Chandra MouliVenkata Srinivas Akana

Work place: Department of CSE, JNTUK, Kakinada, AP, India

E-mail: mouliac@yahoo.com

Website:

Research Interests: Computer systems and computational processes, Autonomic Computing, Computer Architecture and Organization, Data Structures and Algorithms

Biography

Prof. Chandra Mouli Venkata Srinivas Akana is a graduate in Electronics from Andhra University, Visakhapatnam, Andhra Pradesh, India (1991) and an M.Tech. in Computer Science and Engineering from Guru Jambheshwar University of Science & Technology, Hisar, Haryana, India (2001). His areas of interest are Software Testing, Reliability, Quality Assurance and Cloud Computing. As a researcher, he is specializing in Software Testing at Jawaharlal Nehru Technological University, Andhra Pradesh, India. He is currently working as a Professor and Head, Department of Computer Applications, AMC Engineering College, Bengaluru, Karnataka, India. He has also served as a member of Board of Examiners-MCA under Visvesvaraya Technological University, Belagavi and as a Coordinator for BOE-MCA, VTU Practical Examinations. Prof. Akana is a member of various professional organizations such as IEEE, ISTE, IE, IAE, CSI and SSC.

Author Articles
Design of Generalized Weighted Laplacian Based Quality Assessment for Software Reliability Growth Models

By Chandra MouliVenkata Srinivas Akana C. Divakar Ch. Satyanarayana

DOI: https://doi.org/10.5815/ijitcs.2018.05.05, Pub. Date: 8 May 2018

The reliability of a software depends on the quality. So, the software growth models require efficient quality assessment procedure. It can be estimated by various parameters. The current paper proposes a novel approach for assessment of quality based on the Generalized Weighted Laplacian (GWL) method. The proposed method evaluates various parameters for detection and removal time. The Mean Value Function (MVF) is then calculated and the quality of the software is estimated, based on the detection of failures. The proposed method is evaluated on process CMMI level 5 project data and the experimental results shows the efficiency of the proposed method.

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