Goal-oriented modeling and verification of feature-oriented product lines

Asadi, Mohsen; Gröner, Gerd; Mohabbati, Bardia; Gašević, Dragan

doi:10.1007/s10270-014-0402-8

Cited by 33 publications

(19 citation statements)

References 41 publications

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“…On the other hand, many research combines the GM with other research fields. Mohammadi et al [28] propose a framework for combining GMs and problem frames, so that the goals of the system can be documented together with the corresponding knowledge of the system's context; Asadi et al [29] study both GM and feature model for the development lifecycle of software product lines, they give a description logic (DL)‐based approach to represent both models and their relations in a common DL knowledge base. Similar to these research, our work combines the analysis of GM with the methods of reviews mining and provides a new way to extend the studies of the GM.…”

Section: Related Workmentioning

confidence: 99%

Combining goal model with reviews for supporting the evolution of apps

Liu

et al. 2020

IET softw.

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To support the iterative development process of Apps, the goal model is not only established to describe the requirements at the early stage but also used for identifying the updating strategy in every iteration. In this process, reviews from users provide valuable information for developers to analyse the model with users sentiments. In this study, the authors combine the goal model with reviews for supporting the evolution of Apps. First, the authors introduce the reviews into the goal model as a new factor by comparing keywords. Second, the users sentiments in reviews are mined, and two kinds of information are gained by analysing the model to help developers make decisions on which goals to be improved in next version: one kind of information is about users sentiments on the goals to evaluate whether users like them; another kind is the impact of updating one goal to others. To validate the proposed approach, they conducted experiments and a survey based on the Apps in Google Play. The results show that the proposed approach can establish relationships between goals and reviews reasonably and further provide useful information for optimising the evolution strategy of the App.

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Section: Related Workmentioning

confidence: 99%

Combining goal model with reviews for supporting the evolution of apps

Liu

et al. 2020

IET softw.

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“…Standard goal models languages like i* [9] can represent intentional variability, but lack mechanisms for representing differences between intentional spaces of various systems (i.e., product line variability in the intentional space). Therefore, Asadi et al [10] have introduced the notion of family goal model to extend standard goal modeling techniques, which we apply in this paper to iStar 2.0 [5].…”

Section: A Metamodel For Agile Product Linementioning

confidence: 99%

Formalizing Agile Software Product Lines with a RE Metamodel

Haidar

Kolp

Wautelet

2018

Proceedings of the 13th International Conference on Software Technologies

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Requirements engineering (RE) techniques can play a determinant role when making the strategic decision to adopt an Agile Product Line approach to the production of software-intensive systems. This paper proposes an integrated goal and feature-based metamodel for agile software product lines. The aim is to allow analysts and developers to produce specifications that precisely capture the stakeholder's needs and intentions as well as to manage product line variabilities. Adopting practices from requirements engineering, especially goal and feature models, helps designing the domain and application engineering tiers of an agile product line. Such an approach allows a holistic perspective integrating human, organizational and agile aspects to better understand product lines dynamic business environments. It helps bridging the gap between product lines structures and requirements models, and proposes an integrated framework to all actors involved in the product line architecture.

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“…Table depicts the comparison of existing approaches with the proposed approach on the basis of various parameters, and the details of these parameters are given in Appendix A. 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.…”

Section: Related Workmentioning

confidence: 99%

“…The presented approach also handled inconsistencies in cardinality-based FMs. Moreover, the explanation for the cause of defects is an improvement on earlier work by Zhang and Møller-Pedersen (2013), Yang and Dong (2013), Asadi et al (2014), and , where inconsistency detection is done, but no explanation for their causes is given. The use of natural language for explaining the cause of defects due to inconsistency helps modellers to detect the incorrect relationships that lead to these inconsistencies.…”

Section: Scalabilitymentioning

confidence: 99%

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

2017

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In software product line engineering, feature models (FMs) represent the variability and commonality of a family of software products. The development of FMs may introduce inaccurate feature relationships. These relationships may cause various types of defects such as inconsistencies, which deteriorate the quality of software products. Several researchers have worked on the identification of defects due to inconsistency in FMs, but only a few of them have explained their causes. In this paper, FM is transformed to predicate‐based feature model ontology using Prolog. Further, first‐order logic is employed for defining rules to identify defects due to inconsistency, the explanations for their causes, and suggestions for their corrections. The proposed approach is explained using an FM available in Software Product Line Online Tools repository. It is validated using 26 FMs of discrete sizes up to 5,543 features, generated using the FeatureIDE tool and real‐world FMs. Results indicate that the proposed methodology is effective, accurate, and scalable and improves software product line.

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Goal-oriented modeling and verification of feature-oriented product lines

Cited by 33 publications

References 41 publications

Combining goal model with reviews for supporting the evolution of apps

Combining goal model with reviews for supporting the evolution of apps

Formalizing Agile Software Product Lines with a RE Metamodel

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

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