Compositional specification of functionality and timing of manufacturing systems

In this paper, a formal modeling approach is introduced for compositional specification of both functionality and timing of manufacturing systems. Functionality aspects can be considered orthogonally to the timing. The functional aspects are specified using two abstraction levels; high-level activities and lower level actions. Design of a functionally correct controller is possible by looking only at the activity level, abstracting from the different execution orders of actions. Furthermore, the specific timing of actions is not needed. As a result, controller designcan be performed on a much smaller state space compared to an explicit model where timing and actions are present. The performance of the controller can be analyzed and optimizedby taking into account the timing characteristics. Since formal semantics are given in terms of a (max, +) state space, various existing performance analysis techniques can be used. Weillustrate the approach, including performance analysis, on an example manufacturing system

Sciduction: Combining Induction, Deduction, and Structure for Verification and Synthesis

Even with impressive advances in automated formal methods, certain problems in system verification and synthesis remain challenging. Examples include the verification of quantitative properties of software involving constraints on timing and energy consumption, and the automatic synthesis of systems from specifications. The major challenges include environment modeling, incompleteness in specifications, and the complexity of underlying decision problems. This position paper proposes sciduction, an approach to tackle these challenges by integrating inductive inference, deductive reasoning, and structure hypotheses. Deductive reasoning, which leads from general rules or concepts to conclusions about specific problem instances, includes techniques such as logical inference and constraint solving. Inductive inference, which generalizes from specific instances to yield a concept, includes algorithmic learning from examples. Structure hypotheses are used to define the class of artifacts, such as invariants or program fragments, generated during verification or synthesis. Sciduction constrains inductive and deductive reasoning using structure hypotheses, and actively combines inductive and deductive reasoning: for instance, deductive techniques generate examples for learning, and inductive reasoning is used to guide the deductive engines. We illustrate this approach with three applications: (i) timing analysis of software; (ii) synthesis of loop-free programs, and (iii) controller synthesis for hybrid systems. Some future applications are also discussed

Scheduler modeling based on the controller synthesis paradigm

The controller synthesis paradigm provides a general framework for scheduling real-time applications. Schedulers can be considered as controllers of the applications; they restrict their behavior so that given scheduling requirements are met. We study a modeling methodology based on the controller synthesis paradigm. The methodology allows to get a correctly scheduled system from timed models of its processes in an incremental manner, by application of composability results which simplify schedulability analysis. It consists in restricting successively the system to be scheduled by application of constraints defined from scheduling requirements. The latter are a conjunction of schedulability requirements that express timing properties of the processes and policy requirements about resource management. The presented methodology allows a unified view of scheduling theory and approaches based on timing analysis of models of real-time applications