Performance Indicators Analysis in Software Processes Using Semi-supervised Learning with Information Visualization

Software development process requires judicious quality control, using performance indicators to support decision-making in the different processes chains. This paper recommends the use of machine learning with the semi-supervised algorithms to analyze these indicators. In this context, this paper proposes the use of visualization techniques of multidimensional information to support the labeling process of samples, increasing the reliability of the labeled indicators (group or individual). The experiments show analysis from real indicators data of a software development company and use the algorithm bioinspired Particle Competition and Cooperation. The information visualization techniques used are: Least Square Projection, Classical Multidimensional Scaling and Parallel Coordinates. Those techniques help to correct the labeling process performed by specialists (labelers), enabling the identification of mistakes in order to improve the data accuracy for application of the semi-supervised algorithm.

[1]  Rosane Minghim,et al.  Improved Similarity Trees and their Application to Visual Data Classification , 2011, IEEE Transactions on Visualization and Computer Graphics.

[2]  R. Kaplan,et al.  The balanced scorecard--measures that drive performance. , 2015, Harvard business review.

[3]  Marcos Kalinowski,et al.  Results of 10 Years of Software Process Improvement in Brazil Based on the MPS-SW Model , 2014, 2014 9th International Conference on the Quality of Information and Communications Technology.

[4]  Rosane Minghim,et al.  On Improved Projection Techniques to Support Visual Exploration of Multi-Dimensional Data Sets , 2003, Inf. Vis..

[5]  M. Moraes,et al.  Utilização de redes neurais artificiais para avaliação socioeconômica: uma aplicação em cooperativas , 2006 .

[6]  Witold Pedrycz,et al.  Particle Competition and Cooperation in Networks for Semi-Supervised Learning , 2012, IEEE Trans. Knowl. Data Eng..

[7]  Danilo Medeiros Eler,et al.  Hybrid Visualization: A New Approach to Display Instances Relationship and Attributes Behaviour in a Single View , 2015, 2015 19th International Conference on Information Visualisation.

[8]  Danilo Medeiros Eler,et al.  Visual analysis of image collections , 2009, The Visual Computer.

[9]  Stanley T. Birchfield,et al.  Microphone array position calibration by basis-point classical multidimensional scaling , 2005, IEEE Transactions on Speech and Audio Processing.

[10]  W. Torgerson,et al.  Multidimensional scaling of similarity , 1965, Psychometrika.

[11]  Haim Levkowitz,et al.  Least Square Projection: A Fast High-Precision Multidimensional Projection Technique and Its Application to Document Mapping , 2008, IEEE Transactions on Visualization and Computer Graphics.