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N. Karunanithi, D. Whitley, Y.K. Malaiya, "Prediction of Software Reliability Using Connectionist Models," IEEE Transactions on Software Engineering, vol. 18, no. 7, pp. 563574, July, 1992.  
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@article{ 10.1109/32.148475, author = {N. Karunanithi and D. Whitley and Y.K. Malaiya}, title = {Prediction of Software Reliability Using Connectionist Models}, journal ={IEEE Transactions on Software Engineering}, volume = {18}, number = {7}, issn = {00985589}, year = {1992}, pages = {563574}, doi = {http://doi.ieeecomputersociety.org/10.1109/32.148475}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Software Engineering TI  Prediction of Software Reliability Using Connectionist Models IS  7 SN  00985589 SP563 EP574 EPD  563574 A1  N. Karunanithi, A1  D. Whitley, A1  Y.K. Malaiya, PY  1992 KW  software reliability; connectionist models; network models; training regimes; data representation methods; complexity; neural nets; software reliability VL  18 JA  IEEE Transactions on Software Engineering ER   
The usefulness of connectionist models for software reliability growth prediction is illustrated. The applicability of the connectionist approach is explored using various network models, training regimes, and data representation methods. An empirical comparison is made between this approach and five wellknown software reliability growth models using actual data sets from several different software projects. The results presented suggest that connectionist models may adapt well across different data sets and exhibit a better predictive accuracy. The analysis shows that the connectionist approach is capable of developing models of varying complexity.
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