Sumanth Yenduri

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In this paper, we conduct an experimental study over two groups of students comprising of undergraduate students (seniors) who develop software using the conventional way of performing unit testing after development and also by extracting test cases before implementation as in Agile Programming. Both groups developed the same software using an incremental(More)
We consider the improvement in accuracy of latent semantic analysis when a part of speech tagger is used to augment a term/document matrix. We first construct an augmented term/document matrix as input into singular value decomposition (SVD). The singular values then serve as principal components for a cosine projection. The results show that the addition(More)
In this study, we compare the performance of four different imputation strategies ranging from the commonly used Listwise Deletion to model based approaches such as the Maximum Likelihood on enhancing completeness in incomplete software project data sets. We evaluate the impact of each of these methods by implementing them on six different real-time(More)
to improve the performance of document library searches. We show that latent semantic analysis, augmented with a Part–of–Speech Tagger, may be an effective algorithm for classifying a textual document as well. Using Brille’s Part–of–Speech Tagger, we truncate the singular value decomposition used in latent semantic analysis to reduce the size of the(More)
The node capture attack in wireless sensor networks (WSNs) can be decomposed into three stages: physically capture of node, redeployment of compromised node, and rejoin the network for various insider attacks. A well accepted belief — that the physical capture is easy to implement and that its detection is difficult — has directed majority of(More)
In this paper, we demonstrate the use of a simplistic time based routing protocol called Simple Resilient Multi-hop Routing (SRMR) for a multi sink wireless sensor network (WSN). SRMR will allow the network to maximize efficiency by using a combination of performance metrics. For this simulation we will use the approximate distance measure based upon travel(More)
In this study, we compare the performance of four different imputation strategies ranging from the commonly used Listwise Deletion to model based approaches such as the Max19 imum Likelihood on enhancing completeness in incomplete software project data sets. We evaluate the impact of each of these methods by implementing them on six different 21 real-time(More)