Nomi Baruah 1, Ravi Kumar 2, Dhrubajit Barman 3
1Department of Computer Science and Engineering, Dibrugarh, India
Software Cloning has grown an active area in software engineering research community yielding numerous techniques, various tools and other methods for clone detection and removal. The copying, modifying a block of code is identified as cloning as it is the most basic means of software reuse. Agile Software Development is an approach which is currently being used in various software projects, so that it helps to respond the unpredictability of building software through incremental, iterative work cadences. Software Cloning has been introduced to Agile Environment and many Agile software Development approaches are using the concept of Software Cloning. This paper discusses the various Agile Software Development approaches. It also discusses the degree to which the Software Cloning concept is being introduced in the Agile Software development approaches.
© 2015 The Authors. Published by Elsevier B. V.
Keywords: Agile Environment, FDD, Refactoring, Reuse, Scrum, Software Cloning
AN IMPROVED GRID BASED DENSITY METHODS FOR IMAGE CLUSTERING
D.V. Lalita Parameswari1, Dr. M. Seetha2, Dr. K.V.N. Sunitha3
1Sr. Asst. Professor, Dept. of CSE, GNITS, Hyderabad, India,
2Professor, Dept. of CSE, GNITS, Hyderabad, India
3Principal, BVRITH, Hyderabad, India,
Clustering plays an important role in the data mining fields. Image clustering based on partitioning methods such as PAM, CLARA and CLARANS groups set of objects based on a deviation of the Euclidean distance among the cluster representative objects. These techniques will fail to produce precise results if the data contains noise. This paper emphasizes on the clustering of the images using DBSCAN, OPTICS and Grid (STING) clustering techniques. These techniques are intended to determine the clusters of an arbitrary shape which includes cluster ordering. The hybrid approach is proposed to implement new clustering algorithms like GRID_ DBSCAN and GRID_OPTICS. The proposed method achieves fast processing time and better performance when compared with DBSCAN and OPTICS. Among these two new clustering techniques GRID_OPTICS outperforms well.
Keywords: Image clustering, density based methods, clustering accuracy, processing time.