Applying model-driven paradigm: CALIPSOneo experience

Model-Driven Engineering paradigm is being used by the research community in the last years, obtaining suitable results. However, there are few practical experiences in the enterprise field. This paper presents the use of this paradigm in an aeronautical PLM project named CALIPSOneo currently under development in Airbus. In this context, NDT methodology was adapted as methodology in order to be used by the development team. The paper presents this process and the results that we are getting from the project. Besides, some relevant learned lessons from the trenches are concluded.Ministerio de Ciencia e Innovación TIN2010-20057-C03-02Junta de Andalucía TIC-578

Defining and validating a multimodel approach for product architecture derivation and improvement

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-41533-3_24Software architectures are the key to achieving the non-functional requirements (NFRs) in any software project. In software product line (SPL) development, it is crucial to identify whether the NFRs for a specific product can be attained with the built-in architectural variation mechanisms of the product line architecture, or whether additional architectural transformations are required. This paper presents a multimodel approach for quality-driven product architecture derivation and improvement (QuaDAI). A controlled experiment is also presented with the objective of comparing the effectiveness, efficiency, perceived ease of use, intention to use and perceived usefulness with regard to participants using QuaDAI as opposed to the Architecture Tradeoff Analysis Method (ATAM). The results show that QuaDAI is more efficient and perceived as easier to use than ATAM, from the perspective of novice software architecture evaluators. However, the other variables were not found to be statistically significant. Further replications are needed to obtain more conclusive results.This research is supported by the MULTIPLE project (MICINN TIN2009-13838) and the Vali+D fellowship program (ACIF/2011/235).González Huerta, J.; Insfrán Pelozo, CE.; Abrahao Gonzales, SM. (2013). Defining and validating a multimodel approach for product architecture derivation and improvement. En Model-Driven Engineering Languages and Systems. Springer. 388-404. https://doi.org/10.1007/978-3-642-41533-3_24S388404Ali-Babar, M., Lago, P., Van Deursen, A.: Empirical research in software architecture: opportunities, challenges, and approaches. 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Architecture for Provenance Systems

This document covers the logical and process architectures of provenance systems. The logical architecture identifies key roles and their interactions, whereas the process architecture discusses distribution and security. A fundamental aspect of our presentation is its technology-independent nature, which makes it reusable: the principles that are exposed in this document may be applied to different technologies

Automatic allocation of safety requirements to components of a software product line

Safety critical systems developed as part of a product line must still comply with safety standards. Standards use the concept of Safety Integrity Levels (SILs) to drive the assignment of system safety requirements to components of a system under design. However, for a Software Product Line (SPL), the safety requirements that need to be allocated to a component may vary in different products. Variation in design can indeed change the possible hazards incurred in each product, their causes, and can alter the safety requirements placed on individual components in different SPL products. Establishing common SILs for components of a large scale SPL by considering all possible usage scenarios, is desirable for economies of scale, but it also poses challenges to the safety engineering process. In this paper, we propose a method for automatic allocation of SILs to components of a product line. The approach is applied to a Hybrid Braking System SPL design

The Feature-Architecture Mapping Method for Feature-Oriented Development of Software Product Lines

Software Produktlinien sind die Antwort von Software Engineering auf die zu-nehmende Komplexität und kürzerenProdukteinführungszeiten von heutigen Softwaresystemen. Nichtsdestotrotz erfordern Software Produktlinien einefortgeschrittene Wartbarkeit und hohe Flexibilität. Das kann durch die angemessene Trennung der Belange erreicht werden.Merkmale stellen die Hauptbelange im Kontext von Software Produktlinien dar. Demzufolge sollte ein Merkmal idealerweise ingenau einer Architekturkomponente implementiert werden. In der Praxis ist das jedoch nicht immer machbar. Deshalb solltezumindest ein starkes Mapping zwischen Merkmalen und der Architektur bestehen. Die Methoden zur Entwicklung von SoftwareProduktlinien, die dem Stand der Technik entsprechen, führen zu bedeutender Verstreutheit und Vermischung von Merkmalen. Indieser Arbeit wird die Feature-Architecture Mapping (FArM) Methode entwickelt, um ein stärkeres Mapping zwischen Merkmalenund der Produktlinien-Architektur zu erzielen. Der Input für FArM besteht in einem initialen Merkmalmodell, das anhand einerMethode zur Domänenanalyse erstellt wurde. Dieses initiale Merkmalmodell wird einer Serie von Transformationen unterzogen.Die Transformationen streben danach, ein Gleichgewicht zwischen der Sichtweise von Kunden und Softwarearchitekteneinzustellen. Die Merkmalinteraktionen werden während der Transformationen ausdrücklich optimiert. Von jedem Merkmal destransformierten Merkmalmodells wird eine Architekturkomponente abgeleitet. Die Architekturkomponenten implementieren dieApplikationslogik der entsprechenden Merkmale. Die Kommunikation zwischen den Komponenten spiegelt die Interaktion zwischenden Merkmalen wider. Dieser Ansatz führt im Vergleich zu den Produktlinien-Entwicklungsmethoden des Stands der Technik zueinem stärkeren Mapping zwischen Merkmalen und der Architektur und zu einer höheren Variabilität auf Merkmalebene. DieseEigenschaften haben eine bessere Wartbarkeit und eine vereinfachte generative Produktinstanzierung zur Folge, was wiederumdie Flexibilität der Produktlinien steigert. FArM wurde durch ihre Anwendung in einigen Domänen evaluiert, z.B. in denDomänen von Mobiltelefonen und Integrierten Entwicklungsumgebungen (IDEs). Diese Arbeit wird FArM anhand einer Fallstudie inder Domäne von Künstlichen Neuronalen Netzwerken präsentieren.Software product lines are the answer of software engineering to the increasing complexity and shorter time-to-market ofcontemporary software systems. Nonetheless, software product lines demand for advanced maintainability and high flexibility.The latter can be achieved through the proper separation of concerns. Features pose the main concerns in the context ofsoftware product lines. Consequently, one feature should ideally be implemented into exactly one architectural component. Inpractice, this is not always feasible. Therefore, at least a strong mapping between features and the architecture mustexist. The state of the art product line development methodologies introduce significant scattering and tangling offeatures. In this work, the Feature-Architecture Mapping (FArM) method is developed, to provide a stronger mapping betweenfeatures and the product line architecture. FArM receives as input an initial feature model created by a domain analysismethod. The initial feature model undergoes a series of transformations. The transformations strive to achieve a balancebetween the customer and architectural perspectives. Feature interaction is explicitly optimized during the feature modeltransformations. For each feature of the transformed feature model, one architectural component is derived. Thearchitectural components implement the application logic of the respective features. The component communication reflectsthe feature interaction. This approach, compared to the state of the art product line methodologies, allows a strongerfeature-architecture mapping and for higher variability on the feature level. These attributes provide highermaintainability and an improved generative approach to product instantiation, which in turn enhances product lineflexibility. FArM has been evaluated through its application in a number of domains, e.g in the mobile phone domain and theIntegrated Development Environment (IDE) domain. This work will present FArM on the basis of a case study in the domain ofartificial Neural Networks

