270,726 research outputs found

    Evaluation and Measurement of Software Process Improvement -- A Systematic Literature Review

    Full text link
    BACKGROUND: Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE: This paper aims to identify and characterize evaluation strategies and measurements used to assess the impact of different SPI initiatives. METHOD: The systematic literature review includes 148 papers published between 1991 and 2008. The selected papers were classified according to SPI initiative, applied evaluation strategies, and measurement perspectives. Potential confounding factors interfering with the evaluation of the improvement effort were assessed. RESULTS: Seven distinct evaluation strategies were identified, wherein the most common one, "Pre-Post Comparison" was applied in 49 percent of the inspected papers. Quality was the most measured attribute (62 percent), followed by Cost (41 percent), and Schedule (18 percent). Looking at measurement perspectives, "Project" represents the majority with 66 percent. CONCLUSION: The evaluation validity of SPI initiatives is challenged by the scarce consideration of potential confounding factors, particularly given that "Pre-Post Comparison" was identified as the most common evaluation strategy, and the inaccurate descriptions of the evaluation context. Measurements to assess the short and mid-term impact of SPI initiatives prevail, whereas long-term measurements in terms of customer satisfaction and return on investment tend to be less used

    A conceptual framework for SPI evaluation

    Full text link
    Software Process Improvement (SPI) encompasses the analysis and modification of the processes within software development, aimed at improving key areas that contribute to the organizations' goals. The task of evaluating whether the selected improvement path meets these goals is challenging. On the basis of the results of a systematic literature review on SPI measurement and evaluation practices, we developed a framework (SPI Measurement and Evaluation Framework (SPI-MEF)) that supports the planning and implementation of SPI evaluations. SPI-MEF guides the practitioner in scoping the evaluation, determining measures, and performing the assessment. SPI-MEF does not assume a specific approach to process improvement and can be integrated in existing measurement programs, refocusing the assessment on evaluating the improvement initiative's outcome. Sixteen industry and academic experts evaluated the framework's usability and capability to support practitioners, providing additional insights that were integrated in the application guidelines of the framework

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

    Full text link
    [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

    Measuring Software Process: A Systematic Mapping Study

    Get PDF
    Context: Measurement is essential to reach predictable performance and high capability processes. It provides support for better understanding, evaluation, management, and control of the development process and project, as well as the resulting product. It also enables organizations to improve and predict its process’s performance, which places organizations in better positions to make appropriate decisions. Objective: This study aims to understand the measurement of the software development process, to identify studies, create a classification scheme based on the identified studies, and then to map such studies into the scheme to answer the research questions. Method: Systematic mapping is the selected research methodology for this study. Results: A total of 462 studies are included and classified into four topics with respect to their focus and into three groups based on the publishing date. Five abstractions and 64 attributes were identified, 25 methods/models and 17 contexts were distinguished. Conclusion: capability and performance were the most measured process attributes, while effort and performance were the most measured project attributes. Goal Question Metric and Capability Maturity Model Integration were the main methods and models used in the studies, whereas agile/lean development and small/medium-size enterprise were the most frequently identified research contexts.Ministerio de Economía y Competitividad TIN2013-46928-C3-3-RMinisterio de Economía y Competitividad TIN2016-76956-C3-2- RMinisterio de Economía y Competitividad TIN2015-71938-RED

    Software Reuse in Agile Development Organizations - A Conceptual Management Tool

    Get PDF
    The reuse of knowledge is considered a major factor for increasing productivity and quality. In the software industry knowledge is embodied in software assets such as code components, functional designs and test cases. This kind of knowledge reuse is also referred to as software reuse. Although the benefits can be substantial, software reuse has never reached its full potential. Organizations are not aware of the different levels of reuse or do not know how to address reuse issues. This paper proposes a conceptual management tool for supporting software reuse. Furthermore the paper presents the findings of the application of the management tool in an agile development organization
    • …
    corecore