Towards detecting redundancy in domain engineering process using first order logic rules

Elfaki, Abdelrahman Osman; Fong, Sim Liew; Aik, Kevin Loo Teow; Johar, Gapar Md

doi:10.1504/ijkesdp.2013.052716

Cited by 6 publications

(7 citation statements)

References 34 publications

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“…Salinesi and Mazo (2012) identified redundancy based on their verification criteria. Few researchers worked on the identification and cause of redundancies (Elfaki, Fong, Aik & Johar, 2013;White, Benavides, Schmidt, Trinidad, Dougherty & Ruiz-Cortes, 2010), but none of them resolved redundancy. Felfernig et al (Felfernig, Benavides Cuevas, Galindo Duarte & Reinfrank, 2013) have not given any details related to the implementation of recommended solutions for redundancies.…”

Section: Comparison With Existing Methodsmentioning

confidence: 99%

“…According to Table 14, the proposed method not only deals with redundancies considered by existing works (column 1) but also handled other cases of redundancy (Section 2). It provides more rules (17) to deal with redundancies when compared to (Elfaki, Fong, Aik & Johar, 2013;Felfernig et al, 2013;Mazo, Lopez-Herrejon, Salinesi, Diaz & Egyed, 2011;Salinesi, Mazo & Diaz, 2010;White, Benavides, Schmidt, Trinidad, Dougherty & Ruiz-Cortes, 2010). The presented method takes less time to deal with redundancies (column 6) for particular cases (columns 2-4) when compared to existing methods (column 5).…”

Section: Comparison With Existing Methodsmentioning

confidence: 99%

“…In this Section, various FM redundancies that exist in the literature have been classified mainly into six categories as shown in the typology given in Fig. 1 (Elfaki, Fong, Aik & Johar, 2013;Felfernig, Benavides Cuevas, Galindo Duarte & Reinfrank, 2013;Mazo, 2011;Salinesi & Mazo, 2012;Salinesi, Mazo & Diaz, 2010). The redundancies include defects due to redundant relationships in models.…”

Section: Typology Of Redundanciesmentioning

confidence: 99%

“…(Salinesi et al, 2010) Table 2 depicts the cases of redundancy caused by exclusion of an alternative-child feature. (Elfaki et al, 2013;Salinesi et al, 2010;Van Der Storm, 2007;Von der Maßen & Lichter, 2004;White et al, 2010) Table 3 represents the cases of redundancy caused by implication constraint(s) and a FMF.…”

Section: Typology Of Redundanciesmentioning

confidence: 99%

See 3 more Smart Citations

Classifying and resolving software product line redundancies using an ontological first-order logic rule based method

Bhushan

Duarte

Samant³

et al. 2021

Expert Systems with Applications

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Section: Comparison With Existing Methodsmentioning

confidence: 99%

Section: Comparison With Existing Methodsmentioning

confidence: 99%

Section: Typology Of Redundanciesmentioning

confidence: 99%

Section: Typology Of Redundanciesmentioning

confidence: 99%

See 2 more Smart Citations

Classifying and resolving software product line redundancies using an ontological first-order logic rule based method

Bhushan

Duarte

Samant³

et al. 2021

Expert Systems with Applications

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“…Compared with the ranges reported in the literature, to the best of our knowledge, our range is the biggest tested thus far. Elfaki et al (2010Elfaki et al ( , 2013Elfaki et al ( , 2014 provide the technical details of how we prepare our data sets.…”

Section: Scalability Experimentsmentioning

confidence: 99%

A rule‐based approach to detect and prevent inconsistency in the domain‐engineering process

Elfaki

2015

Expert Systems

Self Cite

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A medium‐sized domain‐engineering process can contain thousands of features that all have constraint dependency rules between them. Therefore, the validation of the content of domain‐engineering process is vital to produce high‐quality software products. However, it is not feasible to do this manually. This paper aims to improve the quality of the software products generated by the domain‐engineering process by ensuring the validity of the results of that process. We propose rules for two operations: inconsistency detection and inconsistency prevention. We introduce first‐order logic (FOL) rules to detect three types of inconsistency and prevent the direct inconsistency in the domain‐engineering process. Developing FOL rules to detect and prevent inconsistency in the domain‐engineering process directly without the need to the configuration process is our main contribution. We performed some experiments to test the scalability and applicability of our approach on domain‐engineered software product lines containing 1000 assets to 20000 assets. The results show that our approach is scalable and could be utilized to improve the domain‐engineering process.

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A classification and systematic review of product line feature model defects

Bhushan

Negi²,

Samant³

et al. 2020

Software Qual J

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Towards detecting redundancy in domain engineering process using first order logic rules

Cited by 6 publications

References 34 publications

Classifying and resolving software product line redundancies using an ontological first-order logic rule based method

Classifying and resolving software product line redundancies using an ontological first-order logic rule based method

A rule‐based approach to detect and prevent inconsistency in the domain‐engineering process

A classification and systematic review of product line feature model defects

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