Validating a model-driven software architecture evaluation and improvement method: A family of experiments

Context: Software architectures should be evaluated during the early stages of software development in order to verify whether the non-functional requirements (NFRs) of the product can be fulfilled. This activity is even more crucial in software product line (SPL) development, since it is also necessary to identify whether the NFRs of a particular product can be achieved by exercising the variation mechanisms provided by the product line architecture or whether additional transformations are required. These issues have motivated us to propose QuaDAI, a method for the derivation, evaluation and improvement of software architectures in model-driven SPL development. Objective: We present in this paper the results of a family of four experiments carried out to empirically validate the evaluation and improvement strategy of QuaDAI. Method: The family of experiments was carried out by 92 participants: Computer Science Master s and undergraduate students from Spain and Italy. The goal was to compare the effectiveness, efficiency, perceived ease of use, perceived usefulness and intention to use with regard to participants using the evaluation and improvement strategy of QuaDAI as opposed to the Architecture Tradeoff Analysis Method (ATAM). Results: The main result was that the participants produced their best results when applying QuaDAI, signifying that the participants obtained architectures with better values for the NFRs faster, and that they found the method easier to use, more useful and more likely to be used. The results of the meta-analysis carried out to aggregate the results obtained in the individual experiments also confirmed these results. Conclusions: The results support the hypothesis that QuaDAI would achieve better results than ATAM in the experiments and that QuaDAI can be considered as a promising approach with which to perform architectural evaluations that occur after the product architecture derivation in model-driven SPL development processes when carried out by novice software evaluators.The authors would like to thank all the participants in the experiments for their selfless involvement in this research. This research is supported by the MULTIPLE Project (MICINN TIN2009-13838) and the ValI+D Program (ACIF/2011/235).González Huerta, J.; Insfrán Pelozo, CE.; Abrahao Gonzales, SM.; Scanniello, G. (2015). Validating a model-driven software architecture evaluation and improvement method: A family of experiments. Information and Software Technology. 57:405-429. https://doi.org/10.1016/j.infsof.2014.05.018S4054295

Towards an Adaptive Skeleton Framework for Performance Portability

The proliferation of widely available, but very different, parallel architectures makes the ability to deliver good parallel performance on a range of architectures, or performance portability, highly desirable. Irregularly-parallel problems, where the number and size of tasks is unpredictable, are particularly challenging and require dynamic coordination. The paper outlines a novel approach to delivering portable parallel performance for irregularly parallel programs. The approach combines declarative parallelism with JIT technology, dynamic scheduling, and dynamic transformation. We present the design of an adaptive skeleton library, with a task graph implementation, JIT trace costing, and adaptive transformations. We outline the architecture of the protoype adaptive skeleton execution framework in Pycket, describing tasks, serialisation, and the current scheduler.We report a preliminary evaluation of the prototype framework using 4 micro-benchmarks and a small case study on two NUMA servers (24 and 96 cores) and a small cluster (17 hosts, 272 cores). Key results include Pycket delivering good sequential performance e.g. almost as fast as C for some benchmarks; good absolute speedups on all architectures (up to 120 on 128 cores for sumEuler); and that the adaptive transformations do improve performance