All-at-once-synthesis of controllers from scenario-based product line specifications

Maxime Cordy, J. Davril, Joel Greenyer, Erika Gressi, P. Heymans
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引用次数: 3

Abstract

Software-intensive systems often consist of multiple components that interact to realize complex requirements. An additional dimension of complexity arises when one designs many variants of a system at once, that is, a software product line (SPL). We propose a scenario-based approach to design SPLs, based on a combination of Modal Sequence Diagrams (MSDs) and a feature model. It consists in associating every MSD to the set of variants that have to satisfy its specification. Variability constitutes a new source of complexity, which can lead to inconsistencies in the specification of one or multiple variants. It is therefore crucial to detect these inconsistencies, and to produce a controller for each variant that makes it behave so that it satisfies its specification. We present a new controller synthesis technique that checks the absence of inconsistencies in all variants at once, thereby more radically exploiting the similarities between them. Our method first translates the MSD specification into a variability-aware Büchi game, and then solves this game for all variants in a single execution. We implemented the approach in ScenarioTools, a software tool which we use to evaluate our algorithms against competing methods.
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从基于场景的产品线规格中一次性合成控制器
软件密集型系统通常由多个组件组成,这些组件相互作用以实现复杂的需求。当一个人同时设计一个系统的许多变体,即软件产品线(SPL)时,复杂性的另一个维度就出现了。我们提出了一种基于场景的方法来设计SPLs,该方法基于模态序列图(MSDs)和特征模型的组合。它包括将每个MSD与必须满足其规范的一组变体相关联。可变性构成了复杂性的新来源,这可能导致一个或多个变体的规格不一致。因此,至关重要的是检测这些不一致,并为每个变体生成一个控制器,使其行为符合其规范。我们提出了一种新的控制器综合技术,可以立即检查所有变体中是否存在不一致性,从而更彻底地利用它们之间的相似性。我们的方法首先将MSD规范转换为可感知变量的b chi游戏,然后在一次执行中为所有变体解决这个游戏。我们在ScenarioTools中实现了该方法,这是一个软件工具,我们使用它来评估我们的算法与竞争方法。
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Understanding hybrid SPL composition impact on the refactoring into SPL Modular synthesis of product lines (ModSyn-PL) All-at-once-synthesis of controllers from scenario-based product line specifications Empirical comparison of regression methods for variability-aware performance prediction Mechanical product lifecycle management meets product line engineering
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