The amount of e-information available has increased greatly over the past few decades. As the vast amount of information is available for every theme on Internet, shortening the information in the form of summary would immensely benefit readers. Hence, the natural language processing research community is developing new methods for summarizing the text mechanically. Automatic text summarization system produces a summary, i.e. short length text that includes all the significant information for the article. This paper presents a comprehensive survey of contemporary text summarization of extractive and abstractive approaches.

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Principal component analysis is one of the dimension reduction methods with the goal of using the correlation structure among the predictor variables. Qualitative/quantitative measurement of software quality related aspects in all stages of software development are desirable [9,10,11,12].Any measurement using any element in the software metrics is helpful for analysis in the set of software quality metrics. In this paper seventeen software metric variables [4], are considered. Four cases are carried out using principle component analysis. First analysis is with size as predominant factor. Second analysis is with effort as predominant factor. Third analysis is with duration as predominant factor. Finally all the three association taken together used for analysis of quality performance. The analysis of variables is to identify the dimension that are latent [7,8].