Finding Similar Files Using Text Mining

IET Software, 2008

2008 Third International Conference on Digital Information Management, 2008

In software development, many kinds of knowledge are shared and reused as software patterns. However, the relation analysis among software patterns by hand is difficult on the large scale. In this paper, we propose a technique for the automatic relation analysis among the patterns. Our technique is based on a new pattern model to treat various patterns, and utilizes exiting text processing techniques to extract patterns from documents and to calculate the strength of pattern relations. As a result of experiments, the system that implements our technique has extracted appropriate relations among patterns without information on relations described in original pattern documents. Moreover, our system has the ability to suggest relations among patterns that the author has not noticed.

2014

The Information Retrieval method is used to produce the traceability links between the source code and documentation. Here we use a IR approach to establish a traceability links between these two. When we develop a software system and documentation for this system. After the delivery of the software if there is any change in the source code which is to be change by the developer as the same time he forget to make a change into the documentation in this case we use above software and the use with Information Retrieval to establish a traceability links between the source code and the documentation. This result to faster efficient traceability links formation and states a traceability links and show that this source code is identical for this documentation. Here we propose a method with three models, First model is the text normalization model, second is Query Extraction Model and the third is Document Classifier with the help of the document classifier we classify the document and the...

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

IRA-International Journal of Technology & Engineering (ISSN 2455-4480), 2017

Proceedings of the Institute for System Programming of the RAS, 2017

Lecture Notes in Computer Science, 2007

2000

Abstract The paper describes the results of applying Latent Semantic Analysis (LSA), an advanced information retrieval method, to program source code and associated documentation. Latent semantic analysis is a corpus based statistical method for inducing and representing aspects of the meanings of words and passages (of natural language) reflective in their usage. This methodology is assessed for application to the domain of software components (ie, source code and its accompanying documentation).