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Empirical Study on the Distribution of Object-Oriented Metrics in Software Systems

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Information and Software Technologies (ICIST 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1078))

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Abstract

We attempt to model the probability distribution of object-oriented software metrics. We employ 5 distribution models to find out the distributions the metrics follow. We use AIC, BIC and RMSE as goodness-of-fit measures. Though the past studies have shown that the software projects frequently follow power law, having a Pareto distribution, we seek to study more number of software systems and distribution models to infer more generalizable results, since they occasionally seem to follow Log-normal or Gamma distribution as well. Apart from these three models we have also considered Weibull distribution and Generalized Pareto Distribution (GPD). In this study, we have made an attempt to answer the hypothesis that the object-oriented software metrics follow a particular distribution by comparing various distributions applied over a large number of projects using a recognized statistical framework.

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References

  1. Adamic, L.A., Huberman, B.A.: Zipf’s law and the internet. Glottometrics 3(1), 143–150 (2002)

    Google Scholar 

  2. Akaike, H.: A new look at the statistical model identification. IEEE Trans. Autom. Control 19(6), 716–723 (1974)

    Article  MathSciNet  Google Scholar 

  3. Andersson, C., Runeson, P.: A replicated quantitative analysis of fault distributions in complex software systems. IEEE Trans. Soft. Eng. 33(5), 273–286 (2007)

    Article  Google Scholar 

  4. Baxter, G., Frean, M., Noble, J., Rickerby, M., Smith, H., Visser, M., Melton, H., Tempero, E.: Understanding the shape of Java software. ACM Sigplan Not. 41, 397–412 (2006)

    Article  Google Scholar 

  5. Booch, G.: Object-oriented development. IEEE Trans. Software Eng. 2, 211–221 (1986)

    Article  Google Scholar 

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

    Article  Google Scholar 

  7. Concas, G., Marchesi, M., Murgia, A., Tonelli, R., Turnu, I.: On the distribution of bugs in the eclipse system. IEEE Trans. Software Eng. 37(6), 872–877 (2011)

    Article  Google Scholar 

  8. Concas, G., Marchesi, M., Pinna, S., Serra, N.: Power-laws in a large object-oriented software system. IEEE Trans. Software Eng. 33(10), 687–708 (2007)

    Article  Google Scholar 

  9. D’Ambros, M., Lanza, M., Robbes, R.: Evaluating defect prediction approaches: a benchmark and an extensive comparison. Empirical Soft. Eng. 17(4–5), 531–577 (2012)

    Article  Google Scholar 

  10. Demšar, J.: Statistical comparisons of classifiers over multiple data sets. J. Mach. Learn. Res. 7, 1–30 (2006)

    MathSciNet  MATH  Google Scholar 

  11. Fenton, N.E., Ohlsson, N.: Quantitative analysis of faults and failures in a complex software system. IEEE Trans. Softw. Eng. 26(8), 797–814 (2000)

    Article  Google Scholar 

  12. Gibrat, R.: Les inégalités économiques: applications: aux inégalitês des richesses, à la concentration des entreprises, aux populations des villes, aux statistiques des familles, etc: d’une loi nouvelle: la loi de l’effet proportionnel. Librairie du Recueil Sirey (1931)

    Google Scholar 

  13. Grbac, T.G., Huljenić, D.: On the probability distribution of faults in complex software systems. Inf. Softw. Technol. 58, 250–258 (2015)

    Article  Google Scholar 

  14. Herraiz, I., Rodriguez, D., Harrison, R.: On the statistical distribution of object-oriented system properties. In: 2012 3rd International Workshop on Emerging Trends in Software Metrics (WETSoM), pp. 56–62. IEEE (2012)

    Google Scholar 

  15. Huang, C.Y., Kuo, C.S., Luan, S.P.: Evaluation and application of bounded generalized pareto analysis to fault distributions in open source software. IEEE Trans. Reliab. 63(1), 309–319 (2013)

    Article  Google Scholar 

  16. Jureczko, M.: Significance of different software metrics in defect prediction. Soft. Eng. Int. J. 1(1), 86–95 (2011)

    Google Scholar 

  17. Jureczko, M., Madeyski, L.: Towards identifying software project clusters with regard to defect prediction. In: Proceedings of the 6th International Conference on Predictive Models in Software Engineering, p. 9. ACM (2010)

    Google Scholar 

  18. Kolassa, C., Riehle, D., Salim, M.A.: A model of the commit size distribution of open source. In: van Emde Boas, P., Groen, F.C.A., Italiano, G.F., Nawrocki, J., Sack, H. (eds.) SOFSEM 2013. LNCS, vol. 7741, pp. 52–66. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-35843-2_6

