Abstract
Context
In the last two decades, open-source software (OSS) has gained increasing attention due to its voluntary supporters, growing community, and ease of accessibility in cloud repositories. Standardization in OSS quality is of vital importance as a communication vehicle for stakeholders in identifying and selecting high-quality products. Thus, meta-models help to define a standardized language and enable to propose quality models that can be used to perform comparable measurements.
Objective
Considering the lack of a comprehensive meta-model of OSS quality in the literature, there appears a need to see a more complete picture of OSS quality and to represent its concepts more formally. Therefore, in this study, it is aimed to develop a solid base for a comprehensive meta-model of OSS quality to create a common understanding among stakeholders.
Method
A systematic way has been followed toward developing a common structure, defining a consistent terminology and, finally, providing a meta-model of OSS quality. In this context, (1) the common structure of the quality models for OSS has been investigated, (2) the terms of the general-purpose meta-models of software quality have been analyzed based on the international standards, and (3) the terms of the quality models for OSS have been mapped with the elements of these meta-models.
Results
An initial meta-model of OSS quality, which employs a unified structure from the OSS quality models and eliminates the inconsistencies determined in the general-purpose meta-models of software quality, has been proposed and an implementation of this meta-model has been demonstrated.
Conclusion
This initial meta-model of OSS quality with a standard terminology can be taken as a guide by researchers who will propose or revise their OSS quality models. It will allow developing multiple OSS quality models with homogenous structure and terms, and also enable comparing the evaluation results obtained by these models.
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Data Availability
The data that support the findings of this study are openly available in Zenodo at the following URL: definition of the terminologies in the SQMM, Zenodo, https://doi.org/10.5281/zenodo.6367596.
References
Adewumi, A., Misra, S., & Omoregbe, N. (2013). A review of models for evaluating quality in open source software. IERI Procedia, 4, 88–92.
Adewumi, A., Misra S., Omoragbe, N., Crawford, B., & Soto, R. (2016). A systematic literature review of open source software quality assessment models. SpringerPlus, 5.1, 1936.
Adewumi, A., Misra S., & Omoragbe, N. (2019). FOSSES: framework for open‐source software evaluation and selection. Software: Practice and Experience, 49.5, 780–812.
Ahmad, N., & Laplante, P. A. (2013). A systematic approach to evaluating open source software. Howard C, ed. Strategic Adoption of Technological Innovations. Hershey, PA: IGI Global: pp 50–69.
Al-Badareen, A. B., Selamat, M. H., Jabar, M. A., Din, J., & Turaev, S. (2011). Software quality models: a comparative study. International Conference on Software Engineering and Computer Systems, (pp. 46–55). Springer, Berlin, Heidelberg.
Al-Dhaqm, A., Razak, S., Othman, S. H., Ngadi, A., Ahmed, M. N., & Ali Mohammed, A. (2017). Development and validation of a database forensic metamodel (DBFM). PloS one, 12(2), e0170793.
Alfonzo, O., Domínguez, K., Rivas, L., Perez, M., Mendoza, L., & Ortega, M. (2008). Quality measurement model for analysis and design tools based on FLOSS. 19th Australian conference on software engineering. Perth, (pp 26–28) Australia.
Alvaro, A., Almeida, E. S., & Meira, S. R. L. (2010). A software component quality framework. ACM SIGSOFT Software Engineering Notes, 35(1), 1–4.
Aversano, L., & Tortorella, M. (2013). Quality evaluation of floss projects: application to ERP systems. Information and Software Technology. 55.7, 1260–1276.
Barcellos, M.P., de Almeida Falbo, R., & Dal Moro, R. (2010). A well-founded software measurement ontology. FOIS, (pp. 213–226).
Barcellos, M. P., & de Almeida Falbo, R. (2013). A software measurement task ontology. Proceedings of the 28th Annual ACM Symposium on Applied Computing, (pp. 311–318).
Bertoa, M., & Vallecillo, A. (2002). Quality attributes for COTS components”, I+D Computación, Vol 1. Nro, 2, 128–144.
Bertoa, M. F., Vallecillo, A., & García, F. (2006). An ontology for software measurement. Ontologies for Software Engineering and Software Technology, (pp. 175–196). Springer, Berlin, Heidelberg.
Beydoun, G., Low, G., Henderson-Sellers, B., Mouratidis, H., Gomez-Sanz, J. J., Pavon, J., & Gonzalez-Perez, C. (2009). FAML: A generic metamodel for MAS development. IEEE Transactions on Software Engineering, 35(6), 841–863.
