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    A systematic review of quality attributes and measures for software product lines

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    [EN] It is widely accepted that software measures provide an appropriate mechanism for understanding, monitoring, controlling, and predicting the quality of software development projects. In software product lines (SPL), quality is even more important than in a single software product since, owing to systematic reuse, a fault or an inadequate design decision could be propagated to several products in the family. Over the last few years, a great number of quality attributes and measures for assessing the quality of SPL have been reported in literature. However, no studies summarizing the current knowledge about them exist. This paper presents a systematic literature review with the objective of identifying and interpreting all the available studies from 1996 to 2010 that present quality attributes and/or measures for SPL. These attributes and measures have been classified using a set of criteria that includes the life cycle phase in which the measures are applied; the corresponding quality characteristics; their support for specific SPL characteristics (e. g., variability, compositionality); the procedure used to validate the measures, etc. We found 165 measures related to 97 different quality attributes. The results of the review indicated that 92% of the measures evaluate attributes that are related to maintainability. In addition, 67% of the measures are used during the design phase of Domain Engineering, and 56% are applied to evaluate the product line architecture. However, only 25% of them have been empirically validated. In conclusion, the results provide a global vision of the state of the research within this area in order to help researchers in detecting weaknesses, directing research efforts, and identifying new research lines. In particular, there is a need for new measures with which to evaluate both the quality of the artifacts produced during the entire SPL life cycle and other quality characteristics. There is also a need for more validation (both theoretical and empirical) of existing measures. In addition, our results may be useful as a reference guide for practitioners to assist them in the selection or the adaptation of existing measures for evaluating their software product lines. © 2011 Springer Science+Business Media, LLC.This research has been funded by the Spanish Ministry of Science and Innovation under the MULTIPLE (Multimodeling Approach For Quality-Aware Software Product Lines) project with ref. TIN2009-13838.Montagud Gregori, S.; Abrahao Gonzales, SM.; Insfrán Pelozo, CE. (2012). A systematic review of quality attributes and measures for software product lines. Software Quality Journal. 20(3-4):425-486. https://doi.org/10.1007/s11219-011-9146-7S425486203-4Abdelmoez, W., Nassar, D. M., Shereschevsky, M., Gradetsky, N., Gunnalan, R., Ammar, H. H., et al. (2004). Error propagation in software architectures. In 10th international symposium on software metrics (METRICS), Chicago, Illinois, USA.Ajila, S. A., & Dumitrescu, R. T. (2007). Experimental use of code delta, code churn, and rate of change to understand software product line evolution. Journal of Systems and Software, 80, 74–91.Aldekoa, G., Trujillo, S., Sagardui, G., & Díaz, O. (2006). Experience measuring maintainability in software product lines. In XV Jornadas de Ingeniería del Software y Bases de Datos (JISBD). Barcelona.Aldekoa, G., Trujillo, S., Sagardui, G., & Díaz, O. (2008). Quantifying maintanibility in feature oriented product lines, Athens, Greece, pp. 243–247.Alves de Oliveira Junior, E., Gimenes, I. M. S., & Maldonado, J. C. (2008). A metric suite to support software product line architecture evaluation. In XXXIV Conferencia Latinamericana de Informática (CLEI), Santa Fé, Argentina, pp. 489–498.Alves, V., Niu, N., Alves, C., & Valença, G. (2010). Requirements engineering for software product lines: A systematic literature review. Information & Software Technology, 52(8), 806–820.Bosch, J. (2000). Design and use of software architectures: Adopting and evolving a product line approach. USA: ACM Press/Addison-Wesley Publishing