47,946 research outputs found
Evolving feature model configurations in software product lines
The increasing complexity and cost of software-intensive systems has led developers to seek ways
of reusing software components across development projects. One approach to increasing software
reusability is to develop a software product-line (SPL), which is a software architecture that can be
reconfigured and reused across projects. Rather than developing software from scratch for a new project,
a new configuration of the SPL is produced. It is hard, however, to find a configuration of an SPL that
meets an arbitrary requirement set and does not violate any configuration constraints in the SPL.
Existing research has focused on techniques that produce a configuration of an SPL in a single step.
Budgetary constraints or other restrictions, however, may require multi-step configuration processes.
For example, an aircraft manufacturer may want to produce a series of configurations of a plane over a
span of years without exceeding a yearly budget to add features.
This paper provides three contributions to the study of multi-step configuration for SPLs. First, we
present a formal model of multi-step SPL configuration and map this model to constraint satisfaction
problems (CSPs). Second, we show how solutions to these SPL configuration problems can be automatically
derived with a constraint solver by mapping them to CSPs. Moreover, we show how feature model
changes can be mapped to our approach in a multi-step scenario by using feature model drift. Third, we
present empirical results demonstrating that our CSP-based reasoning technique can scale to SPL models
with hundreds of features and multiple configuration steps.Ministerio de Economía y Competitividad TIN2012-32273Junta de Andalucía TIC-590
Time-Space Efficient Regression Testing for Configurable Systems
Configurable systems are those that can be adapted from a set of options.
They are prevalent and testing them is important and challenging. Existing
approaches for testing configurable systems are either unsound (i.e., they can
miss fault-revealing configurations) or do not scale. This paper proposes
EvoSPLat, a regression testing technique for configurable systems. EvoSPLat
builds on our previously-developed technique, SPLat, which explores all
dynamically reachable configurations from a test. EvoSPLat is tuned for two
scenarios of use in regression testing: Regression Configuration Selection
(RCS) and Regression Test Selection (RTS). EvoSPLat for RCS prunes
configurations (not tests) that are not impacted by changes whereas EvoSPLat
for RTS prunes tests (not configurations) which are not impacted by changes.
Handling both scenarios in the context of evolution is important. Experimental
results show that EvoSPLat is promising. We observed a substantial reduction in
time (22%) and in the number of configurations (45%) for configurable Java
programs. In a case study on a large real-world configurable system (GCC),
EvoSPLat reduced 35% of the running time. Comparing EvoSPLat with sampling
techniques, 2-wise was the most efficient technique, but it missed two bugs
whereas EvoSPLat detected all bugs four times faster than 6-wise, on average.Comment: 14 page
Conflict Detection for Edits on Extended Feature Models using Symbolic Graph Transformation
Feature models are used to specify variability of user-configurable systems
as appearing, e.g., in software product lines. Software product lines are
supposed to be long-living and, therefore, have to continuously evolve over
time to meet ever-changing requirements. Evolution imposes changes to feature
models in terms of edit operations. Ensuring consistency of concurrent edits
requires appropriate conflict detection techniques. However, recent approaches
fail to handle crucial subtleties of extended feature models, namely
constraints mixing feature-tree patterns with first-order logic formulas over
non-Boolean feature attributes with potentially infinite value domains. In this
paper, we propose a novel conflict detection approach based on symbolic graph
transformation to facilitate concurrent edits on extended feature models. We
describe extended feature models formally with symbolic graphs and edit
operations with symbolic graph transformation rules combining graph patterns
with first-order logic formulas. The approach is implemented by combining
eMoflon with an SMT solver, and evaluated with respect to applicability.Comment: In Proceedings FMSPLE 2016, arXiv:1603.0857
Recovering Architectural Variability of a Family of Product Variants
A Software Product Line (SPL) aims at applying a pre-planned systematic reuse
of large-grained software artifacts to increase the software productivity and
reduce the development cost. The idea of SPL is to analyze the business domain
of a family of products to identify the common and the variable parts between
the products. However, it is common for companies to develop, in an ad-hoc
manner (e.g. clone and own), a set of products that share common
functionalities and differ in terms of others. Thus, many recent research
contributions are proposed to re-engineer existing product variants to a SPL.
Nevertheless, these contributions are mostly focused on managing the
variability at the requirement level. Very few contributions address the
variability at the architectural level despite its major importance. Starting
from this observation, we propose, in this paper, an approach to reverse
engineer the architecture of a set of product variants. Our goal is to identify
the variability and dependencies among architectural-element variants at the
architectural level. Our work relies on Formal Concept Analysis (FCA) to
analyze the variability. To validate the proposed approach, we experimented on
two families of open-source product variants; Mobile Media and Health Watcher.
The results show that our approach is able to identify the architectural
variability and the dependencies
Context for goal-level product line derivation
Product line engineering aims at developing a family of products and facilitating the derivation of product variants from it. Context can be a main factor in determining what products to derive. Yet, there is gap in incorporating context with variability models. We advocate that, in the first place, variability originates from human intentions and choices even before software systems are constructed, and context influences variability at this intentional level before the functional one. Thus, we propose to analyze variability at an early phase of analysis adopting the intentional ontology of goal models, and studying how context can influence such variability. Below we present a classification of variation points on goal models, analyze their relation with context, and show the process of constructing and maintaining the models. Our approach is illustrated with an example of a smarthome for people with dementia problems. 1
Towards Product Lining Model-Driven Development Code Generators
A code generator systematically transforms compact models to detailed code.
Today, code generation is regarded as an integral part of model-driven
development (MDD). Despite its relevance, the development of code generators is
an inherently complex task and common methodologies and architectures are
lacking. Additionally, reuse and extension of existing code generators only
exist on individual parts. A systematic development and reuse based on a code
generator product line is still in its infancy. Thus, the aim of this paper is
to identify the mechanism necessary for a code generator product line by (a)
analyzing the common product line development approach and (b) mapping those to
a code generator specific infrastructure. As a first step towards realizing a
code generator product line infrastructure, we present a component-based
implementation approach based on ideas of variability-aware module systems and
point out further research challenges.Comment: 6 pages, 1 figure, Proceedings of the 3rd International Conference on
Model-Driven Engineering and Software Development, pp. 539-545, Angers,
France, SciTePress, 201
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