    Chapter  Google Scholar 

  19. Kumar, L., Misra, S., Rath, S.K.: An empirical analysis of the effectiveness of software metrics and fault prediction model for identifying faulty classes. Comput. Stand. & Interfaces 53, 1–32 (2017)

    Article  Google Scholar 

  20. Lessmann, S., Baesens, B., Mues, C., Pietsch, S.: Benchmarking classification models for software defect prediction: a proposed framework and novel findings. IEEE Trans. Soft. Eng. 34(4), 485–496 (2008)

    Article  Google Scholar 

  21. Li, P.L., Shaw, M., Herbsleb, J., Ray, B., Santhanam, P.: Empirical evaluation of defect projection models for widely-deployed production software systems. ACM SIGSOFT Soft. Eng. Notes 29, 263–272 (2004)

    Article  Google Scholar 

  22. Louridas, P., Spinellis, D., Vlachos, V.: Power laws in software. ACM Trans. Soft. Eng. Methodol. (TOSEM) 18(1), 2 (2008)

    Google Scholar 

  23. Meyer, B.: Object-Oriented Software Construction, vol. 2. Prentice hall, New York (1988)

    Google Scholar 

  24. Misra, S., Adewumi, A., Fernandez-Sanz, L., Damasevicius, R.: A suite of object oriented cognitive complexity metrics. IEEE Access 6, 8782–8796 (2018)

    Article  Google Scholar 

  25. Mitzenmacher, M.: A brief history of generative models for power law and lognormal distributions. Internet Math. 1(2), 226–251 (2004)

    Article  MathSciNet  Google Scholar 

  26. Murgia, A., Concas, G., Marchesi, M., Tonelli, R., Turnu, I.: An analysis of bug distribution in object oriented systems. arXiv preprint arXiv:0905.3296 (2009)

  27. Newman, M.E.: Power laws, pareto distributions and Zipf’s law. Contemp. Phys. 46(5), 323–351 (2005)

    Article  Google Scholar 

  28. Pani, F.E., Concas, G.: Stochastic models of software development activities. In: Proceedings of WSEAS International Conference. Recent Advances in Computer Engineering Series, No. 7 (2012)

    Google Scholar 

  29. Pareto, V., Page, A.N.: Translation of manuale di economia politica (“manual of political economy”). AM Kelley, New York (1971)

    Google Scholar 

  30. Pickands III, J.: Statistical inference using extreme order statistics. Ann. Stat. 3, 119–131 (1975)

    Article  MathSciNet  Google Scholar 

  31. Shatnawi, R., Althebyan, Q.: An empirical study of the effect of power law distribution on the interpretation of OO metrics. ISRN Soft. Eng. 2013 (2013)

    Google Scholar 

  32. Shriram, C., Muthukumaran, K., Bhanu Murthy, N.: Empirical study on the distribution of bugs in software systems. Int. J. Soft. Eng. Knowl. Eng. 28(01), 97–122 (2018)

    Article  Google Scholar 

  33. Shukla, S., Radhakrishnan, T., Muthukumaran, K., Neti, L.B.M.: Multi-objective cross-version defect prediction. Soft Comput. 22(6), 1959–1980 (2018)

    Article  Google Scholar 

  34. Vose, D.: Fitting distributions to data (2010)

    Google Scholar 

  35. Wheeldon, R., Counsell, S.: Power law distributions in class relationships. In: 2003 Proceedings of 3rd IEEE International Workshop on Source Code Analysis and Manipulation, pp. 45–54. IEEE (2003)

    Google Scholar 

  36. Zhang, H.: On the distribution of software faults. IEEE Trans. Soft. Eng. 34(2), 301 (2008)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Computing and Information Technology, Manipal University Jaipur, Jaipur, India

    K. Muthukumaran

  2. Department of Computer Science and Information Systems, BITS Pilani Hyderabad Campus, Hyderabad, India

    N. L. Bhanu Murthy & P. Sarguna Janani

Authors
  1. K. Muthukumaran
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  2. N. L. Bhanu Murthy
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  3. P. Sarguna Janani
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Correspondence to K. Muthukumaran .

Editor information

Editors and Affiliations

  1. Kaunas University of Technology, Kaunas, Lithuania

    Robertas Damaševičius

  2. Kaunas University of Technology, Kaunas, Lithuania

    Giedrė Vasiljevienė

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Muthukumaran, K., Bhanu Murthy, N.L., Sarguna Janani, P. (2019). Empirical Study on the Distribution of Object-Oriented Metrics in Software Systems. In: Damaševičius, R., Vasiljevienė, G. (eds) Information and Software Technologies. ICIST 2019. Communications in Computer and Information Science, vol 1078. Springer, Cham. https://doi.org/10.1007/978-3-030-30275-7_23

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  • DOI: https://doi.org/10.1007/978-3-030-30275-7_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30274-0

  • Online ISBN: 978-3-030-30275-7

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