Abstract
This paper provides a study of several process metrics of an industrial large-scale embedded software system, the Lucent product Lambda-UniteTM MSS. This product is an evolutionary hardware/software system for the metropolitan and wide-area transmission and switching market. An analysis of defect data is performed, including and comparing all major (i.e. feature) releases till end of 2004. Several defect metrics on file-level are defined and analyzed, as basis for a defect prediction model. Main analysis results include the following. Faults and code size per file show only a weak correlation. Portion of faulty files per release tend to decrease across releases. Size and error-proneness in previous release alone is not a good predictor of a file’s faults per release. Customer-found defects are strongly correlated with pre-delivery defects found per subsystem. These results are being compared to a recent similar study of fault distributions; the differences are significant.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Lucent Technologies: LambdaUniteTM MultiService Switch (MSS) product description, Online at http://www.lucent.com/solutions/core_optical.html
Leszak, M., Brunck, W., Moessler, G.: Analysis of Software Defects in a Large Evolutionary Telecommunication System. In: 12th Int. Workshop on Software Measurement (IWSM), Magdeburg, Germany. Shaker Publ. (2002)
Fenton, N.E., Ohlson, N.: Quantitative Analysis of Faults and Failures in a Complex Software System. IEEE Trans. on SW Engineering 26(8), 797–814 (2000)
Hartman, P.: Utility of Popular Software Defect Models. In: Proc. IEEE Reliability and Maintainability Symposium (2002)
Gana, A., Huang, S.T.: Statistical Modeling Applied to Managing Global 5ESS-2000 Switch Software Development. Bell Labs Techn. Journal, 144–153 (Winter 1997)
Leszak, M., Perry, D.E., Stoll, D.: A Case Study in Root Cause Defect Analysis. In: IEEE International Conference on Software Engineering (ICSE-22), Limerick/Ireland (June 2000)
Leszak, M.: Practical Product and Process Measurement - Lessons Learned from 6 Years of Experience. DASMA Software Metrik Kongress (MetriKon 2001), Dortmund, Germany (October 2001)
Leszak, M., Perry, D.E., Stoll, D.: Classification and Evaluation of Defects in a Project Retrospective. Journal of Systems and Software 61(3), 173–187 (2002)
Stoll, D., Leszak, M., Heck, T.: Measuring Process and Product Characteristics of Software Components - A Case Study. In: 3rd Conf. on Quality Engineering in Software Technology (Conquest), Nuernberg, Germany (September 1999)
Li, P.L., Shaw, M., Herbsleb, J.D.: Selecting a Defect Prediction Model for Maintenance Resource Planning and Software Insurance. In: Position paper for the Fifth Workshop on Economics-Driven Software Research (EDSER-5), affiliated with the 25th International Conference on Software Engineering (2003), Online at http://www-2.cs.cmu.edu/%7ECompose/li%2Bedser5.pdf
Li, P., Shaw, M., Herbsleb, J., Ray, B., Santhanam, P.: Empirical Evaluation of Defect Projection Models for Widely-deployed Production Software Systems. In: ACM Symposium on the Foundations of Software Engineering (2004)
Ostrand, T.J., Weyuker, E.J.: The distribution of faults in a large industrial software system. In: ACM SIGSOFT Int. Symp. on Software Testing and Analysis (2002)
Ostrand, T.J., Weyuker, E.J., Bell, R.M.: Where the bugs are. In: ACM SIGSOFT Int. Symp. on Software Testing and Analysis (2004)
Ostrand, T.J., Weyuker, E.J.: A Tool for Mining Defect-Tracking Systems to Predict Fault-Prone Files. In: Proc. MSR 2004: International Workshop on Mining Software Repositories, affiliated with the 26th International Conference on Software Engineering (2004), Online at http://msr.uwaterloo.ca/papers/Ostrand.pdf
Denaro, G., Pezzè, M.: Software evaluation: An empirical evaluation of fault-proneness models. In: IEEE 24th Int. Conference on Software Engineering (2002)
Mockus, A., Weiss, D.M., Zhang, P.: Understanding and predicting effort in software projects. In: IEEE 25th Int. Conference on Software Engineering, Portland, Oregon (May 2003)
Zuse, H.: Lecture on Defect-Density, Online at http://irb.cs.tu-berlin.de/~zuse/metrics/lecture02.html
Tian, J.: Quality-Evaluation Models and Measurements. IEEE Software 21(3), 84–91 (2004)
Park, R.E.: Software Size Measurement: A Framework for Counting Source Statements. Tech. Report CMU/SEI-92-TR- 20. SEI, Carnegie Mellon Univ., Pittsburgh (1992)
Leszak, M.: The Versatility of Software Defect Prediction Models (or why it’s so hard to replicate related Case Studies). In: 14th Int. Workshop on SW Measurement (IWSM/ Metrikon), November 2004. Shaker Publ., Berlin (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Leszak, M. (2005). Software Defect Analysis of a Multi-release Telecommunications System. In: Bomarius, F., Komi-Sirviö, S. (eds) Product Focused Software Process Improvement. PROFES 2005. Lecture Notes in Computer Science, vol 3547. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11497455_10
Download citation
DOI: https://doi.org/10.1007/11497455_10
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26200-8
Online ISBN: 978-3-540-31640-4
eBook Packages: Computer ScienceComputer Science (R0)