The success of a number of projects has been shown to be significantly improved by the use of a formalism . However, there remains an open issue: to what extent can a development process based on a singular formal notation and method succeed. The majority of approaches demonstrate a low level of flexibility by attempting to use a single notation to express all of the different aspects encountered in software development. Often, these approaches leave a number of scalability issues open. We prefer a more eclectic approach. In our experience, the use of a formalism-based toolkit with adequate notations for each development phase is a viable solution. Following this principle, any specific notation is used only where and when it is really suitable and not necessarily over the entire software lifecycle. The approach explored in this article is perhaps slowly emerging in practice -we hope to accelerate its adoption. However, the major challenge is still finding the best way to instantiate it for each specific application scenario. In this work, we describe a development process and method for automotive applications which consists of five phases. The process recognizes the need for having adequate (and tailored) notations (Problem Frames, Requirements State Machine Language, and Event-B) for each development phase as well as direct traceability between the documents produced during each phase. This allows for a stepwise verification/validation of the system under development. The ideas for the formal development method have evolved over two significant case studies carried out in the DEPLOY project.
While requirements engineering has received considerable attention in academia over the past years, formalization of requirements for physically influenced systems is still a difficult task in practice. In this paper, we give formal representations of some typical requirement classes arising in the automotive industry. We divide these patterns into three main classes: those mostly referring to properties of continuous signals, those mostly referring to discrete events and those referring to similarity to a reference signal. We discuss these patterns on concrete examples from automotive embedded systems, where specifications are used for test case generation. Category: industrial Difficulty: medium Context and OriginsDeriving formal specifications for industrial embedded systems is a challenging task. In this paper, we discuss some typical patterns of such specifications as well as challenges when trying to represent the requirements in existing formalisms. One major use case for the derived formal specification is test case generation, i. e., systematically deriving test cases from specifications. In this paper we discuss typical specification patterns occuring in the automotive domain, for test case generation approaches see [3] and [6], for instance.From an industry perspective, it is important to note that formalized specifications for physically-driven systems will usually form an incomplete picture, as there are requirements which are simply not amenable to suitable formalization at this point. This includes requirements on how driving is supposed to "feel" for the customer. Also, some requirements (like noise levels or vibrations inside the car) may be formalizable, but since there are usually no useful physical models for these effects, the specification cannot be leveraged. However, we believe that formal specifications even of subsets of requirements, together with adequate physical models are still very useful, since the development process can be accelerated with help of formal methods.For the specifications given in this paper, we generally use pre-and postconditions. Here, a precondition A describes the assumptions made on the environment under which the required behavior, a postcondition B, is supposed to hold. The examples raise the question what are suitable formalisms for A and B to cover a large class of requirements. Usually, A will be tightened for testing purposes. While a specification might require B to hold under a large 80
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