International audienceWe present SPLEnD, the first compositional design verification engine for evolving software product lines(SPLs). The unique aspect of SPL development is the reuse of common features and management of variability among the family of products. The proposed design verification engine assumes that each SPL is composed of multiple features with each feature exhibiting variability. One novel aspect of SPLEnD is that it enables verification of SPLs, in which the variability information is captured differently at different levels of abstractions in the design and requirement stages. Another novel aspect of SPLEnD is that it enables compositional verification of designs against requirements. This involves first verifying the individual features separately, which provides a mapping between the variabilities at the requirement and design levels. The obtained mapping relations are then combined in the second step to check the conformance of the entire SPL. Feature level verification essentially involves standard model checking, while for the second step, a Quantified Boolean Formula (QBF) is synthesized and solved. The QBF avoids the explicit enumeration of all possible products thereby reducing the verification effort greatly. SPLEnD uses SPIN for the first step while the state of the art QBF solver CirQit is used for the second step. Thanks to the compositionality, SPLEnD easily handles the evolution of SPL by addition of new features and modification of existing features. Experimental results with SPLEnD look very promising: SPLs with several thousands of features were verified efficiently. A video of SPLEnD can be seen at http://www.cse.iitb.ac.in/$\sim$krishnas/splend.swf or http://www.cse.iitb.ac.in/$\sim$krishnas/splend.avi

International audienceIn a Software Product Line (SPL) comprising specifications (feature sets), implementations (component sets) and traceability between them, the definition of product is quite subtle. Intuitively, a strong relation of implementability should be established between implementations and specifications due to traceability. Various notions of traceability has been proposed in the literature : [13], [17], [8], [9]; but we found in our experience that they do not capture all situations that arise in practice. One example is the case where, an implementation, due to packaging reasons, contains additional components not required for a particular product specification. We have defined a general notion of traceability in order to cover such situations. Moreover, state-of-the-art satisfiability based notions lead to products where the implementability relation does not exist. Therefore, in this paper, we propose a simple, set-theoretic formalism to express the notions of traceability and implementability in a formal manner. The subsequent definition of SPL products is used to introduce a set of analysis problems that are either refinements of known problems, or are completely novel. Last but not the least, we propose encoding the analysis problems as Quantified Boolean Formula (QBF) constraints and use Quantified SAT (QSAT) solvers to solve these problems efficiently. To the best of our knowledge, the QBF encoding is novel; we prove the correctness of our encoding and demonstrate its practical feasibility through our prototype implementation Software Product Line Engine (SPLE)

Abstract:In a Software Product Line (SPL), the central notion of implementability provides the requisite connection between specifications and their implementations, leading to the definition of products. While it appears to be a simple extension of the traceability relation between components and features, it involves several subtle issues that were overlooked in the existing literature. In this paper, we have introduced a precise and formal definition of implementability over a fairly expressive traceability relation. The consequent definition of products in the given SPL naturally entails a set of useful analysis problems that are either refinements of known problems or are completely novel. We also propose a new approach to solve these analysis problems by encoding them as Quantified Boolean Formulae (QBF) and solving them through Quantified Satisfiability (QSAT) solvers. QBF can represent more complex analysis operations, which cannot be represented by using propositional formulae. The methodology scales much better than the SAT-based solutions hinted in the literature and were demonstrated through a tool called SPLAnE (SPL Analysis Engine) on a large set of SPL models.

Modern automotive systems are composed of hundreds of software-implemented features often interacting with physical subsystems under real-time constraints. For efficient management of their development, the features are conceived and realized as product lines involving variability with different variants being deployed in different vehicle classes. The variability information is expressed at different levels of abstraction during the various phases of development, like requirements, design and implementation. We introduce and study a formal model of such feature product lines capable of capturing variability and real-time behavior. We define a notion of conformance to relate the variability at different levels of abstraction and propose a compositional method of verifying conformance of multiple features. The proposed approach naturally extends to hybrid system behaviors consisting of discrete and continuous plant variables. We demonstrate the applicability of the approach by giving a simple paradigmatic example.

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