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Software Metrics in Static Program Analysis

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Formal Methods and Software Engineering (ICFEM 2010)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 6447))

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Abstract

Software metrics play an important role in the management of professional software projects. Metrics are used, e.g., to track development progress, to measure restructuring impact and to estimate code quality. They are most beneficial if they can be computed continuously at development time. This work presents a framework and an implementation for integrating metric computations into static program analysis. The contributions are a language and formal semantics for user-definable metrics, an implementation and integration in the existing static analysis tool , and a user-definable visualization approach to display metrics results. Moreover, we report our experiences on a case study of a popular open source code base.

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References

  1. Badri, L., Badri, M.: A proposal of a new class cohesion criterion: An empirical study. Journal of Object Technology 3(4), 145–159 (2004)

    Article  MathSciNet  Google Scholar 

  2. Clark, J., DeRose, S.: XML Path Language 1.0 (XPath). W3C (1999), http://www.w3.org/TR/xpath

  3. Clarke, E.M., Grumberg, O., Peled, D.A.: Model Checking. MIT Press, Cambridge (1999)

    Google Scholar 

  4. Curtis, B., Sheppard, S.B., Milliman, P.: Third time charm: Stronger prediction of programmer performance by software complexity metrics. In: Proceedings of the Fourth International Conference on Software Engineering, pp. 356–360. IEEE Computer Society Press, Los Alamitos (1979)

    Google Scholar 

  5. Elshoff, J.: An analysis of some commercial PL/I programs. IEEE Transactions on Software Engineering SE-5(2), 113–120 (1976)

    Article  Google Scholar 

  6. Fehnker, A., Huuck, R., Jayet, P., Lussenburg, M., Rauch, F.: Model Checking Software at Compile Time. In: Proceedings of the 1st International Symposium on Theoretical Aspects of Software Engineering, Shanghai, China (2007)

    Google Scholar 

  7. Ferzund, J., Ahsan, S.N., Wotawa, F.: Empirical evaluation of hunk metrics as bug predictors. In: Abran, A., Braungarten, R., Dumke, R.R., Cuadrado-Gallego, J.J., Brunekreef, J. (eds.) IWSM 2009. LNCS, vol. 5891, pp. 242–254. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  8. IBM: In pursuit of code quality: Code quality for software architects, Website http://www.ibm.com/developerworks/java/library/j-cq04256/ (visited on February 3, 2010)

  9. IEEE: IEEE Standard for a Software Quality Metrics Methodology. Institute of Electrical and Electronics Engineers (1061)

    Google Scholar 

  10. Martin, R.C.: Agile software development: principles, patterns, and practices. Alan Apt series. Prentice-Hall, Englewood Cliffs (2003)

    Google Scholar 

  11. McCabe, T.J.: A complexity measure. IEEE Transactions on Software Engineering 2(4), 308–320 (1976)

    Article  MathSciNet  MATH  Google Scholar 

  12. McConnell, S.: Code Complete: A Practical Handbook of Software Construction. Microsoft Press, Redmond (1993)

    Google Scholar 

  13. Misra, S.C., Bhavsar, V.C.: Relationships between selected software measures and latent bug-density: Guidelines for improving quality. In: Kumar, V., Gavrilova, M.L., Tan, C.J.K., L’Ecuyer, P. (eds.) ICCSA 2003. LNCS, vol. 2667, pp. 724–732. Springer, Heidelberg (2003)

    Chapter  Google Scholar 

  14. Nagappan, N., Ball, T., Zeller, A.: Mining metrics to predict component failures. In: ICSE 2006: Proceedings of the 28th International Conference on Software Engineering, pp. 452–461. ACM, New York (2006)

    Google Scholar 

  15. The Standish Group: Chaos report (2009), Website http://www1.standishgroup.com/newsroom/chaos_2009.php (visited on February 25, 2010)

  16. Vistein, M., Ortmeier, F., Reif, W., Huuck, R., Fehnker, A.: An abstract specification language for static program analysis. Electr. Notes Theor. Comput. Sci. 254, 181–197 (2009)

    Article  Google Scholar 

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Vogelsang, A., Fehnker, A., Huuck, R., Reif, W. (2010). Software Metrics in Static Program Analysis. In: Dong, J.S., Zhu, H. (eds) Formal Methods and Software Engineering. ICFEM 2010. Lecture Notes in Computer Science, vol 6447. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16901-4_32

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  • DOI: https://doi.org/10.1007/978-3-642-16901-4_32

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16900-7

  • Online ISBN: 978-3-642-16901-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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