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The three soft computing techniques are compared and they are Artificial Neural Network ( ANN ) , Adaptive Neuro Fuzzy Inference System ( ANFIS ) and Support Vector machines ( SVM )
| Content Provider | Semantic Scholar |
|---|---|
| Author | Kumar, Sushant Ranjan, Prabhat |
| Copyright Year | 2018 |
| Abstract | The aim of the proposed methodology is to improve the quality and reduce the testing efforts of the software. The methodology consists of three approaches namely pre development, during development and post development. The first approach finds the fault prone module in software. The second approach finds the fault in different phases of the software development life cycle (SDLC) before the maintenance phase (post development). The third approach finds the fault in post development phase. In the pre development approach one fuzzy inference system is developed for finding the fault prone module. In during development approach fuzzy inference system is developed for four phases of SDLC (requirement, design, coding and testing) to find the total number of fault in software. In post development approach test case prioritization is developed for early fault detection. The validation is performed using promise data sets for pre development and during development phase. The benchmark example is used for post development phase. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.ripublication.com/ijaer17/ijaerv12n24_263.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
