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Measurement & Statistics

  1. Basili, V.R.; Selby, R.W.; Phillips, T.: Metric Analysis and Data Validation Across Fortran Projects. IEEE Transactions on Software Engineering, 9(1983)6, pp. 652-663
  2. Berthold, M.; Hand, D. J.: Intelligent Data Analysis. Springer Publ., 1999
  3. Bessey, A. et al.: A Few Billion Lines of Code Later - Using Static Analysis to Find Bugs in the Real World. Comm. of the ACM, 53(2010)2, S. 66-75
  4. Bowles, J & Hanczaryk, W.: Threat effects analysis: Applying FMEA to model computer system threats. Annual Reliability and Maintainability Symposium, Las Vegas, NV, USA, 2008
  5. Coupal, D.; Robillard, P.N.: Factor Analysis of Source Code Metrics. The Journal of Systems and Software, 12 (1990), pp. 263-269
  6. Coupal, D.; Robillard, P.N.: How meaningful are software metrics? Bell Canada Quality Engineering Workshop, Montreal, October 4-5, 1990
  7. Courtney, R.E.; Gustafson, D.A.: Shotgun correlations in software measures. Software Engineering Journal, January 1993, pp. 5-13
  8. Crawford, S.G.; McIntosh, A.A.; Pregibon, D.: An Analysis of Static Metrics and Faults in C Software. The Journal of Systems and Software, 5 (1985), pp. 37-45
  9. Cuadrado-Gallego, J. J.; Buglione, L.; Rejas-Muslera, R. J.; Machado-Piriz, F.: IFPUG-COSMIC Statistical Conversion. Proc. of the 34th Euromicro Conference Software Engineering and Advanced Applications (SEAA), Parma, Italy, September 3-5, 2008, S. 427-432
  10. Dao, M.; Huchard, M.; Libourel, Z.; Roume, C.; Leblanc, H.: A New Approach to Factorization - Introducing Metrics. Proc. of the Eight IEEE Symposium on Software Metrics (METRICS 2002), June 4-7, 2002, Ottawa, Canada, pp. 227-236
  11. Deept, i.V.; Ramanamurthy, N. U.: Effective Risk Management: Risk Analysis Using an Enhanced FMEA Technique. In Annual Project Management Leadership Conference, India, 2004
  12. Del Alamo, C.J.L.; Pizarro, D.A.; Pinto, R.V.: Discovery of patterns in software metrics using clustering techniques. XXXVIII Conferencia Latinoamericana En Informatica (CLEI), 2012, pp. 1 - 7
  13. Dhar, V.: Data Science and Prediction. Communications of the ACM, 56(2013)12, S. 64-73
  14. Dinesh Kumar Verma; Shishir Kumar: Emperical study of defects dependency on software metrics using clustering approach. 2015 IEEE UP Section Conference on Electrical Computer and Electronics (UPCON), p. 1-5
  15. Fehlmann, T.: Using Six Sigma for Software Project Estimation - An Application of Statistical Methods for Software Metrics. In: Büren, G.; Dumke, R.: MetriKon 2009 - Praxis der Software-Messung, Shaker Verlag, 2009, S. 153-168
  16. Fenton N.: System Construction and Analysis – A Mathematical and Logical Framework. McGraw Hill Publ., 1993
  17. Fenton, N. E.; Pfleeger, S. L.: Software Metrics - a rigorous and practical approach. Thompson Publ., 1997
  18. Fiegler, A.; Dumke, R.R.: Growth- and Entropy-based SOA Measurement - Vision and Approach in a Large Scale Environment. Proceedings of the Joint Conference of the 21st International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement (IWSM-MENSURA 2011), November 3-4, 2011, Nara, Japan, IEEE Computer Society Los Alamitos, California, Washington, Tokyo, S. 318-322
  19. Finlay, P.; Pears, R.; Connor, A. M.: Data stream mining for predicting software build outcomes using source code metrics. Information and Software Technology, 56(2014)2, pp. 183-198
  20. Florac, W. A.; Carleton, A. D.: Measuring the Software Process – Statistical Process Control for Software Process Improvement. Pearson Education, 1999 
  21. Foss, T.; Stensrud, E.; Kitchenham, B.; Myrtveit, I.: A Simulation Study of the Model Evaluation Criterion MMRE. IEEE Transactions on Software Engineering, 29(2003)11, pp. 985-995
  22. Georgieva, K.: Conducting FMEA over the Software Development Process. in Software Engineering Notes., Volume 35 (3, ACM New York), 2010, p.35.
