaciones SPI llevadas a cabo en MiPyMEs desarrolladoras de software, en el período comprendido de 1995 a diciembre de 2013, centrándose en tendencias, países, y sectores que publican, así como en los modelos, metodologías, estándares y procesos de soporte del software del área de calidad. Los resultados obtenidos sugieren que en la comunidad de Ingeniería de Software hay un interés creciente en este tema, por ejemplo, la mayoría de las investigaciones realizadas surgen en el sector educativo. El modelo de procesos y la metodología más utilizada es CMMi y Xtreme Programing, respectivamente. El estándar más utilizado es el ISO/ IEC 15504 y el proceso de soporte del software del ciclo de vida del software mayormente abordado es SQA.

Abstract:Materials with new visual appearances have emerged over the last few years. In the automotive industry in particular, there is a growing interest in materials with new effect finishes, such as metallic, pearlescent, sparkle and graininess effects. Typically for solid colors the mean of the three measurements with repetitions it is enough for obtaining a representative measurement of the color characterization. But gonio-apparent samples are colors not homogeneous and there are not studies that recommend the minimal number of repetitions for color, sparkle and graininess characterization in this type of panels. We suppose that the color panels incorporating special-effect pigments in their color recipes will require a higher minimum number of measurements than solid color panels. Therefore the purpose of this study is to confirm this by using a multiangle spectrophotometer BYK-mac, given that it is currently the only commercial device that can measure color, sparkle and graininess values simultaneously. In addition, this paper shows a possible methodology for assessing the minimum number of measurements when characterising gonio-apparent materials using a specific instrument. Thus, we studied the minimum number of measurements needed to characterize the color, sparkle and graininess of three types of samples with solid, metallic and http://mc.manuscriptcentral.com/cte Coloration Technology