The Promise and Challenge of Runtime Variability

Runtime variability offers a good choice for many systems that experience dynamic changes in their quality and context. Since the advent of software product lines (SPLs) in the 1990s as a successful approach for building multiple, related products, feature models (FMs)-compact representations of all...

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Bibliographic Details
Published in:Computer (Long Beach, Calif.) Calif.), 2011-12, Vol.44 (12), p.93-95
Main Authors: Capilla, R., Bosch, J.
Format: Article
Language:English
Subjects:
Applied sciences
Computer programming
Computer science
control theory
systems
Dynamical systems
Dynamics
Exact sciences and technology
Runtime environment
Runtime variability modeling
Software
Software architecture
Software engineering
Software technologies
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Summary:Runtime variability offers a good choice for many systems that experience dynamic changes in their quality and context. Since the advent of software product lines (SPLs) in the 1990s as a successful approach for building multiple, related products, feature models (FMs)-compact representations of all the features of the products in the SPL-have increased in popularity. Large and medium- size software companies now rely on numerous second-generation SPL tools such as Gears SPL Lifecycle Framework (www.biglever.com) and pure::variants (www.pure-systems, com) that use FMs to describe the variability of their products. Today, systems with adaptive and context-aware architectures- including autonomic and ubiquitous computing systems and software ecosystems-require more dynamic capabilities to address runtime needs (S. Hallsteinsen et al., "Dynamic Software Product Lines," Computer, Apr. 2008, pp. 93-95). In service-oriented computing, for example, the selection of services motivated by changing conditions or service-level agreements implies an automated binding of the current service to a different one. Likewise, autonomous software designed to load a new system configuration, based on a set of allowed choices, must cope with different situations. Such systems must be able to adapt to runtime conditions and manage them with minimal human intervention.
ISSN:0018-9162
1558-0814
1558-0814
DOI:10.1109/MC.2011.382