A Multi-instance Model for Software Quality Estimation in OO Systems

Author(s):  
Peng Huang ◽  
Jie Zhu
2005 ◽  
Vol 9 (5) ◽  
pp. 487-508 ◽  
Author(s):  
Taghi M. Khoshgoftaar ◽  
Pierre Rebours

Author(s):  
A. O. Olagunju ◽  
J. Turner ◽  
D. Richey ◽  
R. Jackson ◽  
S. Hanley ◽  
...  

2005 ◽  
Vol 13 (2) ◽  
pp. 177-193 ◽  
Author(s):  
Sousuke Amasaki ◽  
Takashi Yoshitomi ◽  
Osamu Mizuno ◽  
Yasunari Takagi ◽  
Tohru Kikuno

2020 ◽  
Vol 5 (17) ◽  
pp. 1-5
Author(s):  
Jitendrea Kumar Saha ◽  
Kailash Patidar ◽  
Rishi Kushwah ◽  
Gaurav Saxena

Software quality estimation is an important aspect as it eliminates design and code defects. Object- oriented quality metrics prediction can help in the estimation of software quality of any defects and the chances of errors. In this paper a survey and the case analytics have been presented for the object-oriented quality prediction. It shows the analytical and experimental aspects of previous methodologies. This survey also elaborates different object-oriented parameters which is useful for the same problem. It also elaborates the problem aspects as well the limitations for the future directions. Machine learning and artificial intelligence methods have been considered mostly for this survey. The parameters considered are inheritance, dynamic behavior, encapsulation, objects etc.


In this chapter, some new ideas about estimation and evaluation of the quality of software. At the outset, it deals with the possibilities of using a standard conversion method so that lines of code from any language may be compared and be used as a uniform metric. The present work is also credited through the introduction of some new terms like efficiency and variation to understand the change in software quality. The main focus is to evaluate and estimate software quality at a particular stage of software development. This is not average quality understanding, but quality estimation at a particular instance. One of the salient aspects of the method suggested is that the developer can evaluate the work at any stage using the methods given to review the present status and make future plans to meet the required target.


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