Boehm, B. W., Brown, H., & Lipow, M. (1978). Quantitative evaluation of software quality. Proceedings of the 2nd International Conference on Software Engineering, (pp. 592–605).
Briand, L., Morasca, S., & Basili, V. (2002). An operational process for goal driven definition of measures. IEEE Transactions on Software Engineering, 28(12), 1106–1125.
Ciolkowski, M., & Soto, M. (2008). Towards a comprehensive approach for assessing open source projects. Software Process and Product Measurement, (pp. 316–330). Springer, Berlin, Heidelberg.
Chirinos, L., Losavio, F., & Bøegh, J. (2005). Characterizing a data model for software measurement. Journal of Systems and Software, 74(2), 207–226.
Czarnacka, C. B. (2009). The ISO/IEC Standards for the Software Processes and Products Measurement. (pp. 187–200).
Del Bianco, V., Lavazza, L., Morasca, S., & Taibi, D. (2009). Quality of open source software: The QualiPSo Trustworthiness Model. IFIP International Conference on Open Source Systems. Springer, Berlin, Heidelberg.
Dromey, R. G. (1995). A model for software product quality. IEEE Transactions on Software Engineering, 21(2), 146–162.
Duijnhouwer, F. W., & Widdows, C. (2003). Capgemini Expert Letter Open Source Maturity Model, Capgemini, tinyurl.com/yxdbvjk6.
Eghan, E. E., Alqahtani, S.S., Forbes, C., & Rilling, J. (2019). API trustworthiness: an ontological approach for software library adoption. Software Quality, Journal, 27.3, 969–1014.
Garcia, F., Bertoa, M. F., Calero, C., Vallecillo, A., Ruiz, F., Piattini, M., & Genero, M. (2006). Towards a consistent terminology for software measurement. Information and Software Technology, 48(8), 631–644.
Garcia, F., Ruiz, F., Calero, C., Bertoa, M. F., Vallecillo, A., Mora, B., & Piattini, M. (2009). Effective use of ontologies in software measurement. Knowledge Eng. Review, 24(1), 23–40.
Garcia, F., Serrano, M., Cruz-Lemus, J., Ruiz, F., Piattini, M., & ALARCOS Research Group. (2007). Managing software process measurement: a metamodel-based approach. Information Sciences, 177(12), pp. 2570–2586.
Georgiadoui, E. (2003). GEQUAMO–a generic, multilayered, customizable software quality model. Software Quality Journal, 11(4), 313–323. https://doi.org/10.1023/A:1025817312035
Grady, R. B. (1992). Practical software metrics for project management and process improvement. Prentice Hall.
Haaland, K., Groven, A.K., Regnesentral, N., Glott, R., Tannenberg, A., & FreeCode, A.S. (2010). Free/libre open source quality models–a comparison between two approaches. 4th FLOS International Workshop on Free/Libre/Open Source Software, (pp. 1–17).
Hauge, O., Osterlie, T., & Sorensen, C. F. (2009). An empirical study on selection of open source software–preliminary results. ICSE Workshop on Emerging Trends in Free/Libre/Open Source Software Research and Development. IEEE.
Hasnain, S., Ali, M. K., Akhter, J., Ahmed, B., & Abbas, N. (2020). Selection of an industrial boiler for a soda-ash production plant using analytical hierarchy process and TOPSIS approaches. Case Studies in Thermal Engineering, 19, 100636.
Henderson-Sellers, B., & Bulthuis, A. (1996). COMMA: Sample metamodels. JOOP, 9(7), 44–48.
Hwang, C. L., & Yoon, K. (1981). Multiple attribute decision making: Methods and applications. Springer-Verlag.
Işıklar, G., & Büyüközkan, G. (2007). Using a multi-criteria decision making approach to evaluate mobile phone alternatives. Computer Standards & Interfaces, 29(2), 265–274.
IEEE. (1998). Standard for a Software Quality Metrics Methodology. IEEE Standards, (pp. 1061–1998).
IEEE 610.12. (1990). IEEE Standard Glossary of Software Engineering Terminology.
ISO/IEC 9126–1. (2001). Software Engineering - Product Quality - Part 1: Quality Model, International Organization for Standardization, Geneva, Switzerland.
ISO/IEC 15939. (2007). Software engineering – software measurement process, second edition.
ISO/IEC 25010. (2008). Software Engineering: Software Product Quality Requirements and Evaluation (SQuaRE) Quality Model and Guide. International Organization for Standardization. Geneva, Switzerland.