  23. Georgieva, K.; Neumann, R.; Dumke, R.R.: Applying Human Error Assessment and Reduction Technique (HEART) in the software development process. In: A. Abran; G. Büren; R.R. Dumke; J.J. Cuadrado-Gallego; J. Münch: Applied Software Measurement. Proceedings of the joined International Conferences on Software Measurement (IWSM/MetriKon/Mensura 2010), 10.-12. November 2010, Stuttgart, Shaker Verlag Aachen, S. 617-632
  24. Georgieva, K., Neumann, R. & Dumke, R.: Failure Mode and Effect Analysis for the software team capabilities. In MetriKon 2011 - Praxis der Software-Messung. Tagungsband des DASMA Software Merik Kongresses. Kaiserslautern Shaker Verlag Aachen, 2011
  25. Georgieva, K.; Neumann, R.; Fiegler, A.; Dumke, R.R.: Validation of the model for prediction of the human performance. Proceedings of the Joint Conference of the 21st International Workshop on Software Measurement and the 6th International Conference on Software Process and Product Measurement (IWSM-MENSURA 2011), November 3-4, 2011, Nara, Japan, IEEE Computer Society Los Alamitos, California, Washington, Tokyo, S. 245-250
  26. Ghosh, R.; Naik, V. K.: Biting off Safely More than You Can Chew: Predictive Analytics for Resource Over-commit in IaaS Cloud. 2012 IEEE Fifth International Conference on Cloud Computing, IEEE Computer Society, pp. 25-32
  27. Gibbons, J. D.: Nonparametric Methods for Quantitative Analysis. Holt, Rinehart and Winston, New York, NY, USA, 1976
  28. Grimm, E.: Correlation about software complexity measures (German). Master's Thesis, TU Berlin/TU Magdeburg, 1991
  29. Guazelli, A.; Stathatos, K.; Zeller, M.: Efficient Deployment of Predictive Analytics through Open Standards and Cloud Computing. SIGKDD Explorations, 11(2015)1, pp. 32-38
  30. Hammond, K.; Varde, A. S.: Cloud Based Predictive Analytics - Text Classification, Recommender Systems and Decision Support. 2013 IEEE 13th International Conference on Data Mining Workshops, IEEE Computer Society, pp. 607-612
  31. Hanebutte, N.; Dumke, R. R.: Analyzing Software Design using a Measurable Program Design Language. Metrics News, 5(2000)2, pp. 23-33
  32. ] Juristo, N.; Moreno, A. M.: Basics of Software Engineering Experimentation. Kluwer Academic Publishers, Boston, 2003
  33. Khaddaj, S.; Horgan, G.: Factors in Software Quality for Advanced Computer Architectures. Proc. of the ESCOM 2001, April 2001, London, pp. 437-442
  34. Kitchenham, B.A.; Linkman, S.J.: Design metrics in practice. Information and Software Technology, 32(1990)4, pp. 304-310
  35. Khoshgoftaar, T.M.; Bhattacharya, B.B.; Richardson, G.D.: Predicting Software Errors, During Development, Using Nonlinear Regression Models: A Comparative Study. IEEE Transactions on Reliability, 41(1992)3, pp. 390-395
  36. Khoshgoftaar, T.M.; Munson, J.C.: Predictive Modeling Techniques of Software Quality from Software Measures. IEEE Transactions on Software Engineering, 18(1992)11, pp. 979-987
  37. Khoshgoftaar, T.M.; Panday, A.S.; Lanning, D.L.: Application of neural networks for predicting program faults. Annals of Software Engineering, 1(1995)1, pp. 141-154
  38. Kitchenham, B: Empirical Paradigm – The Role of Experiments. In: Basili et al.: Empirical Software Engineering, Springer Publ., pp. 25-32, 2007
  39. Leiss, E. L.: A Programmer’s Companion to Algorithm Analysis. Chapman & Hall Publ., 2007
  40. Levene M.; Poulovassilis, A.: Web Dynamics – Adapting to Change in Content, Size, Topology and Use. Springer Publ., 2004
  41. Li, H.F.; Cheung, W.K.: An Empirical Study of Software Metrics. IEEE Transactions on Software Engineering, 13(1987)6, pp. 697-708
  42. Lipow, M.: Number of Faults per Line Code. IEEE Transactions on Software Engineering, 5(1979)2, pp. 76-79
  43. Liu, P.; Du, Z.: E-commerce Performance Assessment Research Based on the D-S Theory and the Balanced Score Card Method. Proc. of the 2008 International Seminar on Future Information Technology and Management Engineering, IEEE Computer Press, S. 120-123
  44. Mata-Toledo, R.A.; Gustafson, D.A.: A Factor Analysis of Software Complexity Measures. The Journal of Systems and Software, 17(1992), pp. 267-273
  45. Mirseidova, S.; Atymtayeva, L.: Definition of software metrics for software project development by using fuzzy sets and logic. Joint 6th International Conference on Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012, pp. 272-276
  46. Mueller, B.: Redundancies of Metrics. in: Lehne, F.: Softwarewartung und Reengineering. DUV Publ., Wiesbaden, Germany, 1996, pp. 141-155
  47. Munson, J. C.: Software Engineering Measurement. Auerbach Publ., CRC Press, 2003
  48. Myrvold, A.: Data Analysis for Software Metrics. The Journal of Systems and Software, 12 (1990), pp. 271-274
  49. Neumann, D. E.: An Enhanced Neural Network Technique for Software Risk Analysis. IEEE Trans. Softw. Eng., vol 28, 2002, pp. 904--912.
