| Full text | |
| Author(s): |
Choma Neto, Joao
;
Gaieski, Tatiane F. P.
;
Amaral, Aline M. M. Miotto
;
Colanzi, Thelma Elita
;
IEEE
Total Authors: 5
|
| Document type: | Journal article |
| Source: | 2018 IEEE 30TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI); v. N/A, p. 8-pg., 2018-01-01. |
| Abstract | |
The Product Line Architecture (PLA) is one of the most important artifacts of a Software Product Line (SPL). PLA design can be formulated as an optimization problem with many factors. In this context, OPLA-Tool was developed to automatically identify the best alternatives for a PLA design using multi-objective evolutionary algorithms, based on genetic algorithms (GA). From an original PLA, OPLA-Tool obtains alternative designs to improve the original one in terms of the objectives selected for optimization. In a recent study, we extend OPLA-Tool to add a memetic algorithm (MA) and promising empirical results were obtained. However, the results allow us to hypothesize that including feature modularization as an objective to be optimized by MA could obtain even better solutions. In addition, it is interesting to know the experts' opinion about PLA designs automatically obtained, what has not been done yet. Thus, the objective of this work is twofold: to investigate the aforementioned hypothesis and to conduct the first qualitative evaluation of the PLA design solutions automatically obtained by search algorithms. An empirical study involving MA and GA was carried out with four different PLA designs. MA presented the best solutions according the quality indicators used in the quantitative analysis. The results of the qualitative evaluation showed that the optimized solutions are well evaluated by the experts. After both analyzes, the hypothesis could be confirmed. (AU) | |
| FAPESP's process: | 14/03389-9 - Supporting mechanisms to the design and development of mobile learning environments and applications |
| Grantee: | Ellen Francine Barbosa |
| Support Opportunities: | Regular Research Grants |