Abstract. Software product line engineering allows large software systems to be developed and adapted for varying customer needs. The products of a software product line can be described by means of a hierarchical variability model specifying the commonalities and variabilities between the artifacts of the individual products. The number of products generated by a hierarchical model is exponential in its size, which poses a serious challenge to software product line analysis and verification. For an analysis technique to scale, the effort has to be linear in the size of the model rather than linear in the number of products it generates. Hence, efficient product line verification is only possible if compositional verification techniques are applied that allow the analysis of products to be relativized on the properties of their variation points. In this paper, we propose simple hierarchical variability models (SHVM) with explicit variation points as a novel way to describe a set of products consisting of sets of methods. SHVMs provide a trade-off between expressiveness and a clean and simple model suitable for compositional verification. We generalize a previously developed compositional technique and tool set for the automatic verification of control-flow based temporal safety properties to product lines defined by SHVMs, and prove soundness of the generalization. The desired property relativization is achieved by introducing variation point specifications. We evaluate the proposed technique on a number of test cases.
Our overall goal is to support model-based approaches to verification and validation of communication protocols by techniques that automatically generate models of communication protocol entities from observations of their external behavior, using techniques based on regular inference (aka automata learning). In this paper, we address the problem that existing regular inference techniques produce "flat" state machines, whereas practically useful protocol models structure the internal state in terms of control locations and state variables, and describes dynamic behavior in a suitable (abstract) programming notation. We present a technique for introducing structure of an unstructured finite-state machine by introducing state variables and program-like descriptions of dynamic behavior, given a certain amount of user guidance. Our technique groups states with "similar control behavior" into control locations, and obtain program-like descriptions by means of decision tree generation. We have applied parts of our approach to an executable state machine specification of the Mobile Arts Advanced Mobile Location Center (A-MLC) protocol and evaluated the results by comparing them to the original specification.QC 2011121
Abstract. This paper describes ProMoVer, a tool for fully automated procedure-modular verification of Java programs equipped with methodlocal and global assertions that specify safety properties of sequences of method invocations. Modularity at the procedure-level is a natural instantiation of the modular verification paradigm, where correctness of global properties is relativized on the local properties of the methods rather than on their implementations, and is based here on the construction of maximal models for a program model that abstracts away from program data. This approach allows global properties to be verified in the presence of code evolution, multiple method implementations (as arising from software product lines), or even unknown method implementations (as in mobile code for open platforms). ProMoVer automates a typical verification scenario for a previously developed tool set for compositional verification of control flow safety properties, and provides appropriate pre-and post-processing. Modularity is exploited by a mechanism for proof reuse that detects and minimizes the verification tasks resulting from changes in the code and the specifications. The verification task is relatively light-weight due to support for abstraction from private methods and automatic extraction of candidate specifications from method implementations. We evaluate the tool on a number of applications from the smart card domain.
Abstract. This paper describes ProMoVer, a tool for fully automated procedure-modular verification of Java programs equipped with methodlocal and global assertions that specify safety properties of sequences of method invocations. Modularity at the procedure-level is a natural instantiation of the modular verification paradigm, where correctness of global properties is relativized on the local properties of the methods rather than on their implementations. Here it is based on the construction of maximal models for a program model that abstracts away from program data. This approach allows global properties to be verified in the presence of code evolution, multiple method implementations (as arising from software product lines), or even unknown method implementations (as in mobile code for open platforms). ProMoVer automates a typical verification scenario for a previously developed tool set for compositional verification of control flow safety properties, and provides appropriate pre-and post-processing. Both linear-time temporal logic and finite automata are supported as formalisms for expressing local and global safety properties, allowing the user to choose a suitable format for the property at hand. Modularity is exploited by a mechanism for proof reuse that detects and minimizes the verification tasks resulting from changes in the code and the specifications. The verification task is relatively light-weight due to support for abstraction from private methods and automatic extraction of candidate specifications from method implementations. We evaluate the tool on a number of applications from the domains of Java Card and web-based application.
This paper describes a novel technique for fully automated procedure-modular verification of Java programs equipped with method-local and global assertions that specify safety properties of sequences of method invocations. Modularity of verification is achieved by relativizing the correctness of global properties on the local properties rather than on the implementations of methods, and is based on the construction of maximal models. Tool support is provided by means of ProMoVer, a tool that is essentially a wrapper around a previously developed tool set for compositional verification of control flow safety properties, where program data is abstracted away completely. We evaluate the technique on a small but realistic case study.
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