Co.Briand, L. C., Differing, C. M., & Rombach, D. (1996a). Practical guidelines for measurement-based process improvement. Software Process-Improvement and Practice, 2, 253–280.Briand, L. C., Morasca, S., & Basili, V. R. (1996b). Property based software engineering measurement. IEEE Transactions on Software Eng., 22(1), 68–86.Calero, C., Ruiz, J., & Piattini, M. (2005). Classifying web metrics using the web quality model. Online Information Review, 29(3): 227–248.Chen, L., Ali Babar, M., & Ali, N. (2009). Variability management in software product lines: A systematic review. In 13th international software product lines conferences (SPLC), San Francisco, USA.Clements, P., & Northrop, L. (2002). Software product lines. 2003. Software product lines practices and patterns. Boston, MA: Addison-Wesley.Crnkovic, I., & Larsson, M. (2004). Classification of quality attributes for predictability in component-based systems. Journal of Econometrics, pp. 231–250.Conference Rankings of Computing Research and Education Association of Australasia (CORE). (2010). Available in http://core.edu.au/index.php/categories/conference%20rankings/1 .Davis, A., Dieste, Ó., Hickey, A., Juristo, N., & Moreno, A. M. (2006). Effectiveness of requirements elicitation techniques: Empirical results derived from a systematic review. In 14th IEEE international conference requirements engineering, pp. 179–188.de Souza Filho, E. D., de Oliveira Cavalcanti, R., Neiva, D. F. S., Oliveira, T. H. B., Barachisio Lisboa, L., de Almeida E. S., & de Lemos Meira, S. R. (2008). Evaluating domain design approaches using systematic review. In 2nd European conference on software architecture, Cyprus, pp. 50–65.Ejiogu, L. (1991). Software engineering with formal metrics. QED Publishing.Engström, E., & Runeson, P. (2011). Software product line testing—A systematic mapping study. Information & Software Technology, 53(1), 2–13.Etxeberria, L., Sagarui, G., & Belategi, L. (2008). Quality aware software product line engineering. Journal of the Brazilian Computer Society, 14(1), Campinas Mar.Ganesan, D., Knodel, J., Kolb, R., Haury, U., & Meier, G. (2007). Comparing costs and benefits of different test strategies for a software product line: A study from Testo AG. In 11th international software product line conference, Kyoto, Japan, pp. 74–83, September 2007.Gómez, O., Oktaba, H., Piattini, M., & García, F. (2006). A systematic review measurement in software engineering: State-of-the-art in measures. In First international conference on software and data technologies (ICSOFT), Setúbal, Portugal, pp. 11–14.IEEE standard for a software quality metrics methodology, IEEE Std 1061-1998, 1998.Inoki, M., & Fukazawa, Y. (2007). Software product line evolution method based on Kaizen approach. In 22nd annual ACM symposium on applied computing, Korea.Insfran, E., & Fernandez, A. (2008). A systematic review of usability evaluation in Web development. 2nd international workshop on web usability and accessibility (IWWUA’08), New Zealand, LNCS 5176, Springer, pp. 81–91.ISO/IEC 25010. (2008). Systems and software engineering. Systems and software Quality Requirements and Evaluation (SQuaRE). System and software quality models.ISO/IEC 9126. (2000). Software engineering. Product Quality.Johansson, E., & Höst, R. (2002). Tracking degradation in software product lines through measurement of design rule violations. In 14th International conference on software engineering and knowledge engineering, Ischia, Italy, pp. 249–254.Journal Citation Reports of Thomson Reuters. (2010). Available in http://thomsonreuters.com/products_services/science/science_products/a-z/journal_citation_reports/ .Khurum, M., & Gorschek, T. (2009). A systematic review of domain analysis solutions for product lines. The Journal of Systems and Software.Kim, T., Ko, I. Y., Kang, S. W., & Lee, D. H. (2008). Extending ATAM to assess product line architecture. In 8th IEEE international conference on computer and information technology, pp. 790–797.Kitchenham, B. (2007). Guidelines for performing systematic literature reviews in software engineering. Version 2.3, EBSE Technical Report, Keele University, UK.Kitchenham, B., Pfleeger, S., & Fenton, N. (1995). Towards a framework for software measurement validation. IEEE Transactions on Software Engineering, 21(12).Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33, 159–174.Mendes, E. (2005). A systematic review of Web engineering research. International symposium on empirical software engineering. Noosa Heads, Australia.Meyer, M. H., & Dalal, D. (2002). Managing platform architectures and manufacturing processes for non assembled products. Journal of Product Innovation Management, 19(4), 277–293.Montagud, S., & Abrahão, S. (2009). Gathering Current knowledge about quality evaluation in software product lines. In 13th international software product lines conferences (SPLC), San Francisco, USA.Montagud, S., & Abrahão, S. (2009). A SQuaRE-bassed quality evaluation method for software product lines. Master’s thesis, December 2009 (in Spanish).Needham, D., & Jones, S. (2006). A software fault tree metric. In 22nd international conference on software maintenance (ICSM), Philadelphia, Pennsylvania, USA.Niemelä, E., & Immonen, A. (2007). Capturing quality requirements of product family architecture. Information and Software Technology, 49(11–12), 1107–1120.Odia, O. E. (2007). Testing in software product lines. Master Thesis Software Engineering of School of Engineering, Bleking Institute of Technology. Thesis no. MSE-2007:16, Sweden.Olumofin, F. G., & Mišić, V. B. (2007). A holistic architecture assessment method for software product lines. Information and Software Technology, 49, 309–323.Pérez Lamancha, B., Polo Usaola, M., & Piattini Velthius, M. (2009). Software product line testing—a systematic review. ICSOFT, (1), 23–30.Poels, G., & Dedene, G. (2000). Distance-based software measurement: necessary and sufficient properties for software measures. Information and Software Technology, 42(I), 35–46.Prehofer, C., van Gurp, J., & Bosch, J. (2008). Compositionality in software platforms. In Emerging methods, technologies and process management in software engineering. Wiley.Rahman, A. (2004). Metrics for the structural assessment of product line architecture. Master Thesis on Software Engineering, Thesis no. MSE-2004:24. School of Engineering, Blekinge Institute of Technology, Sweden.Sethi, K., Cai, Y., Wong, S., Garcia, A., & Sant’Anna, C. (2009). From retrospect to prospect: Assessing modularity and stability from software architecture. Joint working IEEE/IFIP conference on software architecture, 2009 & European conference on software architecture. WICSA/ECSA.Shaik, I., Abdelmoez, W,. Gunnalan, R., Shereshevsky, M., Zeid, A., Ammar, H. H., et al. (2005). Change propagation for assessing design quality of software architectures. 5th working IEEE/IFIP conference on software architecture (WICSA’05).Siegmund, N., Rosenmüller, M., Kuhlemann, M., Kästner, C., & Saake, G. (2008). Measuring non-functional properties in software product lines for product derivation. In 15th Asia-Pacific software engineering conference, Beijing, China.Sun Her, J., Hyeok Kim, J., Hun Oh, S., Yul Rhew, S., & Dong Kim, S. (2007). A framework for evaluating reusability of core asset in product line engineering. Information and Software Technology, 49, 740–760.Svahnberg, M., & Bosch, J. (2000). Evolution in software product lines. In 3rd international workshop on software architectures for products families (IWSAPF-3). Las Palmas de Gran Canaria.Van der Hoek, A., Dincel, E., & Medidović, N. (2003). Using services utilization metrics to assess the structure of product line architectures. In 9th international software metrics symposium (METRICS), Sydney, Australia.Van der Linden, F., Schmid, K., & Rommes, E. (2007). Software product lines in action. Springer.Whitmire, S. (1997). Object oriented design measurement. John Wiley & Sons.Wnuk, K., Regnell, B., & Karlsson, L. (2009). What happened to our features? Visualization and understanding of scope change dynamics in a large-scale industrial setting. In 17th IEEE international requirements engineering conference.Yoshimura, K., Ganesan, D., & Muthig, D. (2006). Assessing merge potential of existing engine control systems into a product line. In International workshop on software engineering for automative systems, Shangai, China, pp. 61–67.Zhang, T., Deng, L., Wu, J., Zhou, Q., & Ma, C. (2008). Some metrics for accessing quality of product line architecture. In International conference on computer science and software engineering (CSSE), Wuhan, China, pp. 500–503

