Abstract
In Software Product Line Engineering, concrete products of a family can be generated through a configuration process over a feature model. The configuration process selects features from the feature model according to the stakeholders' requirements. Selecting the right set of features for one product from all the available features in the feature model is a cumbersome task because 1) the stakeholders may have diverse business concerns and limited resources that they can spend on a product and 2) features may have negative and positive contributions on different business concern. Many configurations techniques have been proposed to facilitate software developers' tasks through automated product derivation. However, most of the current proposals for automatic configuration are not devised to cope with business oriented requirements and stakeholders' resource limitations. We propose a framework, which employs an artificial intelligence planning technique to automatically select suitable features that satisfy the stakeholders' business concerns and resource limitations. We also provide tooling support to facilitate the use of our framework.
| Original language | English |
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| Title of host publication | 2011 26th IEEE/ACM International Conference on Automated Software Engineering, ASE 2011, Proceedings |
| Pages | 536-539 |
| Number of pages | 4 |
| DOIs | |
| Publication status | Published - 1 Dec 2011 |
| Externally published | Yes |
| Event | Automated Software Engineering Conference 2011 - Lawrence, United States of America Duration: 6 Nov 2011 → 12 Nov 2011 Conference number: 26th https://dl.acm.org/doi/proceedings/10.5555/2190078 (Proceedings) |
Conference
| Conference | Automated Software Engineering Conference 2011 |
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| Abbreviated title | ASE 2011 |
| Country/Territory | United States of America |
| City | Lawrence |
| Period | 6/11/11 → 12/11/11 |
| Other | 2011 26th IEEE/ACM International Conference on Automated Software Engineering ASE 2011 |
| Internet address |
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Keywords
- Artificial Intelligence
- Configuration
- Feature Model