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

Analysis of Software Binaries for Reengineering-Driven Product Line Architecture\^aAn Industrial Case Study

This paper describes a method for the recovering of software architectures from a set of similar (but unrelated) software products in binary form. One intention is to drive refactoring into software product lines and combine architecture recovery with run time binary analysis and existing clustering methods. Using our runtime binary analysis, we create graphs that capture the dependencies between different software parts. These are clustered into smaller component graphs, that group software parts with high interactions into larger entities. The component graphs serve as a basis for further software product line work. In this paper, we concentrate on the analysis part of the method and the graph clustering. We apply the graph clustering method to a real application in the context of automation / robot configuration software tools.Comment: In Proceedings FMSPLE 2015, arXiv:1504.0301

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. Empirical Software Engineering 16(5), 539–543 (2011)Ali-Babar, M., Zhu, L., Jeffery, R.: A Framework for Classifying and Comparing Software Architecture Evaluation Methods. In: 15th Australian Software Engineering Conference, Melbourne, Australia, pp. 309–318 (2004)Basili, V.R., Rombach, H.D.: The TAME project: towards improvement-oriented software environments. IEEE Transactions on Software Engineering 14(6), 758–773 (1988)Barkmeyer, E.J., Feeney, A.B., Denno, P., Flater, D.W., Libes, D.E., Steves, M.P., Wallace, E.K.: Concepts for Automating Systems Integration NISTIR 6928. National Institute of Standards and Technology, U.S. Dept. of Commerce (2003)Bosch, J.: Design and Use of Software Architectures. Adopting and Evolving Product-Line Approach. Addison-Wesley, Harlow (2000)Botterweck, G., O’Brien, L., Thiel, S.: Model-driven derivation of product architectures. In: 22th Int. Conf. on Automated Software Engineering, New York, USA, pp. 469–472 (2007)Buschmann, F., Meunier, R., Rohnert, H., Sommerlad, P., Stal, M.: Pattern-Oriented software architecture, vol. 1: A System of Patterns. Wiley (1996)Cabello, M.E., Ramos, I., Gómez, A., Limón, R.: Baseline-Oriented Modeling: An MDA Approach Based on Software Product Lines for the Expert Systems Development. In: 1st Asia Conference on Intelligent Information and Database Systems, Vietnam (2009)Carifio, J., Perla, R.J.: Ten Common Misunderstandings, Misconceptions, Persistent Myths and Urban Legends about Likert Scales and Likert Response Formats and their Antidotes. Journal of Social Sciences 3(3), 106–116 (2007)Clements, P., Northrop, L.: Software Product Lines: Practices and Patterns. Addison-Wesley, Boston (2007)Czarnecki, K., Kim, C.H.: Cardinality-based feature modeling and constraints: A progress report. In: Int. Workshop on Software Factories, San Diego-CA (2005)Datorro, J.: Convex Optimization & Euclidean Distance Geometry. Meboo Publishing (2005)Davis, F.D.: Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quarterly 13(3), 319–340 (1989)Douglass, B.P.: Real-Time Design Patterns: Robust Scalable Architecture for Real-Time Systems. Addison-Wesley, Boston (2002)Feiler, P.H., Gluch, D.P., Hudak, J.: The Architecture Analysis & Design Language (AADL): An Introduction. Tech. Report CMU/SEI-2006-TN-011. SEI, Carnegie Mellon University (2006)Gómez, A., Ramos, I.: Cardinality-based feature modeling and model-driven engineering: Fitting them together. In: 4th Int. Workshop on Variability Modeling of Software Intensive Systems, Linz, Austria (2010)Gonzalez-Huerta, J., Insfran, E., Abrahao, S.: A Multimodel for Integrating Quality Assessment in Model-Driven Engineering. In: 8th International Conference on the Quality of Information and Communications Technology (QUATIC 2012), Lisbon, Portugal, September 3-6 (2012)Gonzalez-Huerta, J., Insfran, E., Abrahao, S., McGregor, J.D.: Non-functional Requirements in Model-Driven Software Product Line Engineering. In: 4th Int. Workshop on Non-functional System Properties in Domain Specific Modeling Languages, Insbruck, Austria (2012)Guana, V., Correal, V.: Variability quality evaluation on component-based software product lines. In: 15th Int. Software Product Line Conference, Munich, Germany, vol. 2, pp. 19.1–19.8 (2011)Insfrán, E., Abrahão, S., González-Huerta, J., McGregor, J.D., Ramos, I.: A Multimodeling Approach for Quality-Driven Architecture Derivation. In: 21st Int. Conf. on Information Systems Development (ISD 2012), Prato, Italy (2012)ISO/IEC 25000:2005, Software Engineering. Software product Quality Requirements and Evaluation SQuaRE (2005)Kazman, R., Klein, M., Clements, P.: ATAM: Method for Architecture Evaluation (CMU/SEI-2000-TR-004, ADA382629). Software Engineering Institute, Carnegie Mellon University, Pittsburgh (2000), http://www.sei.cmu.edu/publications/documents/00.reports/00tr004.htmlKim, T., Ko, I., Kang, S., Lee, D.: Extending ATAM to assess product line architecture. In: 8th IEEE Int. Conference on Computer and Information Technology, Sydney, Australia, pp. 790–797 (2008)Kitchenham, B.A., Pfleeger, S.L., Hoaglin, D.C., Rosenber, J.: Preliminary Guidelines for Empirical Research in Software Engineering. IEEE Transactions on Software Engineering 28(8) (2002)Kruchten, P.B.: The Rational Unified Process: An Introduction. Addison-Wesley (1999)Martensson, F.: Software Architecture Quality Evaluation. Approaches in an Industrial Context. Ph. D. thesis, Blekinge Institute of Technology, Karlskrona, Sweden (2006)Maxwell, K.: Applied Statistics for Software Managers. Software Quality Institute Series. Prentice-Hall (2002)Olumofin, F.G., Mišic, V.B.: A holistic architecture assessment method for software product lines. Information and Software Technology 49, 309–323 (2007)Perovich, D., Rossel, P.O., Bastarrica, M.C.: Feature model to product architectures: Applying MDE to Software Product Lines. In: IEEE/IFIP & European Conference on Software Architecture, Helsinki, Findland, pp. 201–210 (2009)Robertson, S., Robertson, J.: Mastering the requirements process. ACM Press, New York (1999)Roos-Frantz, F., Benavides, D., Ruiz-Cortés, A., Heuer, A., Lauenroth, K.: Quality-aware analysis in product line engineering with the orthogonal variability model. Software Quality Journal (2011), doi:10.1007/s11219-011-9156-5Saaty, T.L.: The Analytical Hierarchical Process. McGraw- Hill, New York (1990)Taher, L., Khatib, H.E., Basha, R.: A framework and QoS matchmaking algorithm for dynamic web services selection. In: 2nd Int. Conference on Innovations in Information Technology, Dubai, UAE (2005)Wohlin, C., Runeson, P., Host, M., Ohlsson, M.C., Regnell, B., Weslen, A.: Experimentation in Software Engineering - An Introduction. Kluwer (2000