ISO/IEC 14598. (1999). Information Technology, Software Product Evaluation: Process for Developers. Software Engineering.
ISO/IEC 15504–1. (2004). Information technology – Process assessment – Concepts and vocabulary.
ISO/IEC 14143–6. (2012). Information technology, Software measurement, Functional size measurement.
ISO/IEC. ISO/IEC 12207. (2008). System and software engineering – Software life-cycle processes, second edition.
ISO/IEC 19761. (2002). Software Engineering COSMIC-FFP, A functional size measurement method. International Organization for Standardization ISO, Geneva.
ISO/IEC 25020. (2019). Systems and software engineering, Systems and software Quality Requirements and Evaluation (SQuaRE), Quality measurement framework.
ISO, International Standard ISO VIM. (1993). International Vocabulary of Basic and General Terms in Metrology, International Standards Organization, Geneva, Switzerland, second edition.
Jadhav, A. S., & Sonar, R. M. (2011). Framework for evaluation and selection of the software packages: A hybrid knowledge based system approach. Journal of Systems and Software, 84(8), 1394–1407.
Jean-Christophe, D., & Alexandre, S. (2008). Comparing assessment methodologies for free/open source software: OpenBRR and QSOS. International Conference on Product Focused Software Process Improvement. Springer, Berlin, Heidelberg.
Khatri, S. K., & Singh, I. (2016). Evaluation of open source software and improving its quality. 5th International Conference on Reliability, Infocom Technologies and Optimization (ICRITO). IEEE.
Karagiannis, D., & Kühn, H. (2002). Metamodelling platforms. EC-Web, 2455, p. 182.
Khondoker, R., Zaalouk, A., Marx, R., & Bayarou, K. (2014). Feature-based comparison and selection of software defined networking (SDN) controllers. World Congress on Computer Applications and Information Systems (WCCAIS). Hammamet, Tunisia.
Kim, H. M. (1999). Representing and reasoning about quality using enterprise models. PhD thesis, Dept. Mechanical and Industrial Engineering, University of Toronto, Canad.
Kitchenham, B., Hughes, R. T., & Linkman, S. G. (2001). Modeling software measurement data. IEEE Transactions on Software Engineering, 27(9), 788–804.
Kläs, M., Lampasona, C., Nunnenmacher, S., Wagner, S., Herrmannsdörfer, M., & Lochmann, K. (2010). How to evaluate meta-models for software quality. Proceedings of the 20th International Workshop on Software Measurement.
Kuwata, Y., Takeda, K., & Miura, H. (2014). A study on maturity model of open source software community to estimate the quality of products. Procedia Computer Science, 35, 1711–171.
Lenarduzzi, V., Taibi, D., Tosi, D., Lavazza, L., & Morasca, S. (2020). Open source software evaluation, selection, and adoption: a systematic literature review. 46th Euromicro Conference on Software Engineering and Advanced Applications (SEAA). IEEE.
Maki-Asiala, P., & Matinlassi, M. (2006). Quality assurance of open source components: integrator point of view. 30th Annual International Computer Software and Applications Conference (COMPSAC'06), (Vol 2). IEEE.
Mc Call, J. A., Richards, P. K., & Walters, G. F. (1977). Factors in Software Quality, Volumes I, II, and III. US Rome Air Development Center Reports, US Department of Commerce, USA.
Mcgarry, J., Card, D., Jones, C., Layman, B., Clark, E., Dean, J., & Hall, F. (2002). Practical software measurement: objective information for decision makers. Addison Wesley.
Mens, T., Doctors, L., Habra, N., Vanderose, B., & Kamseu, F. (2011). Qualgen: Modeling and analysing the quality of evolving software systems. 15th European Conference on Software Maintenance and Reengineering. IEEE.
Miguel, J. P., Mauricio, D., & Rodríguez, G. (2014). A review of software quality models for the evaluation of software products. arXiv preprint arXiv:1412.2977.
Mohagheghi, P., & Dehlen, V. (2008). A metamodel for specifying quality models in model-driven engineering. Proceedings of the Nordic Workshop on Model Driven Engineering.
Nistala, P., Nori, K. V., & Reddy, R. (2019). Software quality models: a systematic mapping study. 2019 IEEE/ACM International Conference on Software and System Processes (ICSSP), (pp. 125–134). IEEE.
