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AoURN-based modeling and analysis of software product lines

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Abstract

Software Product Line Engineering concerns itself with domain engineering and application engineering. During domain engineering, the whole product family is modeled with a preferred flavor of feature models and additional models as required (e.g., domain models or scenario-based models). During application engineering, the focus shifts toward a single family member and the configuration of the member’s features. Recently, aspectual concepts have been employed to better encapsulate individual features of a Software Product Line (SPL), but the existing body of SPL work does not include a unified reasoning framework that integrates aspect-oriented feature description artifacts with the capability to reason about stakeholders’ goals while taking feature interactions into consideration. Goal-oriented SPL approaches have been proposed, but do not provide analysis capabilities that help modelers meet the needs of the numerous stakeholders involved in an SPL while at the same time considering feature interactions. We present an aspect-oriented SPL approach for the requirements phase that allows modelers (a) to capture features, goals, and scenarios in a unified framework and (b) to reason about stakeholders’ needs and perform trade-off analyses while considering undesirable interactions that are not obvious from the feature model. The approach is based on the Aspect-oriented User Requirements Notation (AoURN) and helps identify, prioritize, and choose products based on analysis results provided by AoURN editor and analysis tools. We apply the AoURN-based SPL framework to the Via Verde SPL to demonstrate the feasibility of this approach through the selection of a Via Verde product configuration that satisfies stakeholders’ needs and results in a high-level, scenario-based specification that is free from undesirable feature interactions.

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Notes

  1. See http://en.wikipedia.org/wiki/Via_Verde as well as http://www.viaverde.pt/.

  2. A stereotype is indicated by double angle brackets in the URN feature model.

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Acknowledgments

This research was supported by the Natural Sciences and Engineering Research Council of Canada, through its programs of Discovery Grants and Postgraduate Scholarships, as well as the Ontario Graduate Scholarship Program, and FCT MCTES.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science (EECS), University of Ottawa, 800 King Edward, Ottawa, ON, K1N 6N5, Canada

    Gunter Mussbacher & Daniel Amyot

  2. Departamento de Informatica, CITI/FCT, Universidade Nova de Lisboa, 2829-516, Caparica, Portugal

    João Araújo & Ana Moreira

Authors
  1. Gunter Mussbacher
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  2. João Araújo
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  3. Ana Moreira
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  4. Daniel Amyot
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Correspondence to Gunter Mussbacher.

Appendix: OCL constraints

Appendix: OCL constraints

Table 9 details the specification of the AoURN OCL constraints that encode the common requires and conflicts integrity constraints found in feature models as well as AoURN-specific constraints. The OCL constraints exploit the fact that the names of goal model elements (i.e., IntentionalElements) and concerns are unique. Furthermore, the constraints work for qualitative and quantitative goal model values, because qualitative values are internally synchronized with quantitative values. Figure 18 shows an excerpt of the URN metamodel required to formulate these OCL constraints.

Table 9 Mapping for integrity constraints in feature models to OCL constraints in URN profile
Full size table
Fig. 18
figure 18

URN metamodel for GRL strategies and concerns

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For the requires constraint, the specified features ≪A≫ and ≪B≫ are first found in the IntentionalElements, and then all IntentionalElements are found that are selected in a product configuration (i.e., EvaluationStrategy), i.e., all elements that have an evaluation equal to 100 (see Sect. 3.7). The constraint then states that if feature ≪A≫ is selected, feature ≪B≫ must also be selected, i.e., the evaluation of each feature equals 100.

Similarly for the conflicts constraint, the specified features ≪A≫ and ≪B≫ are also found in the IntentionalElements, and then all IntentionalElements are found that are selected in a product configuration. Furthermore, all IntentionalElements are found that are not selected in the same product configuration, i.e., all elements that have an evaluation equal to 0. The constraint then states that if feature ≪A≫ is selected, feature ≪B≫ must not be selected, i.e., the evaluation of the first feature equals 100 while the evaluation of the second feature equals 0.

The third constraint is typically not supported by integrity constraints in external feature models but can easily be incorporated into the ASF to reduce the size of the feature model. Again, the specified features ≪A≫ and ≪B≫ are found in the IntentionalElements, and all IntentionalElements are found that are selected in a product configuration. The constraint then simply states that ≪A≫ or ≪B≫ has to be selected.

Finally, the last constraint is also AoURN-specific. The specified feature ≪F≫ is found in the IntentionalElements, and all IntentionalElements are found that are selected in a product configuration. The stakeholder ≪S≫ is found in the Concerns. The constraint then simply states that if the concern is activated (condition is true), then ≪F≫ has to be selected.

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Mussbacher, G., Araújo, J., Moreira, A. et al. AoURN-based modeling and analysis of software product lines. Software Qual J 20, 645–687 (2012). https://doi.org/10.1007/s11219-011-9153-8

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