Name
Abstract | ||
|---|---|---|
The software engineering is comparatively new and ever changing field. The challenge of meeting tight project schedules with quality software requires that the field of software engineering be automated to large extent and human intervention be minimized to optimum level. To achieve this goal the researchers have explored the potential of machine learning approaches as they are adaptable, have learning capabilities and non-parametric. In this paper, we take a look at how Neural Network (NN) can be used to build tools for software development and maintenance tasks. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-00405-6_17 | Communications in Computer and Information Science |
Keywords | Field | DocType |
Neural Network,Software Testing,Software Metrics | Systems engineering,Software engineering,Computer science,Software project management,Software verification and validation,Software construction,Software development,Software sizing,Search-based software engineering,Social software engineering,Software requirements | Conference |
Volume | ISSN | Citations |
31 | 1865-0929 | 2 |
PageRank | References | Authors |
0.38 | 20 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yogesh Singh | 1 | 2 | 0.38 |
| Pradeep Kumar Bhatia | 2 | 72 | 6.00 |
| Arvinder Kaur | 3 | 370 | 26.99 |
| Omprakash Sangwan | 4 | 32 | 2.12 |