Object Management Group (OMG), Meta Object Facility (MOF). (2019). Core Specification Version 2.5.1. https://www.omg.org/spec/MOF/2.5.1/PDF
Othman, S. H., & Beydoun, G. (2010). Metamodelling approach to support disaster management knowledge sharing. 21st Australasian Conference on Information Systems.
Othman, S. H., Beydoun, G., & Sugumaran, V. (2014). Development and validation of a Disaster Management Metamodel (DMM). Information Processing & Management, 50(2), 235–271.
Orijin, A. (2006). Method for qualification and selection of open source software (QSOS) version 2.0, http://www.qsos.org/.
Özcan, E. C., Ünlüsoy, S., & Eren, T. (2017). A combined goal programming–AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants. Renewable and Sustainable Energy Reviews, 78, 1410–1423.
Petrinja, E., Sillitti, A., & Succi, G. (2010). Comparing OpenBRR, QSOS, and OMM assessment models. IFIP International Conference on Open Source Systems. Springer, Berlin, Heidelberg.
Raffoul, E., Domínguez, K., Perez, M., Mendoza, L. E., & Griman, A. C. (2008). Quality model for the selection of FLOSS-based issue tracking system. Proceedings of the IASTED international conference on software engineering, Innsbruck, Austria.
Ramamoorthy, C. V., Prakash, A., Tsai, W. T., & Usuda, Y. (1984). Software engineering: Problems and perspectives. Computer, 17(10), 191–209.
Rawashdeh, A., & Matalka, B. (2006). A new software quality model for evaluating COTS components”. Journal of Computer Science, 2(4), 373–381.
Raza, A., Capretz, L. F., & Ahmed, F. (2012). An open source usability maturity model (OS-UMM). Computers in Human Behavior, 28.4, 1109–1121.
Rossi, B., Russo, B., & Succi, G. (2012). Adoption of free/libre open source software in public organizations: factors of impact. Information Technology & People.
Rout, T. P. (1999). Consistency and conflict in terminology in software engineering standards. Proceedings 4th IEEE International Software Engineering Standards Symposium and Forum (ISESS'99).
Ruiz, F., Genero, M., García, F., Piattini, M., & Calero, C. (2003). A proposal of a software measurement ontology. Conference on Computer Science and Operational Research, Buenos Aires, Argentina.
Saaty, T. L. (1980). The analytic hierarchy process: Planning, priority setting and resource allocation. McGraw-Hill.
Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83–98.
Saaty, T. L., & Sagir, M. (2015). Ranking countries more reliably in the Summer Olympics. International Journal of the Analytic Hierarchy Process, 7(3), 589–610.
Sadeghzadeh, H. M., & Rashidi, H. (2017). Software quality models: A comprehensive review and analysis. Journal of Electrical and Computer Engineering Innovations (JECEI), 6(1), 59–76.
Samarthyam, G., Suryanarayana, G., Sharma, T., & Gupta, S. (2013). MIDAS: a design quality assessment method for industrial software. Software Engineering in Practice, (pp 911–920). San Francisco, CA, USA.
Samoladas, I., Goussios G., & Spinellis, D. (2008). The SQO-OSS quality model: measurement based open source software evaluation. IFIP international conference on open source systems. Springer, Boston, MA.
Sarrab, M., & Rehman, O. M. H. (2014). Empirical study of open source software selection for adoption, based on software quality characteristics. Advances in Engineering Software, 69, 1–11.
Siemens company, https://www.siemens.com/global/en.html
Software Engineering Institute. (2010). CMMI for development, version 1.3, Technical Report CMU/SEI-2010-TR-033.
Sohn H., Lee M. G., Seong B. M., & Kim J. B. (2015). Quality evaluation criteria based on open source mobile HTML5 UI framework for development of cross-platform. International Journal of Software Engineering and Its Applications, 9.6, 1–12.
Soto, M., & Ciolkowski, M. (2009). The QualOSS open source assessment model measuring the performance of open source communities. Proceedings of the 3rd International Symposium On Empirical Software Engineering and Measurement.
Stol, K. J., & Babar, M. A. (2010). Challenges in using open source software in product development: a review of the literature. Proceedings of the 3rd international workshop on emerging trends in free/libre/open source software research and development.
Suman, M. W., & Rohtak, M. D. U. (2014). A comparative study of software quality models. International Journal of Computer Science and Information Technologies, 5(4), 5634–5638.
Sung, W. J., Kim, J. H., & Rhew, S. Y. (2007) A quality model for open source software selection. Sixth International Conference on Advanced Language Processing and Web Information Technology (ALPIT 2007). IEEE.
