Abstract
We must pay attention and find defects, defects through the prediction to quantify the quality management and quality in order to achieve this goal, requires an estimate of the various defect detection process. Software defects are the departure of software are products’ anticipative function. This paper collecting the data of the software defects, then, using the SVM model the predictive values are gained analyzing the predictive results, software are organizations can improve software control measure software process and allocate testing resources effectively.
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References
Jalote, P.: CMM in Practice-Processes for Executing Software Projects at Infosys, pp. 94–95, 172–175. Electronic Industry Press, Beijing (2002)
Zhi, S.: Knowledge Discovery, pp. 7–8, 213–215. Tsinghua University Press, Beijing (2002)
Yang, J.-E., Wei, C.: China. Based on support vector machine safety input demand forecasting research. Coal Economic Research 9, 84–85 (2009)
Lin, Z.X., Wei, L., Bo, X.C.: The new discrete time-varying delay system stability condition. Journal of Northeast Normal University 3, 31–36 (2008)
Bennett, K.P., Campbell, C.: Support Vector Machines: Hype or Hallelujah? SIGKDD Explorations 2(2), 1–6 (2000)
Barabino, N., Pallavicini, M., Petrolini, A.: Support vector machines vs multi-layer perceptrons in particle identification. In: Proceedings of the European Sympostium on Artifical Neural Networks’99, pp. 257–262. D-Facto Press, Belgium (1999)
International Standards Organization, Information Technology-Software Product Evaluation-Quality Characteristics and Guidelines for Their Use. ISO/IEC IS9126,Geneva (1991)
Kan, S.H.: Metrics and Models in Software Quality Engineering. Addison-Wesley, Reading (1995)
Musa, J.D., Iannino, A., Okumoto, K.: Software Reliability-Measurement, Predication, Application. McGraw Hill, New York (1987)
Grady, R., Caswell, D.: Software Metrics: Establishing a Company-wide Program. Prentice Hall, Englewood Cliffs (1987)
Grady, R.: Practical Software Metrics for Project Management and Process Improvement. Prentice Hall PTR, Englewood Cliffs (1992)
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Liu, Gj., Wang, Wy. (2010). Research on an Educational Software Defect Prediction Model Based on SVM. In: Zhang, X., Zhong, S., Pan, Z., Wong, K., Yun, R. (eds) Entertainment for Education. Digital Techniques and Systems. Edutainment 2010. Lecture Notes in Computer Science, vol 6249. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14533-9_22
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DOI: https://doi.org/10.1007/978-3-642-14533-9_22
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