Software Quality: Issues, Concerns and New Directions
Journal Title: INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY - Year 2013, Vol 11, Issue 8
Abstract
Software metrics and quality models have a very important role to play in measurement of software quality. A number of well-known quality models and software metrics are used to build quality software both in industry and in academia. Development of software metrics is an ongoing process with new metrics being continuously tried out. However, during our research on measuring software quality using object oriented design patterns, we faced many issues related to existing software metrics and quality models. For a particular situation of interest, any established metric can be used. If none is found to be appropriate, a new metric can be devised. In this paper, we discuss some of these issues and present our approach to software quality assessment.
Authors and Affiliations
Sarachyuth Sabbani, Kiran Kumar Reddi, S. V. Achuta Rao
Keywords
Related Articles
- EP ID EP650356
- DOI 10.24297/ijct.v11i8.3007
- Views 88
- Downloads 0
Concept and Dimensions of Web 4.0
Web 4.0 is a new evolution of the Web paradigm based on multiple models, technologies and social relationships. The concept of Web 4.0 is not totally clear and unanimous in literature, because it is composed by several d...
HYBRID TECHNIQUE FOR SOFTWARE CODE CLONE DETECTION
Software Clone detection is one of the hottest research area that helps in detecting duplicate code from an applications. The research has shown that 5% to 20% of software systems can contain duplicated code that is gene...
Voltage Flicker Parameters Estimation UsingShuffled Frog Leaping Algorithm (SFLA) andImperialistic Competitive Algorithm (ICA)
Measurement of magnitude and frequency ofthe voltage flicker is very important for monitoring and controlling voltage flicker efficiently to improve the network power quality. This paper presents two new methods for meas...
A Comparative Analysis of Feed-Forward and Generalized Regression Neural Networks for Face Recognition Using Principal Component Analysis
In this paper we give a comparative analysis of performance of feed forward neural network and generalized regression neural network based face recognition. We use different inner epoch for different input pattern accor...
A Robust High Performance Face Recognition using Decorrelation of Local Features by Discrete Cosine Transforms
This paper proposes a novel method of face recognition using de-correlation of local features using Discrete Cosine Transforms (DCT). The impulse for the proposed idea is with the fact that histograms DC constituent of l...