Activity Diagram Synthesis Using Labelled Graphs And the Genetic Algorithm
- Publisher:
- Springer Verlag
- Publication Type:
- Journal Article
- Citation:
- Journal of Computer Science and Technology, 2021, 33, (1), pp. 1-23
- Issue Date:
- 2021-01-01
Closed Access
Filename | Description | Size | |||
---|---|---|---|---|---|
Activity Diagram Synthesis Using Labelled Graphs And the Genetic Algorithm.pdf | Published version | 100.35 kB |
Copyright Clearance Process
- Recently Added
- In Progress
- Closed Access
This item is closed access and not available.
Many applications need to meet diverse requirements of a large-scale distributed user group. That challenges the current requirements engineering techniques. Crowd-based requirements engineering was proposed as an umbrella term for dealing with the requirements development in the context of large-scale user group. However, there are still many issues. Among others, a key issue is when a set of requirements descriptions from different participants are received, how to merge these requirements to produce the synthesized requirements description. Appropriate techniques are needed for supporting the requirements synthesis. Diagrams are widely used in industry to represent requirements. This paper chooses the activity diagrams and proposes a novel approach for the activity diagram synthesis which adopts genetic algorithm to repeatedly modify a population of individual solutions toward an optimal solution. As a result, it can automatically generate a resulting diagram which combines the commonalities as many as possible while leveraging the variabilities of a set of input diagrams. The approach is featured by (1) the labelled graph is proposed as the representation of the candidate solutions during the iterative evolution; (2) the generalized entropy is proposed and defined as the measurement of the solutions; (3) the genetic algorithm is designed for sorting out the high-quality solution. Four cases of different scales are used to evaluate the effectiveness of the approach. The experimental results show that not only the approach gets high precision and recall but also the resulting diagram satisfies the properties of minimization and information preservation and can support the requirements traceability
Please use this identifier to cite or link to this item: