2013
DOI: 10.1145/2492248.2492270
|View full text |Cite
|
Sign up to set email alerts
|

Study of empirical approaches to analyze the software metrics

Abstract: Software affects nearly every aspect of human lives. Software functional quality is a key to achieve industrial and business relevance, in particular to industrial development and growth. Software metrics are important indicators to improve the processes and products in all organizations. They define baselines of quality and productivity and enable comparisons against industry averages that help in identifying opportunities for improvement. In addition, Software metrics design and analysis are major … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
1
0

Year Published

2021
2021
2021
2021

Publication Types

Select...
1

Relationship

0
1

Authors

Journals

citations
Cited by 1 publication
(1 citation statement)
references
References 13 publications
0
1
0
Order By: Relevance
“…Li et al 41 proposed a meticulous application of the AHP and expert opinion in choosing software reliability metrics, with relevance, experience, correctness, practicality, and feasibility as the criteria determined in their study. Pandey et al 42 explained the relationship between attributes of particular metrics with empirical approaches. Choosing the most significant attributes based on their weight values, the AHP method was used in order to help decrease the dimensionality of metrics.…”
Section: Background and Related Workmentioning
confidence: 99%
“…Li et al 41 proposed a meticulous application of the AHP and expert opinion in choosing software reliability metrics, with relevance, experience, correctness, practicality, and feasibility as the criteria determined in their study. Pandey et al 42 explained the relationship between attributes of particular metrics with empirical approaches. Choosing the most significant attributes based on their weight values, the AHP method was used in order to help decrease the dimensionality of metrics.…”
Section: Background and Related Workmentioning
confidence: 99%