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

Abstract

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.

Advances in multisensor information fusion: A Markov–Kalman viscosity fuzzy statistical predictor for analysis of oxygen flow, diffusion, speed, temperature, and time metrics in CPAP

“…To add internal and external validity to our data fusion study, we decided to adopt a multiple methodology, longitudinal approach to our CPAP sensor experiments, as this method is common in the literature (Aziz, ; Banerjee & Das, ; Chien, Hsu, Morrison, & Dou, ; Elfaki, ; Zhu, Leung, & He, ). Although this original dataset consisted of a sample of only 40 data points, it did give us some preliminary insights to solving our quality control issues.…”

Detecting Feature Duplication in a CRM Product Line

“…In [7], we carried out a systematic review about model defects that may appear in software product lines during their evolution. As a result of this review, we listed the different model defects addressed in literature, such as inconsistency [1]- [3], incorrectness [6], ambiguity [4], and unsafety [5]. A complementary study based on field experience helped us decide to focus on a specific defect, which is feature duplication.…”

“…Duplication is among many other defects (e.g. inconsistency [1]- [3], ambiguity [4], unsafety [5], incorrectness [6]) that may occur in software product lines during their evolution [7]. This defect consists of having the same element repeated many times in a software artefact.…”

Improving quality of software product line by analysing inconsistencies in feature models using an ontological rule‐based approach

“…Most of the existing approaches (Asadi, Gröner, Mohabbati, & Gašević, ; Yang & Dong, ; Zhang & Møller‐Pedersen, ) only identified a direct inconsistency in the configuration process, while the proposed approach additionally identified other types of inconsistencies without the requirement of the configuration process. Furthermore, the proposed approach suggested corrections for other cases of inconsistencies in contrast to the Elfaki () approach where only a direct inconsistency is prevented. Thüm, Kästner, et al () developed a tool that suggests corrective solutions to fix defects.…”

“…Many intelligent methods such as logic‐based methods (Fan & Naixiao, ; Hemakumar, ), constraint satisfaction techniques (White et al, ; White et al, ), formal semantics, optimization algorithms (Afzal, Mahmood, Rauf, & Shaikh, ), and so forth have been proposed till date to identify inconsistencies in an FM. First‐order logic (FOL) (Elfaki, ; Elfaki, Phon‐Amnuaisuk, & Ho, ; Osman, Amnuaisuk, & Ho, ) and ontology‐based approaches (Guo, Wang, Trinidad, & Benavides, ; Noorian, Ensan, Bagheri, Boley, & Biletskiy, ; Wang, Li, Sun, Zhang, & Pan, ) are also used to deal with FM inconsistencies. FMs are represented by ontologies on the basis of FOL predicates (Àlvez, Lucio, & Rigau, ; Gruninger & Menzel, ; Pease & Sutcliffe, ; Ramachandran, Reagan, & Goolsbey, ; Schneider, Carroll, Herman, & Patel‐Schneider, ; Schneider & Sutcliffe, ).…”