An Intelligent Model for Software Project Risk Prediction

Software project development is a risky process with high failure rate. This paper proposes an intelligent model that can predict and control software development risks from an overall project perspective rather than focusing only on the single factor, project output. In this study, we first constructed a formal model for risk identification, and then collected actual cases from software development companies to build a risk prediction model. In order to evaluate the performance of our model, two machine learning algorithms, Artificial Neural Networks (ANN) and Support Vector Machine (SVM), are compared. The experiments show that our risk prediction model based on SVM achieves better performance in prediction.

[1]  Vladimir Vapnik,et al.  The Nature of Statistical Learning , 1995 .

[2]  Donald E. Neumann.  An Enhanced Neural Network Technique for Software Risk Analysis , 2002, IEEE Trans. Software Eng..

[3]  Abhijit S. Pandya,et al.  A neural network modeling methodology for the detection of high-risk programs , 1993, Proceedings of 1993 IEEE International Symposium on Software Reliability Engineering.

[4]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[5]  Peter B. Seddon.  A Respecification and Extension of the DeLone and McLean Model of IS Success , 1997, Inf. Syst. Res..

[6]  Taghi M. Khoshgoftaar,et al.  Application of neural networks to software quality modeling of a very large telecommunications system , 1997, IEEE Trans. Neural Networks.

[7]  Sergey M. Avdoshin,et al.  Software risk management , 2011, 2011 7th Central and Eastern European Software Engineering Conference (CEE-SECR).

[8]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[9]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[10]  Suresh L. Konda,et al.  Taxonomy-Based Risk Identification , 1993 .

[11]  Arthur B. Pyster.  What Beyond CMMI Is Needed to Help Assure Program and Project Success? , 2005, ISPW.

[12]  Steve McConnell,et al.  Software Project Survival Guide , 1997 .

[13]  Deepti Verma,et al.  Large Scale Project Management “Risk Management” , 2011 .

[14]  Leon J. Osterweil,et al.  Unifying Microprocess and Macroprocess Research , 2005, ISPW.

[15]  Mark Keil,et al.  Understanding software project risk: a cluster analysis , 2004, Inf. Manag..

[16]  Robert N. Charette,et al.  Software Engineering Risk Analysis and Management , 1989 .

[17]  Yong Hu,et al.  A research on the appraisal framework of e-government project success , 2005, ICEC '05.

[18]  Mark Keil,et al.  Predicting information technology project escalation: A neural network approach , 2003, Eur. J. Oper. Res..