| Autor: |
S, Saju Sankar, S S, Vinod Chandra |
| Jazyk: |
angličtina |
| Rok vydání: |
2020 |
| Předmět: |
|
| Zdroj: |
Advances in Swarm Intelligence |
| Popis: |
Path testing is the most needed and useful coverage criterion in structural testing. Tracing and obtaining the resultant paths is the main problem in path coverage testing. Evolutionary techniques are adopted in many software product evaluation methods such as generating and selection of input test data. The priority of the feasible paths is also to be determined. In this paper, we proposes an optimization algorithm for identifying the effective test data execution paths in control flow graph for the program module under test and finding the most efficient test paths using modified smell detection agent based optimization algorithm. New innovations are being conducted for bio-motivated algorithmic techniques from the characteristics of animal behavior. Smell detection agent based algorithm helps to identify most feasible paths and it uses sequential search to obtain all paths in a graph. The tester achieves the paths to be tested through a number of smell spot values from the source node to the target node. We will use control flow graph to produce perfect test paths and cyclomatic complexity number for obtaining the number of feasible test paths. The best feasible paths are prioritized using smell detection agent algorithm such that all the paths are thoroughly tested which ensures structural testing. This algorithm generates paths equal to the cyclomatic complexity. It can be illustrated that the proposed approach guarantees full path coverage. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
