Adaptive control technologies that incorporate learning algorithms have been proposed to enable automatic flight control and vehicle recovery, autonomous flight, and to maintain vehicle performance in the face of unknown, changing, or poorly defined operating environments. In order for adaptive control systems to be used in safety-critical aerospace applications, they must be proven to be highly safe and reliable. Rigorous methods for adaptive software verification and validation must be developed to ensure that control system software failures will not occur. Of central importance in this regard is the need to establish reliable methods that guarantee convergent learning, rapid convergence (learning) rate, and algorithm stability. This paper presents the major problems of adaptive control systems that use learning to improve performance. The paper then presents the major procedures and tools presently developed or currently being developed to enable the verification, validation, and ultimate certification of these adaptive control systems. These technologies include the application of automated program analysis methods, techniques to improve the learning process, analytical methods to verify stability, methods to automatically synthesize code, simulation and test methods, and tools to provide on-line software assurance.

Safety-critical real-time standards define several criticality levels for the tasks. In this paper we consider the real-time systems designed under the DO-178B safety assessment process (i.e., Software Considerations in Airborne Systems and Equipment Certification). Vestal introduced a new multiple criticality task model to efficiently take into account criticality levels in the schedulability analysis of such systems. Such a task model represents a potentially very significant advance in the modeling of safety-critical real-time softwares. Baruah and Vestal continue this investigation, with a new scheduling algorithm combining fixed and dynamic priority policies. Another major design issue is to allow a system developer to determine how sensitive is the schedulability analysis to changes in execution time of various software components.In this paper, we first prove that the well-known Audsley's algorithm is optimal for assigning priorities to tasks with multiple criticality levels. We then provide a proof on the optimality of Vestal's algorithm for optimizing the resource requirements to schedule tasks with multiple criticality levels. We then present a sensitivity analysis for multiple criticality tasks that is based on Bini et al. results on sporadic tasks.

We consider real-time systems connected via several fieldbuses. Validating such systems consists in prooving that tasks meet their end-to-end deadlines. Tasks are scheduled on processors by fixed-priority schedulers. We propose an automatic method for allocating tasks on processors and assigning priorities to tasks so that every deadline is met. Allocation and scheduling are simultaneously achieved. We do not limit the search space to a specific priority rule (such as Rate Monotonic or Deadline Monotonic). Feasible schedules are validated by a Holistic Analysis. Numerical results of the method are lastly presented on a real-size application. Our tool will be a beneficial help to design real-time distributed systems.

We consider the scheduling of periodic tasks running on distributed computers. Every execution of a task must meet its deadline. Response time analysis of the tasks is used to prove the schedulabilty of hard real-time distributed systems according the on-line priority rules that schedule the processors and the network. Its main advantage is to take into account the precedence dependencies of the schedules of the tasks on the processors and the messages sent on the network(s). Past works have addressed the issue of tasks related by asynchronous communication constraints with the senders and the receivers working at the same rate. In this paper we study more general relations among tasks when the rates of dependent tasks are not equal. We call such relations generalized communication constraints. Usually distributed systems are scheduled using a synchronization protocol and an on-line scheduling algorithm by processor. We present in this paper a graph theoretical approach to this schedulability analysis. Our algorithm transforms complex communication relations into classical ones, so that the classical scheduling analysis can be fully applied. That transformation is independent of the architecture of the distributed systems and no assumption is made on the synchronization protocol considered.

This article presents some results about schedulability analysis of tasks with offsets also known as transactions, in the particular case of monotonic transactions. The impact of a transaction on the response time of a lower priority task under analysis is computed with the interference implied by the transaction. In the general context of tasks with offsets (general transactions), only exponential methods are known to calculate the exact worst-case response time of a task. However, in this case, Mäki-Turja and Nolin have proposed an efficient approximation method. A monotonic pattern in a transaction (regarding the priority of the task under analysis), occurs when, by rotation of the higher priority tasks in a transaction, it is possible to find a pattern of tasks such that the processor demand of the transaction is monotically decreasing during a period of the transaction. We have shown in our previous work that if a task under analysis is such that all the interfering transactions are monotonic, then it is possible to evaluate its exact response time in a pseudo-polynomial time. This article presents in detail how to apply this method. Then, it compares our results to the multiframe model proposed by Mok and Chen in [5] (AM "Accumulatively Monotonic" pattern). We show that the multiframe model is a particular instance of tasks with offsets but the results presented for AM multiframe cannot be applied on monotonic transactions. Finally, we show that the approximation method proposed by Mäki-Turja and Nolin computes an exact response time in the case of monotonic transactions, even if its complexity is higher than the one of the test that we proposed.