Taibi, D., Lavazza, L., & Morasca, S. (2007). OpenBQR: A framework for the assessment of OSS. In: IFIP International Conference on Open Source Systems. Springer, Boston, MA.
Tanrıöver, Ö. Ö., & Bilgen, S. (2011). A framework for reviewing domain specific conceptual models. Computer Standards & Interfaces, 33(5), 448–464.
Tassone, J., Xu, S., Wang, C., Chen, J., & Du, W. (2018). Quality assessment of open source software: a review. IEEE/ACIS 17th International Conference on Computer and Information Science (ICIS) (pp. 411–416). IEEE.
Thapar, S. S., Singh, P., & Rani, S. (2012). Challenges to development of standard software quality model. International Journal of Computer Applications, 49(10).
Upadhyay, N., Despande, B. M., & Agrawal, V. P. (2011). Towards a software component quality model. International Conference on Computer Science and Information Technology, (pp. 398–412). Springer, Berlin, Heidelberg.
Van Solingen, R., Basili, V., Caldiera, G., & Rombach, H. D. (2002). Goal question metric (GQM) approach. Encyclopedia of Software Engineering.
Wagner, S., Goeb, A., Heinemann, L., Kläs, M., Lampasona, C., Lochmann, K., Mayr, A., Plösch, R., Seidl, A., Streit, J., & Trendowicz, A. (2015). Operationalised product quality models and assessment: The Quamoco approach. Information and Software Technology, 62, 101–123.
Wagner, S., Lochmann, K., Heinemann, L., Kläs, M., Trendowicz, A., Plösch, R., & Streit, J. (2012). The Quamoco product quality modelling and assessment approach. 2012 34th International Conference on Software Engineering (ICSE), (pp. 1133–1142). IEEE.
Wagner, S. (2008). Cost-optimisation of analytical software quality assurance: models, data, case studies. VDM Verlag.
Wang, X. F., Wang, J. Q., & Deng, S. Y. (2013). A method to dynamic stochastic multi-criteria decision making with log-normally distributed random variables. The Scientific World Journal.
Wang, Y., Xu, L., & Solangi, Y. A. (2020). Strategic renewable energy resources selection for Pakistan: Based on SWOT-Fuzzy AHP approach. Sustainable Cities and Society, 52, 101861.
Wasserman, M. P., Chan, C. (2006). Business Readiness Rating Project, BRR Whitepaper RFC 1, tinyurl.com/y5srd5sq.
Wasserman, A. I., Guo, X., McMillian, B., Qian, K., Wei, M. Y., & Xu, Q. (2017). OSSpal: finding and evaluating open source software. IFIP International Conference on Open Source Systems. Springer, Cham.
Yılmaz, N., & Tarhan, A.K. (2022). Quality evaluation models or frameworks for open source software: a systematic literature review. Journal of Software: Evolution and Process, 34(6):e2458. https://doi.org/10.1002/smr.2458.
Yılmaz, N., & Tarhan, A. K. (2020). Meta-models for software quality and its evaluation: a systematic literature review. International Workshop on Software Measurement and the 15th International Conference on Software Process and Product Measurement, Mexico.
Yilmaz, N., & Kolukısa Tarhan, A. (2022). Definition of the terminologies in the SQMM. Zenodo. https://doi.org/10.5281/zenodo.6367596
Zahoor, A., Mehboob, K., & Natha, S. (2017). Comparison of open source maturity models. Procedia Computer Science, 111, 348–354.
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This study was carried out as part of a PhD study pursued by the first author at the Graduate School of Science and Engineering of Hacettepe University.
