Distributed resolution of feature interactions for internet applications

Crespo, Rui Gustavo; Carvalho, Miguel; Logrippo, Luigi

doi:10.1016/j.comnet.2006.08.010

Cited by 9 publications

(4 citation statements)

References 22 publications

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“…There is a large body of research on detecting, managing, and resolving different kinds of feature interactions, in various domains (e.g., Internet applications [16], service systems [55], automotive systems [18], software product lines [27], requirements engineering [42], and computational biology [19]), and using different approaches (e.g., formalisms describing features and their interactions [10,13,20,39], architectures that avoid classes of interactions [25,26,52,53], sampling, static-analysis, and model-checking approaches for interaction detection [4,5,15,21,27,28,44,48], and techniques for resolving interactions at run-time [22,51]). While this body is substantial and diverse, the individual approaches and studies concentrate on specific kinds of interactions, in specific settings, using specific solutions.…”

Section: Introductionmentioning

confidence: 99%

Exploring feature interactions in the wild

Apel

Kolesnikov

Siegmund

et al. 2013

Proceedings of the 5th International Workshop on Feature-Oriented Software Development

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The feature-interaction problem has been keeping researchers and practitioners in suspense for years. Although there has been substantial progress in developing approaches for modeling, detecting, managing, and resolving feature interactions, we lack sufficient knowledge on the kind of feature interactions that occur in real-world systems. In this position paper, we set out the goal to explore the nature of feature interactions systematically and comprehensively, classified in terms of order and visibility. Understanding this nature will have significant implications on research in this area, for example, on the efficiency of interaction-detection or performance-prediction techniques. A set of preliminary results as well as a discussion of possible experimental setups and corresponding challenges give us confidence that this endeavor is within reach but requires a collaborative effort of the community.

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Section: Introductionmentioning

confidence: 99%

Exploring feature interactions in the wild

Apel

Kolesnikov

Siegmund

et al. 2013

Proceedings of the 5th International Workshop on Feature-Oriented Software Development

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show abstract

“…Instances of the feature interaction problem have been observed and addressed first in telecommunication systems [5] followed by studies on Internet applications [6], service systems [7], automotive systems [8], software product lines [9], computational biology [10], and in many other fields outside of computer science.…”

Section: Features and Feature Dependenciesmentioning

confidence: 99%

“…Behavioral dependencies between features (a.k.a. feature interactions [4]) have been observed and addressed first in telecommunication systems [5] followed by studies on Internet applications [6], service systems [7], automotive systems [8], software product lines [9], computational biology [10], and in many other fields outside of computer science. Several studies show that feature dependencies have a negative impact on maintenance efforts [11,12], increase the likelihood of integration failures [13], and prevent modular reasoning [14].…”

Section: Introductionmentioning

confidence: 99%

Feature dependencies in automotive software systems: Extent, awareness, and refactoring

Vogelsang

2020

Journal of Systems and Software

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Many automotive companies consider their software development process to be feature-oriented. In the past, features were regarded as isolated system parts developed and tested by developers from different departments. However, in modern vehicles, features are more and more connected and their behavior depends on each other in many situations. In this article, we describe how feature-oriented software development is conducted in automotive companies and which challenges arise from that. We present an empirical analysis of feature dependencies in three real-world automotive systems. The analysis shows that features in modern vehicles are highly interdependent. Furthermore, the study reveals that developers are not aware of these dependencies in most cases. For the three examined cases, we show that less than 12% of the components in the system architecture are responsible for more than 90% of the feature dependencies. Finally, we propose a refactoring approach for implicit communal components, which makes them explicit by moving them to a dedicated platform component layer.

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“…Our method does not rely on any particular definition of a feature; we leave it to the subject matter expert to decide what constitutes a feature. The feature interaction problem was first studied in telephony (e.g., [1][18]), but has been recognized in other domains, such as internet applications [19], embedded systems [20], security [21], and the automotive domain [22]. The most common definition of a feature interaction is from Cameron and Velthuijsen [3] where a feature interaction means that a feature behaves differently in the presence of other features than it behaves by itself (which could be desirable or undesirable).…”

Section: Related Workmentioning

confidence: 99%

Morse: Reducing the Feature Interaction Explosion Problem using Subject Matter Knowledge as Abstract Requirements

Millet

Day

Joyce

2018

2018 IEEE 26th International Requirements Engineering Conference (RE)

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The feature interaction problem appears in many different kinds of complex systems, especially systems whose elements are created or maintained by separate entities -for example, a modern automobile that incorporates electronic systems produced by different suppliers. Cross-cutting concerns, such as safety and security, require a comprehensive analysis of the possible interactions. However, there is a combinatorial explosion in the number of feature combinations to be considered. Our work approaches the feature interaction problem from a novel point of view: we seek to use the abstract subject matter knowledge of domain experts to deduce why some features will NOT interact, rather than trying to discover or resolve the interactions. In this paper, we present a method that can automatically reduce the required number of combinations and situations that have to be evaluated or resolved for feature interactions. Our tool, called Morse, rules out feature combinations that cannot have interactions based on traceable deductions from relatively simple abstract requirements that capture relevant subject matter knowledge. Our method is useful as a means of focusing attention on particular situations where more detailed functional requirements may be needed to avoid unacceptable risk arising from unintended interactions between features.

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Distributed resolution of feature interactions for internet applications

Cited by 9 publications

References 22 publications

Exploring feature interactions in the wild

Exploring feature interactions in the wild

Feature dependencies in automotive software systems: Extent, awareness, and refactoring

Morse: Reducing the Feature Interaction Explosion Problem using Subject Matter Knowledge as Abstract Requirements

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