Towards Product Lining Model-Driven Development Code Generators

A code generator systematically transforms compact models to detailed code. Today, code generation is regarded as an integral part of model-driven development (MDD). Despite its relevance, the development of code generators is an inherently complex task and common methodologies and architectures are lacking. Additionally, reuse and extension of existing code generators only exist on individual parts. A systematic development and reuse based on a code generator product line is still in its infancy. Thus, the aim of this paper is to identify the mechanism necessary for a code generator product line by (a) analyzing the common product line development approach and (b) mapping those to a code generator specific infrastructure. As a first step towards realizing a code generator product line infrastructure, we present a component-based implementation approach based on ideas of variability-aware module systems and point out further research challenges.Comment: 6 pages, 1 figure, Proceedings of the 3rd International Conference on Model-Driven Engineering and Software Development, pp. 539-545, Angers, France, SciTePress, 201

Variability and Evolution in Systems of Systems

In this position paper (1) we discuss two particular aspects of Systems of Systems, i.e., variability and evolution. (2) We argue that concepts from Product Line Engineering and Software Evolution are relevant to Systems of Systems Engineering. (3) Conversely, concepts from Systems of Systems Engineering can be helpful in Product Line Engineering and Software Evolution. Hence, we argue that an exchange of concepts between the disciplines would be beneficial.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

Creating product line architectures

The creation and validation of product line software architectures are inherently more complex than those of software architectures for single systems. This paper compares a process for creating and evaluating a traditional, one-of-a- kind software architecture with one for a reference software architecture. The comparison is done in the context of PuLSE-DSSA, a customizable process that integrates both product line architecture creation and evaluation

Ontology-based modelling of architectural styles

The conceptual modelling of software architectures is of central importance for the quality of a software system. A rich modelling language is required to integrate the different aspects of architecture modelling, such as architectural styles, structural and behavioural modelling, into a coherent framework. Architectural styles are often neglected in software architectures. We propose an ontological approach for architectural style modelling based on description logic as an abstract, meta-level modelling instrument. We introduce a framework for style definition and style combination. The application of the ontological framework in the form of an integration into existing architectural description notations is illustrated

Context for goal-level product line derivation

Product line engineering aims at developing a family of products and facilitating the derivation of product variants from it. Context can be a main factor in determining what products to derive. Yet, there is gap in incorporating context with variability models. We advocate that, in the first place, variability originates from human intentions and choices even before software systems are constructed, and context influences variability at this intentional level before the functional one. Thus, we propose to analyze variability at an early phase of analysis adopting the intentional ontology of goal models, and studying how context can influence such variability. Below we present a classification of variation points on goal models, analyze their relation with context, and show the process of constructing and maintaining the models. Our approach is illustrated with an example of a smarthome for people with dementia problems. 1