Exploring the Duality between Product and Organizational Architectures: A Test of the Mirroring Hypothesis

A variety of academic studies argue that a relationship exists between the structure of an organization and the design of the products that this organization produces. Specifically, products tend to "mirror" the architectures of the organizations in which they are developed. This dynamic occurs because the organization's governance structures, problem solving routines and communication patterns constrain the space in which it searches for new solutions. Such a relationship is important, given that product architecture has been shown to be an important predictor of product performance, product variety, process flexibility and even the path of industry evolution. We explore this relationship in the software industry. Our research takes advantage of a natural experiment, in that we observe products that fulfill the same function being developed by very different organizational forms. At one extreme are commercial software firms, in which the organizational participants are tightly-coupled, with respect to their goals, structure and behavior. At the other, are open source software communities, in which the participants are much more loosely-coupled by comparison. The mirroring hypothesis predicts that these different organizational forms will produce products with distinctly different architectures. Specifically, loosely-coupled organizations will develop more modular designs than tightly-coupled organizations. We test this hypothesis, using a sample of matched-pair products. We find strong evidence to support the mirroring hypothesis. In all of the pairs we examine, the product developed by the loosely-coupled organization is significantly more modular than the product from the tightly-coupled organization. We measure modularity by capturing the level of coupling between a product's components. The magnitude of the differences is substantial - up to a factor of eight, in terms of the potential for a design change in one component to propagate to others. Our results have significant managerial implications, in highlighting the impact of organizational design decisions on the technical structure of the artifacts that these organizations subsequently develop.Organizational Design, Product Design, Architecture, Modularity, Open-Source Software.

What to Fix? Distinguishing between design and non-design rules in automated tools

Technical debt---design shortcuts taken to optimize for delivery speed---is a critical part of long-term software costs. Consequently, automatically detecting technical debt is a high priority for software practitioners. Software quality tool vendors have responded to this need by positioning their tools to detect and manage technical debt. While these tools bundle a number of rules, it is hard for users to understand which rules identify design issues, as opposed to syntactic quality. This is important, since previous studies have revealed the most significant technical debt is related to design issues. Other research has focused on comparing these tools on open source projects, but these comparisons have not looked at whether the rules were relevant to design. We conducted an empirical study using a structured categorization approach, and manually classify 466 software quality rules from three industry tools---CAST, SonarQube, and NDepend. We found that most of these rules were easily labeled as either not design (55%) or design (19%). The remainder (26%) resulted in disagreements among the labelers. Our results are a first step in formalizing a definition of a design rule, in order to support automatic detection.Comment: Long version of accepted short paper at International Conference on Software Architecture 2017 (Gothenburg, SE

Exploring Maintainability Assurance Research for Service- and Microservice-Based Systems: Directions and Differences

To ensure sustainable software maintenance and evolution, a diverse set of activities and concepts like metrics, change impact analysis, or antipattern detection can be used. Special maintainability assurance techniques have been proposed for service- and microservice-based systems, but it is difficult to get a comprehensive overview of this publication landscape. We therefore conducted a systematic literature review (SLR) to collect and categorize maintainability assurance approaches for service-oriented architecture (SOA) and microservices. Our search strategy led to the selection of 223 primary studies from 2007 to 2018 which we categorized with a threefold taxonomy: a) architectural (SOA, microservices, both), b) methodical (method or contribution of the study), and c) thematic (maintainability assurance subfield). We discuss the distribution among these categories and present different research directions as well as exemplary studies per thematic category. The primary finding of our SLR is that, while very few approaches have been suggested for microservices so far (24 of 223, ?11%), we identified several thematic categories where existing SOA techniques could be adapted for the maintainability assurance of microservices

The P3 platform: an approach and software system for developing diagrammatic model-based methods in design research

Many issues in design and design management have been explored by building models which capture the relationships between different aspects of the problem at hand. These models require computer support to construct and analyse. However, appropriate modelling tools can be time-consuming to develop in a research environment. Reflecting upon five design research projects, this paper proposes that such projects can be facilitated by recognising the iterative and tightly-coupled nature of research and tool development, and by attempting to minimise the effort of solution prototyping within this process. Our approach is enabled by a software platform which can be rapidly configured to implement many conceivable modelling approaches. This configurability is complemented by an emerging library of modelling and analysis approaches tailored to explore design process systems. The platform-based approach enables any mix of modelling concepts to be easily created. We propose it could thus help researchers to explore a wide range of questions without being constrained to existing conventions for modelling – or for model integration

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. 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

Assessing architectural evolution: A case study

This is the post-print version of the Article. The official published can be accessed from the link below - Copyright @ 2011 SpringerThis paper proposes to use a historical perspective on generic laws, principles, and guidelines, like Lehman’s software evolution laws and Martin’s design principles, in order to achieve a multi-faceted process and structural assessment of a system’s architectural evolution. We present a simple structural model with associated historical metrics and visualizations that could form part of an architect’s dashboard. We perform such an assessment for the Eclipse SDK, as a case study of a large, complex, and long-lived system for which sustained effective architectural evolution is paramount. The twofold aim of checking generic principles on a well-know system is, on the one hand, to see whether there are certain lessons that could be learned for best practice of architectural evolution, and on the other hand to get more insights about the applicability of such principles. We find that while the Eclipse SDK does follow several of the laws and principles, there are some deviations, and we discuss areas of architectural improvement and limitations of the assessment approach