    Towards guidelines for building a business case and gathering evidence of software reference architectures in industry

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    Background: Software reference architectures are becoming widely adopted by organizations that need to support the design and maintenance of software applications of a shared domain. For organizations that plan to adopt this architecture-centric approach, it becomes fundamental to know the return on investment and to understand how software reference architectures are designed, maintained, and used. Unfortunately, there is little evidence-based support to help organizations with these challenges. Methods: We have conducted action research in an industry-academia collaboration between the GESSI research group and everis, a multinational IT consulting firm based in Spain. Results: The results from such collaboration are being packaged in order to create guidelines that could be used in similar contexts as the one of everis. The main result of this paper is the construction of empirically-grounded guidelines that support organizations to decide on the adoption of software reference architectures and to gather evidence to improve RA-related practices. Conclusions: The created guidelines could be used by other organizations outside of our industry-academia collaboration. With this goal in mind, we describe the guidelines in detail for their use.Peer ReviewedPostprint (published version

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

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    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

    Software Evolution for Industrial Automation Systems. Literature Overview

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    Quantifying software architecture attributes

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    Software architecture holds the promise of advancing the state of the art in software engineering. The architecture is emerging as the focal point of many modem reuse/evolutionary paradigms, such as Product Line Engineering, Component Based Software Engineering, and COTS-based software development. The author focuses his research work on characterizing some properties of a software architecture. He tries to use software metrics to represent the error propagation probabilities, change propagation probabilities, and requirements change propagation probabilities of a software architecture. Error propagation probability reflects the probability that an error that arises in one component of the architecture will propagate to other components of the architecture at run-time. Change propagation probability reflects, for a given pair of components A and B, the probability that if A is changed in a corrective/perfective maintenance operation, B has to be changed to maintain the overall function the system. Requirements change propagation probability reflects the likelihood that a requirement change that arises in one component of the architecture propagates to other components. For each case, the author presents the analytical formulas which mainly based on statistical theory and empirical studies. Then the author studies the correlations between analytical results and empirical results. The author also uses several metrics to quantify the properties of a Product Line Architecture, such as scoping, variability, commonality, and applicability. He presents his proposed means to measure the properties and the results of the case studies

    Uncovering sustainability concerns in software product lines

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    Sustainable living, i.e., living within the bounds of the available environmental, social, and economic resources, is the focus of many present-day social and scientific discussions. But what does sustainability mean within the context of Software Engineering? In this paper we undertake a comprehensive analysis of 8 case studies to address this question within the context of a specific SE approach, Software Product Line Engineering (SPLE). We identify the sustainability-related characteristics that arise in present-day studies that apply SPLE. We conclude that technical and economic sustainability are in prime focus on the present SPLE practice, with social sustainability issues, where they relate to organisations, also addressed to a good degree. On the other hand, the issues related to the personal sustainability are less prominent, and environmental considerations are nearly completely amiss. We present feature models and cross-relations that result from our analysis as a starting point for sustainability engineering through SPLE, suggesting that any new development should consider how these models would be instantiated and expanded for the intended socio-technical system. The good representation of sustainability features in these models is also validated with two additional case studies

    A Process Framework for Semantics-aware Tourism Information Systems

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    The growing sophistication of user requirements in tourism due to the advent of new technologies such as the Semantic Web and mobile computing has imposed new possibilities for improved intelligence in Tourism Information Systems (TIS). Traditional software engineering and web engineering approaches cannot suffice, hence the need to find new product development approaches that would sufficiently enable the next generation of TIS. The next generation of TIS are expected among other things to: enable semantics-based information processing, exhibit natural language capabilities, facilitate inter-organization exchange of information in a seamless way, and evolve proactively in tandem with dynamic user requirements. In this paper, a product development approach called Product Line for Ontology-based Semantics-Aware Tourism Information Systems (PLOSATIS) which is a novel hybridization of software product line engineering, and Semantic Web engineering concepts is proposed. PLOSATIS is presented as potentially effective, predictable and amenable to software process improvement initiatives
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