Automated Staged Configuration With Semantic Web Technologies

Bošković, Marko; Bagheri, Ebrahim; Gašević, Dragan; Mohabbati, Bardia; Kaviani, Nima; Hatala, Marek

doi:10.1142/s0218194010004827

Cited by 14 publications

(17 citation statements)

References 9 publications

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“…Until recently, the main focus has been on the development of automatic algorithms for the application engineering lifecycle. More specifically most of these techniques have been formulated to address the automated configuration of software product line feature models based on stakeholders' functional and non-functional requirements (Janota and Kiniry 2007;Benavides et al 2005;Batory 2005;Boskovic et al 2010;. Feature model configurations have been often derived, validated and verified using Logic Truth Maintenance Systems (LTMS).…”

Section: Related Workmentioning

confidence: 99%

Decision support for the software product line domain engineering lifecycle

2012

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Software product line engineering is a paradigm that advocates the reusability of software engineering assets and the rapid development of new applications for a target domain. These objectives are achieved by capturing the commonalities and variabilities between the applications of the target domain and through the development of comprehensive and variability-covering feature models. The feature models developed within the software product line development process need to cover the relevant features and aspects of the target domain. In other words, the feature models should be elaborate representations of the feature space of that domain. Given that feature models, i.e., software product line feature models, are developed mostly by domain analysts by sifting through domain documentation, corporate records and transcribed interviews, the process is a cumbersome and error-prone one. In this paper, we propose a decision support platform that assists domain analysts throughout the domain engineering lifecycle by: (1) automatically performing natural language processing tasks over domain documents and identifying important information for the domain analysts such as the features and integrity constraints that exist in the domain documents; (2) providing a collaboration platform around the domain documents such that multiple domain analysts can collaborate with each other during the process using a Wiki; (3) formulating semantic links between domain terminology with external widely used ontologies such as WordNet in order to disambiguate the terms used in domain documents; and (4) developing traceability links between the unstructured information available in the domain documents and Autom Softw Eng (2012) 19:335-377 their formal counterparts within the formal feature model representations. Results obtained from our controlled experimentations show that the decision support platform is effective in increasing the performance of the domain analysts during the domain engineering lifecycle in terms of both the coverage and accuracy measures.

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Section: Related Workmentioning

confidence: 99%

Decision support for the software product line domain engineering lifecycle

2012

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“…Later stages, such as development and installation, are closely related to the actual code base of SmartHome, which has not been developed by the author. Finally, the fact that the stages are derived from industrial experience is a common practice in staged configuration research (e.g., [8,18,7,14,5,3], cf. Section 8).…”

Section: Discussionmentioning

confidence: 99%

Light-weight tool support for staged product derivation

Elsner

2012

Proceedings of the 16th International Software Product Line Conference - Volume 1

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Tool support that checks for configuration errors and generates product parts from configurations can significantly improve on product derivation in product line engineering. Up to now, however, derivation tools commonly disregard the staged derivation process. They do not restrict configuration consistency checks to process entities such as configuration stages, stakeholders, or build tasks. As a result, constraints that are only valid for certain process entities must either be checked permanently, leading to false positive errors, or one must refrain from defining them at all. This paper contributes a light-weight approach to provide tailored tool support for staged product derivation. Compared to previous approaches, it is not tied to a single configuration mechanism (e.g., feature modeling), and also accounts for the stakeholders involved and the build tasks that generate product parts. First, the product line engineer describes the derivation process in a concise model. Then, based on constraint checks on the configuration (e.g., a feature model configuration) that are linked to the modeled entities, comprehensive tool support can be provided: Configuration actions can be guided and restricted depending on the configuring stakeholder in a fine-grained manner, and constraints attached to a build task will only be checked if it actually shall be executed. Finally, in combination with previous work, the paper provides evidence that the approach is applicable to legacy product lines in a light-weight manner and that it technically scales to thousands of constraint checks.

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“…This work relies on the ontology-based feature modeling proposed by Wang et al (2007). In the same direction, Bošković et al (2010) complement the ontology-based feature modeling approach of Wang et al (2007) with automated staged configuration. In this approach, a product configuration is performed as a set of consecutive steps and they provide an algorithm for automatic feature model specialization based on description logic reasoning mechanisms.…”

Section: Related Workmentioning

confidence: 99%