A Fuzzy Logic-Based Model for Classifying Software Modules in Order to Achieve Dependable Software
暂无分享,去创建一个
[1] John D. Musa,et al. Operational profiles in software-reliability engineering , 1993, IEEE Software.
[2] Claes Wohlin,et al. Software reliability prediction incorporating information from a similar project , 1999, J. Syst. Softw..
[3] Lutz Hamel,et al. Self-Organizing Map Convergence , 2018, Int. J. Serv. Sci. Manag. Eng. Technol..
[4] Subhashis Chatterjee,et al. A Mahalanobis distance based algorithm for assigning rank to the predicted fault prone software modules , 2018, Appl. Soft Comput..
[5] Cong Jin,et al. Prediction approach of software fault-proneness based on hybrid artificial neural network and quantum particle swarm optimization , 2015, Appl. Soft Comput..
[6] Subhashis Chatterjee,et al. A new fuzzy rule based algorithm for estimating software faults in early phase of development , 2016, Soft Comput..
[7] Faisal Talib,et al. Quality Evaluation of Health Care Establishment Utilizing Fuzzy AHP , 2017, Int. J. Serv. Sci. Manag. Eng. Technol..
[8] Ali Selamat,et al. An empirical study based on semi-supervised hybrid self-organizing map for software fault prediction , 2015, Knowl. Based Syst..
[9] Niclas Ohlsson,et al. Predicting Fault-Prone Software Modules in Telephone Switches , 1996, IEEE Trans. Software Eng..
[10] Karim O. Elish,et al. Predicting defect-prone software modules using support vector machines , 2008, J. Syst. Softw..
[11] Taghi M. Khoshgoftaar,et al. Ordering Fault-Prone Software Modules , 2003, Software Quality Journal.
[12] Cong Jin,et al. Artificial neural network-based metric selection for software fault-prone prediction model , 2012, IET Softw..
[13] Giulio D'Emilia,et al. Improvement of Measurement Contribution for Asset Characterization in Complex Engineering Systems by an Iterative Methodology , 2018, Int. J. Serv. Sci. Manag. Eng. Technol..
[14] Nancy G Leveson,et al. Software safety: why, what, and how , 1986, CSUR.
[15] Mohammad Azadfallah,et al. A New Entropy-Based Approach to Determine the Weights of Decision Makers for Each Criterion With Crisp and Interval Data in Group Decision Making Under Multiple Attribute , 2018, Int. J. Serv. Sci. Manag. Eng. Technol..
[16] Dilip Kumar Yadav,et al. A fuzzy logic based approach for phase-wise software defects prediction using software metrics , 2015, Inf. Softw. Technol..
[17] Gary Mcgraw. Software security , 2004, IEEE Security & Privacy Magazine.
[18] Manpreet Kaur,et al. A Study on Early Prediction of Fault Proneness in Software Modules using Genetic Algorithm , 2010 .
[19] Ajeet Kumar Pandey and N. K. Goyal,et al. A Fuzzy Model for Early Software Quality Prediction and Module Ranking , 2012 .
[20] Manjubala Bisi and Neeraj Kumar Goyal. Early Prediction of Software Fault-Prone Module using Artificial Neural Network , 2015 .
[21] Mahnaz Zarei,et al. An Integrated QFD-TOPSIS Approach for Supplier Selection Under Fuzzy Environment: A Case of Detergent Manufacturing Industry , 2018, Int. J. Serv. Sci. Manag. Eng. Technol..
[22] Danielle Azar,et al. A PSO-GA approach targeting fault-prone software modules , 2017, J. Syst. Softw..
[23] Bin Liu,et al. Software defect prediction using stacked denoising autoencoders and two-stage ensemble learning , 2017, Inf. Softw. Technol..
[24] Subhashis Chatterjee,et al. A bayesian belief network based model for predicting software faults in early phase of software development process , 2017, Applied Intelligence.