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Do Internal Software Quality Tools Measure Validated Metrics?

Part of the Lecture Notes in Computer Science book series (LNPSE,volume 11915)

Abstract

Internal software quality determines the maintainability of the software product and influences the quality in use. There is a plethora of metrics which purport to measure the internal quality of software, and these metrics are offered by static software analysis tools. To date, a number of reports have assessed the validity of these metrics. No data are available, however, on whether metrics offered by the tools are somehow validated in scientific studies. The current study covers this gap by providing data on which tools and how many validated metrics are provided. The results show that a range of metrics that the tools provided do not seem to be validated in the literature and that only a small percentage of metrics are validated in the provided tools.

Keywords

  • Software metrics tools
  • Static analysis tools
  • Metrics
  • Attributes

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Fig. 1.

Notes

  1. 1.

    https://scholar.google.se/.

  2. 2.

    http://ieeexplore.ieee.org.

  3. 3.

    http://www.sciencedirect.com.

  4. 4.

    http://www.springer.com.

  5. 5.

    https://www.engineeringvillage.com.

  6. 6.

    https://www.qa-systems.com.

  7. 7.

    https://www.scitools.com.

  8. 8.

    https://www.cppdepend.com.

  9. 9.

    https://www.sonarqube.com.

  10. 10.

    http://eclipse-metrics.sourceforge.net/.

  11. 11.

    https://www.campwoodsw.com.

References

  1. Schulmeyer, G.G., McManus, J.I.: Handbook of Software Quality Assurance. Van Nostrand Reinhold Co., New York (1992)

    Google Scholar 

  2. Leveson, N.G., Turner, C.S.: An investigation of the Therac-25 accidents. Computer 26(7), 18–41 (1993)

    CrossRef  Google Scholar 

  3. ISO, I.: IEC 9126–1: Software engineering-product quality-part 1: quality model. International Organization for Standardization 21, Geneva (2001)

    Google Scholar 

  4. Nicolette, D.: Software development metrics (2015). (Electronic source)

    Google Scholar 

  5. Basili, V.R., Briand, L.C., Melo, W.L.: A validation of object-oriented design metrics as quality indicators. IEEE Trans. Softw. Eng. 22(10), 751–761 (1996)

    CrossRef  Google Scholar 

  6. Santos, M., Afonso, P., Bermejo, P.H., Costa, H.: Metrics and statistical techniques used to evaluate internal quality of object-oriented software: a systematic mapping. In: 2016 35th International Conference of the Chilean Computer Science Society (SCCC), pp. 1–11. IEEE (2016)

    Google Scholar 

  7. Carrillo, A.B., Mateo, P.R., Monje, M.R.: Metrics to evalute fuctional quality: A sistematic review. In: 7th Iberian Conference on Information Systems and Technologies (CISTI 2012), pp. 1–6. IEEE (2012)

    Google Scholar 

  8. Lincke, R., Lundberg, J., Löwe, W.: Comparing software metrics tools. In: Proceedings of the 2008 International Symposium on Software Testing and Analysis, pp. 131–142. ACM (2008)

    Google Scholar 

  9. Briand, L.C., Morasca, S., Basili, V.R.: Property-based software engineering measurement. IEEE Trans. Softw. Eng. 22(1), 68–86 (1996)

    CrossRef  Google Scholar 

  10. Ordonez, M.J., Haddad, H.M.: The state of metrics in software industry. In: Fifth International Conference on Information Technology: New Generations (ITNG 2008), pp. 453–458. IEEE (2008)

    Google Scholar 

  11. Shepperd, M., Ince, D.: Derivation and Validation of Software Metrics. Clarendon Press, Oxford (1993)

    MATH  Google Scholar 

  12. de AG Saraiva, J., De França, M.S., Soares, S.C., Fernando Filho, J., de Souza, R.M.: Classifying metrics for assessing object-oriented software maintainability: a family of metrics’ catalogs. J. Syst. Softw. 103, 85–101 (2015)

    Google Scholar 

  13. Suresh, Y., Pati, J., Rath, S.K.: Effectiveness of software metrics for object-oriented system. Procedia Technol. 6, 420–427 (2012)

    CrossRef  Google Scholar 

  14. Jabangwe, R., Börstler, J., Šmite, D., Wohlin, C.: Empirical evidence on the link between object-oriented measures and external quality attributes: a systematic literature review. Empirical Softw. Eng. 20(3), 640–693 (2015)

    CrossRef  Google Scholar 

  15. Antinyan, V., Staron, M., Sandberg, A.: Evaluating code complexity triggers, use of complexity measures and the influence of code complexity on maintenance time. Empirical Softw. Eng. 22(6), 3057–3087 (2017)

    CrossRef  Google Scholar 

  16. McCabe, T.J.: A complexity measure. IEEE Trans. Softw. Eng. 4, 308–320 (1976)

    MathSciNet  CrossRef  Google Scholar 

  17. Halstead, M.H.: Elements of Software Science. Elsevier Science, New York (1977)

    MATH  Google Scholar 

  18. Henry, S., Kafura, D.: Software structure metrics based on information flow. IEEE Trans. Softw. Eng. 5, 510–518 (1981)

    CrossRef  Google Scholar 

  19. Chidamber, S.R., Kemerer, C.F.: A metrics suite for object oriented design. IEEE Trans. Softw. Eng. 20(6), 476–493 (1994)

    CrossRef  Google Scholar 

  20. Antinyan, V., et al.: Identifying risky areas of software code in agile/lean software development: an industrial experience report. In: 2014 Software Evolution Week-IEEE Conference on Software Maintenance, Reengineering, and Reverse Engineering (CSMR-WCRE), pp. 154–163. IEEE (2014)

    Google Scholar 

  21. Tenny, T.: Program readability: procedures versus comments. IEEE Trans. Softw. Eng. 14(9), 1271–1279 (1988)

    CrossRef  Google Scholar 

  22. Buse, R.P., Weimer, W.R.: Learning a metric for code readability. IEEE Trans. Softw. Eng. 36(4), 546–558 (2010)

    CrossRef  Google Scholar 

  23. Alzahrani, M., Melton, A.: Defining and validating a client-based cohesion metric for object-oriented classes. In: 2017 IEEE 41st Annual Computer Software and Applications Conference (COMPSAC), vol. 1, pp. 91–96. IEEE (2017)

    Google Scholar 

  24. Shepperd, M., Ince, D.C.: A critique of three metrics. J. Syst. Softw. 26(3), 197–210 (1994)

    CrossRef  Google Scholar 

  25. Fenton, N.E., Neil, M.: Software metrics: roadmap. In: Proceedings of the Conference on the Future of Software Engineering, pp. 357–370. ACM (2000)

    Google Scholar 

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Nilson, M., Antinyan, V., Gren, L. (2019). Do Internal Software Quality Tools Measure Validated Metrics?. In: Franch, X., Männistö, T., Martínez-Fernández, S. (eds) Product-Focused Software Process Improvement. PROFES 2019. Lecture Notes in Computer Science(), vol 11915. Springer, Cham. https://doi.org/10.1007/978-3-030-35333-9_50

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  • DOI: https://doi.org/10.1007/978-3-030-35333-9_50

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