Requirements engineering in software product line engineering

The final publication is available at Springer via http://dx.doi.org/10.1007/s00766-013-0189-0Many attempts have been made to increase the productivity and quality of software products based on software reuse. Software product line practice is one such approach, one that focuses on developing a family of products which have a majority of features in common. Hence, there are numerous requirements that are common across the family, but others are unique to individual products. Traditional requirements engineering methods were conceived to deal with single product requirements and are usually not flexible enough to address the needs arising from reusing requirements for a family of products. There is also the additional burden of correctly identifying and engineering both product-line-wide requirements and product-specific requirements as well as evolving them. Therefore, in this special issue, we want to highlight the importance and the role of requirements engineering for product line development as well as to provide insights into the state of the art in the field.Insfrán Pelozo, CE.; Chastek, G.; Donohoe, P.; Sampaio Do Prado Leite, JC. (2014). Requirements engineering in software product line engineering. Requirements Engineering. 19(4):331-332. doi:10.1007/s00766-013-0189-0S331332194Clements P, Northrop LM (2001) Software product lines: practices and patterns. Addison-Wesley, BostonDerakhshanmanesh M, Fox J, Ebert J (2012) Adopting feature-centric reuse of requirements assets: an industrial experience report. First international workshop on requirements engineering practices on software product line engineering, Salvador, BrazilKuloor C, Eberlein A (2002) Requirements engineering for software product lines, proceedings of the 15th international conference on software and systems engineering and their applications (ICSSEA’02), Paris, FranceNorthrop LM, Clements P (2013) A framework for software product line practice. Software engineering institute. http://www.sei.cmu.edu/productlines/tools/framework/index.cfm . Accessed 22 July 2013Yu Y, Lapouchnian A, Liaskos S, Mylopoulos J, Leite JCSP (2008) From Goals to High-Variability Software Design. Foundations of Intelligent Systems, 17th International Symposium Proceedings. ISMIS 2008. Springer Lecture Notes in Computer Science, 4994: 1–1

Variability Management in an unaware software product line company: An experience report

Software product line adoption is a challenging task in software development organisations. There are some reports in the literature of how software product line engineering has been adopted in several companies using di erent variabil-ity management techniques and patterns. However, to the best of our knowledge, there are no empirical reports on how variability management is handled in companies that do not know about software product line methods and tools. In this paper we present an experience report observing variability management practices in a software development company that was unaware of software product line approaches. We brie y report how variability management is performed in di erent areas ranging from business architecture to software assets management. From the observation we report some open research opportunities for the future and foster further similar and more structured empirical studies on unaware software product line companies.Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-5906Junta de Andalucía P12-TIC-186

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

[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. 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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). 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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). 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UDAVA: an unsupervised learning pipeline for sensor data validation in manufacturing

Manufacturing has enabled the mechanized mass production of the same (or similar) products by replacing craftsmen with assembly lines of machines. The quality of each product in an assembly line greatly hinges on continual observation and error compensation during machining using sensors that measure quantities such as position and torque of a cutting tool and vibrations due to possible imperfections in the cutting tool and raw material. Patterns observed in sensor data from a (near-)optimal production cycle should ideally recur in subsequent production cycles with minimal deviation. Manually labeling and comparing such patterns is an insurmountable task due to the massive amount of streaming data that can be generated from a production process. We present UDAVA, an unsupervised machine learning pipeline that automatically discovers process behavior patterns in sensor data for a reference production cycle. UDAVA performs clustering of reduced dimensionality summary statistics of raw sensor data to enable high-speed clustering of dense time-series data. It deploys the model as a service to verify batch data from subsequent production cycles to detect recurring behavior patterns and quantify deviation from the reference behavior. We have evaluated UDAVA from an AI Engineering perspective using two industrial case studies.publishedVersio

UML Transformation to Java-based Software Product Lines

Software product line engineering (SPLE) is an emerging approach that enables variability management in software development. SPLE offers tremendous benefits, but lack of tool support becomes a barrier in the adoption of SPLE. Variability modules for Java (VMJ) is an implementation approach that is defined based on the variability modules (VM) concept to support SPLE. VMJ combines Java modules system and design patterns that are commonly used by software developers. VMJ is accompanied by a UML profile, called UML-VM profile, which extends UML notation to model variability in the UML diagram. UML-VM diagram is used to model the problem domain, and VMJ is used in the domain implementation. In this research, we design a model transformation from Unified Modeling Language (UML) diagram into VMJ. The transformation rules are defined based on the UML-VM profile and implemented in the Eclipse Acceleo model to text transformation. As a result, a UML diagram can be transformed automatically into Java-based software product lines. The transformation tool is evaluated using a case study by comparing the generated code and the actual implementation

Product quality control strategy development for non-mAb complex modalities by using combinatorial cell engineering and OMICS screening tools

