Effects of measurements on correlations of software code metrics
暂无分享,去创建一个
[1] Anas N. Al-Rabadi,et al. A comparison of modified reconstructability analysis and Ashenhurst‐Curtis decomposition of Boolean functions , 2004 .
[2] Dirk Riehle,et al. The Total Growth of Open Source , 2008, OSS.
[3] Steve Counsell,et al. Power law distributions in class relationships , 2003, Proceedings Third IEEE International Workshop on Source Code Analysis and Manipulation.
[4] Alexander Serebrenik,et al. Empirical analysis of the relationship between CC and SLOC in a large corpus of Java methods and C functions , 2016, J. Softw. Evol. Process..
[5] Diomidis Spinellis,et al. Power laws in software , 2008, TSEM.
[6] Jean-Louis Letouzey,et al. Managing Technical Debt with the SQALE Method , 2012, IEEE Software.
[7] Damaris Zurell,et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance , 2013 .
[8] Laurie A. Williams,et al. Validating software metrics: A spectrum of philosophies , 2012, TSEM.
[9] Per Runeson,et al. Guidelines for conducting and reporting case study research in software engineering , 2009, Empirical Software Engineering.
[10] Joseph Gil,et al. On the correlation between size and metric validity , 2017, Empirical Software Engineering.
[11] David P. Darcy,et al. Managerial Use of Metrics for Object-Oriented Software: An Exploratory Analysis , 1998, IEEE Trans. Software Eng..
[12] Miroslaw Staron,et al. Unveiling anomalies and their impact on software quality in model-based automotive software revisions with software metrics and domain experts , 2016, ISSTA.
[13] M. Kendall,et al. Rank Correlation Methods (5th ed.). , 1992 .
[14] Yuanfang Cai,et al. A Case Study in Locating the Architectural Roots of Technical Debt , 2015, 2015 IEEE/ACM 37th IEEE International Conference on Software Engineering.
[15] Yeung Sam Hung,et al. A comparative analysis of Spearman's rho and Kendall's tau in normal and contaminated normal models , 2013, Signal Process..
[16] Andy P. Field,et al. Discovering Statistics Using SPSS , 2000 .
[17] R. Brereton,et al. Crucial problems in regression modelling and their solutions. , 2002, The Analyst.
[18] Janice Singer,et al. Studying Software Engineers: Data Collection Techniques for Software Field Studies , 2005, Empirical Software Engineering.
[19] Michele Marchesi,et al. Power-Laws in a Large Object-Oriented Software System , 2007, IEEE Transactions on Software Engineering.
[20] G. Shevlyakov,et al. Robustness in Data Analysis: Criteria and Methods , 2001 .
[21] Paul W. Oman,et al. Using metrics to evaluate software system maintainability , 1994, Computer.
[22] Norman F. Schneidewind,et al. A Methodology for Validating Software Product Metrics , 2000 .
[23] Roberto da Silva Bigonha,et al. Identifying thresholds for object-oriented software metrics , 2012, J. Syst. Softw..
[24] Yahya M. Tashtoush,et al. The Correlation among Software Complexity Metrics with Case Study , 2014, ArXiv.
[25] Rupinder Singh,et al. Better utilization of correlation between metrics using Principal Component Analysis (PCA) , 2015, 2015 Annual IEEE India Conference (INDICON).
[26] Richard Taylor. Interpretation of the Correlation Coefficient: A Basic Review , 1990 .
[27] Nicholas A. Kraft,et al. Cyclomatic Complexity and Lines of Code: Empirical Evidence of a Stable Linear Relationship , 2009, J. Softw. Eng. Appl..
[28] Ewan D. Tempero,et al. Understanding the shape of Java software , 2006, OOPSLA '06.
[29] Witold Pedrycz,et al. An Empirical Exploration of the Distributions of the Chidamber and Kemerer Object-Oriented Metrics Suite , 2004, Empirical Software Engineering.
[30] H. Park. Univariate Analysis and Normality Test Using SAS, STATA, and SPSS , 2015 .
[31] Hae-Young Kim. Statistical notes for clinical researchers: assessing normal distribution (2) using skewness and kurtosis , 2013, Restorative dentistry & endodontics.
[32] Catherine Dehon,et al. Influence functions of the Spearman and Kendall correlation measures , 2010, Stat. Methods Appl..
[33] Ahmed E. Hassan,et al. Understanding the impact of code and process metrics on post-release defects: a case study on the Eclipse project , 2010, ESEM '10.
[34] Sallie M. Henry,et al. Predicting source-code complexity at the design stage , 1990, IEEE Software.
[35] Andrea Janes,et al. A Continuous Software Quality Monitoring Approach for Small and Medium Enterprises , 2017, ICPE Companion.
[36] Yuming Zhou,et al. Examining the Potentially Confounding Effect of Class Size on the Associations between Object-Oriented Metrics and Change-Proneness , 2009, IEEE Transactions on Software Engineering.
[37] M. Kendall,et al. Rank Correlation Methods , 1949 .
[38] Laura Lehtola,et al. The challenge of release planning , 2011, 2011 Fifth International Workshop on Software Product Management (IWSPM).
[39] Rüdiger Lincke,et al. Comparing software metrics tools , 2008, ISSTA '08.
[40] Xianggui Qu,et al. Multivariate Data Analysis , 2007, Technometrics.
[41] Mehwish Riaz,et al. A systematic review of software maintainability prediction and metrics , 2009, ESEM 2009.
[42] Meine van der Meulen,et al. Correlations between Internal Software Metrics and Software Dependability in a Large Population of Small C/C++ Programs , 2007, The 18th IEEE International Symposium on Software Reliability (ISSRE '07).
[43] D. Kafura,et al. On the relationships among three software metrics , 1981, Measurement and evaluation of software quality.
[44] Charu C. Aggarwal,et al. Outlier Analysis , 2013, Springer New York.
[45] Christian Berger,et al. Correlations of software code metrics: an empirical study , 2017, IWSM-Mensura.