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Appendices
Appendix 1 List of questions to obtain feedback from experts
Feedback on the applicability of OSS-QMM in practice | Purpose of question | |
---|---|---|
Q1 | Suppose that you would match the terms of the quality model used in your own company for software evaluation, with the terms of the OSS-QMM. Which of the meta-model terms would you match? | It is asked to see the usefulness of the concepts in our meta-model and find out if there are any unused concepts |
Q2 | As a result of the matching you performed in the previous question (Q1), are there any unused concept of our OSS-QMM? | It is asked to see if there is a missing concept in our meta-model and get feedback from experts in this context |
Q3 | Do you agree that the terms of the example OSS quality model given in Appendix 2 (derived from OSS-QMM) and the terms of the OSS-QMM are compatible with each other? | Experts are asked to derive an OSS quality model using our meta-model. Then, it is asked to get feedback on the compatibility of the model they derived with the model we derived (Appendix 2) |
Feedback on the structure of OSS-QMM | ||
Q1 | Do you agree that the mapping process is compatible with the (5-level) structure of the OSS-QMM? | It is asked to get feedback on the compatibility of the matching process with the structure of the meta-model |
Q2 | Do you agree that the classification of the OSS-QMM terms (under specification, measurement, and evaluation) are useful? | It was asked to get feedback on whether the classification process contributes to a better understanding of our meta-model and the coexistence of compatible concepts |
Q3 | Do you agree that the OSS quality models to be derived from the OSS-QMM will have homogeneous structure? | In order to benefit from the software quality modeling experiences of the experts, they are asked for their opinions on whether the structure of the models to be developed from our meta-model would be homogeneous |
Q4 | Do you agree that the OSS-QMM is understandable? | Experts are asked whether the developed meta-model was understandable and their feedback to make it more understandable |
Feedback on the content of OSS-QMM | ||
Q1 | Do you agree that the OSS-QMM is sufficiently general to describe any existing OSS quality model that you already know? (e.g., OSMM, SQO-OSS, and QualOSS)? | Experts are asked to derive an existing OSS quality model they know using our meta model. Then, it is asked whether there were deficiencies in our model |
Q2 | Do you agree that that relationship between concepts is compatible? | It is asked to get feedback on whether the relationships used between concepts were compatible with the concepts and the structure of our meta-model |
Q3 | Do you agree that the OSS-QMM is complete? | Considering the structure of the meta-model, its concepts, and the relationships among them, it was asked to get feedback on whether quality models derived from our meta-model address all aspects of OSS products (e.g., code-based and community-based aspects) |
Appendix 2 The new operationalized quality model derived from OSS-QMM
Appendix 3 Matching concepts of OSS-QMM and existing OSS quality models (OSMM, OpenBRR, and SQO-OSS)
OSS-QMM concepts | Quality models terms | ||||
---|---|---|---|---|---|
Quality model | OSMM | OpenBRR | SQO-OSS | ||
Viewpoint | Developer | Developer | Developer | ||
OSS aspect | Community-based | Code-based | Community-based | Code-based | Community-based |
Information need | Calculation of developer size to evaluate maintainability | Calculation of fault proneness to evaluate maintainability | Calculation of developer productivity to evaluate maintainability | Calculation of comment frequency to evaluate maintainability | Calculation of documentation quality to evaluate maintainability |
Characteristic | Maintainability | Maintainability | Maintainability | Maintainability | Maintainability |
Sub-characteristic | Acceptance | Product quality | Product quality | Analyzability | Analyzability |
Entity | Developer | Source code | Contributor | Source code | Contributor |
Quality requirement | The large size of developer is desirable for maintainability | The low error proneness of the source code is desirable for maintainability | The productive developers are desirable for maintainability | The high comment frequency is desirable for maintainability | The large number of documents is desirable for maintainability |
Impact | Positive | Negative | Positive | Positive | Positive |
Measurable concepts | The size of developer | The fault proneness of source code | Productivity of contributors | Complexity of source code | Completeness of documentation |
Measure | Number of developers (Base measure) | Defect density (Derived measure) | Number of releases (Base measure) | Weighted method per class (WMC) (Base measure) | Number of documents (Base measure) |
Unit | Developer | Defects, lines | Release | Methods | Documents |
Scale | Integer from zero to five (The score (1–5) is assigned w.r.t. rules given in OSMM) | Integer from zero to three (The score (1–3) is assigned w.r.t. rules given in OpenBRR) | Integer from zero to three (The score (1–3) is assigned w.r.t. rules given in OpenBRR) | Integer from zero to infinity | Integer from zero to infinity |
Measurement method | Manually | Automatically (e.g., Understand scitool, CKJM, Intellij IDEA, etc.) | Manually | Automatically (e.g., Understand scitool, CKJM, Intellij IDEA, etc.) | Manually |
Measurement function | There is no measurement function because it is a base measure | Number of defects/LOC | There is no measurement function because it is a base measure | There is no measurement function because it is a base measure | There is no measurement function because it is a base measure |
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Yılmaz, N., Tarhan, A.K. Matching terms of quality models and meta-models: toward a unified meta-model of OSS quality. Software Qual J 31, 721–773 (2023). https://doi.org/10.1007/s11219-022-09603-3
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DOI: https://doi.org/10.1007/s11219-022-09603-3