  50. Pandian, C. R.: Software Metrics – A Guide to Planning, Analysis, and Application. CRC Press Company, 2004
  51. Peitek, N.: Exploration of Competitive Market Behavior Using Near-Real-Time Sentiment Analysis. Master Thesis, University of Magdeburg, Germany, 2014
  52. Pickard, L.M.: Analysis of Software Metrics. in: Kitchenham; Littlewood: Measurement for Software Control and Assurance. Elsevier Science Publisher Ltd, 1989, pp. 155-180
  53. Pickard, L.; Kitchenham, B.; Linkman, S.: An Investigation of Analysis Techniques For Software Datasets. Proc. of the METRICS'99, Boca Raton, Florida, November 1999, pp. 130-142
  54. Prechelt, L.: Kontrollierte Experimente in der Softwaretechnik - Potenzial und Methode. Springer-Verlag 2001
  55. Sandeep Kaur; Kanwaljeet Kaur; Navjot Kaur: An Empirical Investigation of Relationship between Software Metrics. 2015 Second International Conference on Advances in Computing and Communication Engineering, pp. 639-643
  56. Schneidewind, N. F.: Data Analysis of Software Requirements Risk. Proc. of the ESCOM 2001, April 2001, London, pp. 443-452
  57. Shatnawi, R.; Li, W.; Swain, J.; Newman, T.: Finding software metrics threshold values using ROC curves. Journal of Software Maintenance and Evolution: Research and Practice, 22(2010)1, pp. 1-16
  58. Shen, V.Y.; Yu,T., Thebaut, S.M.; Paulsen, L.R.: Identifying Error-Prone Software -- An Empirical Study. IEEE Transactions on Software Engineering, 11(1985)4, pp. 317-324
  59. Shibata, K.; Rinsaka, K.; Dohi, T.: Metrics-Based Software Reliability Models Using Non-homogeneous Poisson Processes. 17th International Symposium on Software Reliability Engineering, 2006. ISSRE '06, pp. 52 - 61
  60. Singpurwalla, N. D.; Wilson, S. P.: Statistical Methods in Software Engineering - Reliability and Risk. Springer Publ., 1999
  61. Sneed, H. M.: Estimating the Costs of Change Requests based on Impact Analysis. In: Büren et al.: MetriKon 2013 – Praxis der Software-Messung, Shaker Verlag, Aachen, 2013
  62. Stamatis, D.: Failure Mode and Effect Analysis. ASQC Quality Press, Wisconsin, 1995
  63. Torrado; N.; Wiper, M. P.; Lillo, R. E.: Software Reliability Modeling with Software Metrics Data via Gaussian Processes. IEEE Transactions on Software Engineering, 39(2013)8, pp. 1179-1186
  64. Trivedi, K. S.: Probability and Statistics with Reliability, Queuing and Computer Science Applications. John Wiley & Sons, 2002
  65. Vyas, R.; Sharma, L. K.; Vyas, O. P.; Scheider, S.: Associative Classifiers for Predictive analytics: Comparative Performance Study. Second UKSIM European Symposium on Computer Modeling and Simulation 2008, pp. 289-294
  66. Wohlin, C, Runeson, P, Höst, M, Ohlsson, M, Regnell, B, Wesslén, A.: Experimentation in Software Engineering: An Introduction. Kluwer Academic Publishers, Boston, 2000
  67. Woodfield, S.N.; Shen, V.Y.; Dunsmore, H.E.: A Study of Several Metrics for Programming Effort. The Journal of Systems and Software, (1981)2, pp. 97-103
  68. Xu, G.; Gao, Y.; Liu, F.; Chen, A.; Zhang, M.: Statistical Analysis of Software Coupling Measurement Based on Complex Networks. International Seminar on Future Information Technology and Management Engineering, 2008. FITME '08, pp. 577-581
  69. Yong, H, Juhua, C, Zhenbang, R, Liu, M & Kang, X.: A Neural Networks Approach for Software Risk Analysis. ICDMW '06: Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops, IEEE Computer Society, 2006
  70. Young, H, Juhua, C, Huang, J, Liu, M & Xie, K.: Analyzing Software System Quality Risk Using Bayesian Belief Network. GRC '07: Proceedings of the 2007 IEEE International Conference on Granular Computing, IEEE Computer Society, 2007
  71. Yuyu, Y.; Qiang, H.: Data Mining Based Measurement Method for Software Trustworthiness. International Symposium on Intelligence Information Processing and Trusted Computing (IPTC), 2010, pp. 293-296
  72. Zendler, A.; Horn, H.; Schwärtzel, H.; Plödererer, E.: Demonstrating the usage of single-case design in experimental software engineering. Information and Software Technology, 43(2001)12, pp. 681-692
  73. Zeng, D.: Crystal Balls, Statistics, Big Data, and Psychohistory: Predictive Analytics and Beyond. IEEE Intelligent Systems, 2015, pp. 2-4

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