Product quality control without compromising productivity has been a major goal in biotherapeutics process development. The challenge is further increased for new modalities using complex and hybrid protein structures, such as nanobodies and bispecific antibodies. New product-related impurities and unique product quality attribute (PQA) species have been found to accompany these new protein scaffolds, which usually don’t exist in standard mAb production. Undesired attributes include unique patterns of glycosylation, conformation heterogeneity, mis-pairing, and partial molecules. Many of these PQAs are related to protein folding and assembly efficiency inside the cell, which impact post-translational modifications such as disulfide bond formation and glycosylation processes, directly or indirectly. We have identified multiple intracellular causal factors that link some PQAs directly to host cell lineage. To improve understanding and increase options in developing a successful production cell line with desired product quality profile, we have used this information to develop diversified CHO host lineages using both conditioned-culture adaptation and CRISPR genome editing approaches. The resulting CHO hosts showed significant differences in cell growth and recombinant protein production, including productivity and quality attribute profiles. Furthermore, the hosts respond differently to changes in medium components and process conditions. These differences were more significant for complex/ hybrid proteins such as nanobodies and bispecific antibodies. OMICS tools were systematically utilized to identify the evolutionarily significance of genetic and epigenetic variability of individual host cell lineages, which determine the specific PQA profile of the expressed recombinant protein. Overall, our presentation will illustrate the importance of selecting the appropriate host cell line through screening and/or engineering, as part of quality control strategy to obtain the desired recombinant protein PQA profile.

Systems engineering of a CHO cell line for enhanced process robustness

Recent advances in genome engineering have opened great opportunities for engineering Chinese hamster ovary cells. An ideal cell line is no longer just one with high productivity, but also with high stability in both the productivity and product quality, and in both extensive passaging and long term continuous culture. Furthermore, an ideal cell line should be provided with process controllability, allowing the use of environmental control variables to steer its metabolism to a reaction pathway that favors the synthesis of product with the desired quality attributes. Importantly, these superior traits must be genetically and epigenetically stable and be passed on to new production lines in cell line development. We have taken a systems approach that integrates genomic information and metabolic model predictions to devise a strategy and to develop tools for attaining those goals. In tool development we reassembled the Chinese hamster genome and combined different versions of the genome to identify consensus segments as high confidence regions and annotated the genome. An expression microarray and a comparative genomic hybridization array for gene coding regions were designed to facilitate cell engineering studies. Using solution phase capture and nested PCR we also established methods of rapidly identifying the integration sites of transgenes on the genome. An induced pluripotent stem cell (iPSC) line was derived from Chinese hamster embryonic fibroblasts for use as control in genomic and epigenomic tool development. Furthermore, we extended our kinetic model for cell metabolism to link with the glycosylation model and now embark on devising a reduced model suitable for systems optimization. The study involves surveying an established producing line and creating cell lines with a single copy transgene of GFP reporter or of IgG-GFP. The design of the single copy line entails a swappable recombination site for exchange of transgene so that cell lines which are otherwise “identical” but with different transgenes can be systematically compared. Through meta-analysis of archived transcriptome data we identified genes with different dynamics of expression patterns that can be useful for the dynamic control of cell behavior. CRISPR/Cas9 was employed to knock in a GFP between the first exon of the TXNIP gene and its endogenous promoter. Interestingly, the transcript levels of GFP in all investigated clones fell in a small range, but the dynamic profile was variable among them. In single copy clones of GFP reporter and IgG transgene, the transcript levels varied widely reflecting the probabilistic nature of their integration in the genome. The IgG titer and their transcript level of the clones also varied over a wide range. Overall, the result does not reveal a correlation between the transgene transcript level and the expression of the gene at the locus. Importantly, a number of clones showed a very high IgG transcript level, consistent with our previous report of a high transgene level prior to transgene amplification. The genomic context that may contribute to the variability, e.g. genomic consistency among the clones in terms of chromosome number, karyotype, and CGH, is being investigated. The implications of our findings to date and our work on implementing metabolic model prediction in this designing CHO cell line will be discussed. Although this work represents only an early step toward system engineering to cell line development, we believe such approaches will open new avenues to engineer cell lines and influence process development of biologics manufacturing in the coming years

Provisioning of customizable pattern-based software artifacts into Cloud environments

Software architects and engineers frequently face reoccurring problems, when implementing cloud computing applications, leading towards reduced productivity and an increased time to market factor. These issues can be faced by the commonly known concept of patterns. Thus, researchers identified and documented patterns for the cloud computing domain, to preserve gained knowledge about cloud application architectures and service offerings [FLMS11, FLR+12]. These patterns can be used to from the foundation of aggregated cloud computing applications. Dependent on the corresponding cloud service model, such applications require different provisioning steps, which can be performed by individually implemented actions or can be executed by pre-provided cloud services. Yet, these cloud computing patterns are offered in non-technical, written form, which does not allow to aggregate corresponding implementation binaries to pattern-based applications. Therefore, this thesis combines software product line engineering methods, open source build management tools, and open source infrastructure management tools to implement a software product line for cloud computing patterns, which allows to reduce human-driven efforts to implement aggregated cloud computing applications. This approach enables the possibility to create, aggregate and customize cloud computing pattern implementations; and store them in a so-called pattern template catalogue. Hence, each pattern, stored in such a catalogue, is associated with so-called customization points, which allow to adapt instantiated patterns to individual needs. To accomplish these challenges, Apache Maven [Mava], an open source build management tool, is extend with means to create, customize and aggregate pattern-based cloud computing applications. Corresponding provisioning tasks are accomplished, by combining PuppetLabs’ Puppet [Pup] and pre-offered cloud provisioning services. Pattern-specific customization points are stored within a serialized, so-called variability model, embedded in each pattern. Moreover, the presented structure model allows to decouple direct pattern dependencies through common interfaces, which allows to switch pattern implementations transparently, without adapting dependent patterns. Furthermore, combinable reference patterns are presented and discussed, to provide a proof of concept of the implemented software product line approach