Ebert, C.: Visualization Techniques for Analyzing and Evaluating Software Measures. IEEE Trans. Software Engineering, Vol. 18, No. 11, pp. 1029-1034, Nov. 1992. Home/Search Document Not in Database Summary Related Articles Check |
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Space-Filling Software Visualization - Baker, Eick (1995) (12 citations) (Correct)
....a limit on system size. One solution employs data visualizations [Tuf83] Tuf90] to help software engineers understand the code they are working on. Making data or graphical representations of software, known as software visualization, is wellknown and has produced useful tools for developing code [Ebe92]. Previous work in software visualization had its roots in academia and has focused on data structure and algorithm visualization. Notable examples include Baecker s seminal work on sorting [BM88] Brown s work on algorithm animation [BH92] North et al. s displays of software graphs [GKNV93] ....
Christof Ebert. Visualization techniques for analyzing and evaluating software measures. IEEE Transactions on Software Engineering, 11(18):1029--1034, 1992.
Metrics for Identifying Critical Components in Software Projects - Ebert (2001) Self-citation (Ebert) (Correct)
....techniques is shown in fig.2. The CASE environment provides defined methods and process, and holds descriptions of different products developed during the software life cycle. Multivariate statistical techniques provide feedback about relationships between components (e.g. factor analysis [8], principal component analysis [4] 6 Classification techniques help determining outliers (e.g. error prone components) 2,3,9] Finally, detailed diagrams and tables provide insight into the reasons why distinct components are potential outliers and how to improve them [8,10] Quality or ....
.... (e.g. factor analysis [8] principal component analysis [4] 6 Classification techniques help determining outliers (e.g. error prone components) 2,3,9] Finally, detailed diagrams and tables provide insight into the reasons why distinct components are potential outliers and how to improve them [8,10]. Quality or productivity factors to be predicted during the development of a software system are affected by many product and process attributes, e.g. software design characteristics or the underlying development process and its environment. In order to achieve a distinct quality goal that is ....
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Ebert, C.: Visualization Techniques for Analyzing and Evaluating Software Measures. IEEE Trans. Software Engineering, Vol. 18, No. 11, pp. 1029-1034, Nov. 1992.
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