Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study
Context: Software product lines (SPLs) have reached a considerable level of adoption in the software industry. The most commonly used models for managing the variability of SPLs are feature models (FMs). The analysis of FMs is an error-prone, tedious task, and it is not feasible to accomplish this t...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-05-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/12/11/5563 |
| _version_ | 1797494107098054656 |
|---|---|
| author | Samuel Sepúlveda Ania Cravero |
| author_facet | Samuel Sepúlveda Ania Cravero |
| author_sort | Samuel Sepúlveda |
| collection | DOAJ |
| description | Context: Software product lines (SPLs) have reached a considerable level of adoption in the software industry. The most commonly used models for managing the variability of SPLs are feature models (FMs). The analysis of FMs is an error-prone, tedious task, and it is not feasible to accomplish this task manually with large-scale FMs. In recent years, much effort has been devoted to developing reasoning algorithms for FMs. Aim: To synthesize the evidence on the use of reasoning algorithms for feature modeling. Method: We conducted a systematic mapping study, including six research questions. This study included 66 papers published from 2010 to 2020. Results: We found that most algorithms were used in the domain stage (70%). The most commonly used technologies were transformations (18%). As for the origins of the proposals, they were mainly rooted in academia (76%). The FODA model continued to be the most frequently used representation for feature modeling (70%). A large majority of the papers presented some empirical validation process (90%). Conclusion: We were able to respond to the RQs. The FODA model is consolidated as a reference within SPLs to manage variability. Responses to RQ2 and RQ6 require further review. |
| first_indexed | 2024-03-10T01:29:33Z |
| format | Article |
| id | doaj.art-4be0428ac9f044b4afd5fefab43abed8 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T01:29:33Z |
| publishDate | 2022-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-4be0428ac9f044b4afd5fefab43abed82023-11-23T13:43:54ZengMDPI AGApplied Sciences2076-34172022-05-011211556310.3390/app12115563Reasoning Algorithms on Feature Modeling—A Systematic Mapping StudySamuel Sepúlveda0Ania Cravero1Departamento de Ciencias de la Computación e Informática, Centro de Estudios en Ingeniería de Software, Universidad de La Frontera, Temuco 4811230, ChileDepartamento de Ciencias de la Computación e Informática, Centro de Estudios en Ingeniería de Software, Universidad de La Frontera, Temuco 4811230, ChileContext: Software product lines (SPLs) have reached a considerable level of adoption in the software industry. The most commonly used models for managing the variability of SPLs are feature models (FMs). The analysis of FMs is an error-prone, tedious task, and it is not feasible to accomplish this task manually with large-scale FMs. In recent years, much effort has been devoted to developing reasoning algorithms for FMs. Aim: To synthesize the evidence on the use of reasoning algorithms for feature modeling. Method: We conducted a systematic mapping study, including six research questions. This study included 66 papers published from 2010 to 2020. Results: We found that most algorithms were used in the domain stage (70%). The most commonly used technologies were transformations (18%). As for the origins of the proposals, they were mainly rooted in academia (76%). The FODA model continued to be the most frequently used representation for feature modeling (70%). A large majority of the papers presented some empirical validation process (90%). Conclusion: We were able to respond to the RQs. The FODA model is consolidated as a reference within SPLs to manage variability. Responses to RQ2 and RQ6 require further review.https://www.mdpi.com/2076-3417/12/11/5563reasoning algorithmsautomated analysisfeature modelingsoftware product linessystematic mapping |
| spellingShingle | Samuel Sepúlveda Ania Cravero Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study Applied Sciences reasoning algorithms automated analysis feature modeling software product lines systematic mapping |
| title | Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study |
| title_full | Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study |
| title_fullStr | Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study |
| title_full_unstemmed | Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study |
| title_short | Reasoning Algorithms on Feature Modeling—A Systematic Mapping Study |
| title_sort | reasoning algorithms on feature modeling a systematic mapping study |
| topic | reasoning algorithms automated analysis feature modeling software product lines systematic mapping |
| url | https://www.mdpi.com/2076-3417/12/11/5563 |
| work_keys_str_mv | AT samuelsepulveda reasoningalgorithmsonfeaturemodelingasystematicmappingstudy AT aniacravero reasoningalgorithmsonfeaturemodelingasystematicmappingstudy |