The real-time refinement calculus: A foundation for machine-independent real-time programming

The real-time refinement calculus is an extension of the standard refinement calculus in which programs are developed from a precondition plus post-condition style of specification. In addition to adapting standard refinement rules to be valid in the real-time context, specific rules are required for the timing constructs such as delays and deadlines. Because many real-time programs may be nonterminating, a further extension is to allow nonterminating repetitions. A real-time specification constrains not only what values should be output, but when they should be output. Hence for a program to implement such a specification, it must guarantee to output values by the specified times. With standard programming languages such guarantees cannot be made without taking into account the timing characteristics of the implementation of the program on a particular machine. To avoid having to consider such details during the refinement process, we have extended our real-time programming language with a deadline command. The deadline command takes no time to execute and always guarantees to meet the specified time; if the deadline has already passed the deadline command is infeasible (miraculous in Dijkstra's terminology). When such a realtime program is compiled for a particular machine, one needs to ensure that all execution paths leading to a deadline are guaranteed to reach it by the specified time. We consider this checking as part of an extended compilation phase. The addition of the deadline command restores for the real-time language the advantage of machine independence enjoyed by non-real-time programming languages.

Reasoning about timeouts

In real-time programming a timeout mechanism allows exceptional behaviour, such as a lack of response, to be handled effectively, while not overly affecting the programming for the normal case. For. example, in a pump controller if the water level has gone below the minimum level and the pump is on and hence pumping in more water, then the water level should rise above the minimum level within a specified time. If not, there is a fault in the system and it should be shut down and an alarm raised. Such a situation can be handled by normal case code that determines when the level has risen above the minimum, plus a timeout case handling the situation when the specified time to reach the minimum has passed. In this paper we introduce a timeout mechanism, give it a formal definition in terms of more basic real-time commands, develop a refinement law for introducing a timeout clause to implement a specification, and give an example of using the law to introduce a timeout. The framework used is a machine-independent real-time programming language, which makes use of a deadline command to represent timing constraints in a machine-independent fashion. This allows a more abstract approach to handling timeouts.

Timing analysis of assembler code control-flow paths

Timinganalysis of assembler code is essential to achieve the strongest possible guarantee of correctness for safety-critical, real-time software. Previous work has shown how timingconstrain ts on controlflow paths through high-level language programs can be formalised using the semantics of the statements comprisingthe path. We extend these results to assembler-level code where it becomes possible to not only determine timingconstrain ts, but also to verify them against the known execution times for each instruction. A minimal formal model is developed with both a weakest liberal precondition and a strongest postcondition semantics. However, despite the formalism’s simplicity, it is shown that complex timingb ehaviour associated with instruction pipeliningand iterative code can be modelled accurately.

Computer-aided programming using formally specificed design templates

This paper describes a formal component language, used to support automated component-based program development. The components, referred to as templates, are machine processable, meaning that appropriate tool support, such as retrieval support, can be developed. The templates are highly adaptable, meaning that they can be applied to a wide range of problems. Some of the main features of the language are described, including: higher-order parameters; state variable declarations; specification statements and conditionals; applicability conditions and theories; meta-level place holders; and abstract data structures.

A formal metamodeling approach to a transformation between the UML state machine and object-z

A significant problem with currently suggested approaches for transforming between models in different languages is that the transformation is often described imprecisely, with the result that the overall transformation task may be imprecise, incomplete and inconsistent. This paper presents a formal metamodeling approach for transforming between UML and Object-Z. In the paper, the two languages are defined in terms of their formal metamodels, and a systematic transformation between the models is provided at the meta-level in terms of formal mapping functions. As a consequence, we can provide a precise, consistent and complete transformation between them.

Low-cost real-time gesture recognition

A major impediment to developing real-time computer vision systems has been the computational power and level of skill required to process video streams in real-time. This has meant that many researchers have either analysed video streams off-line or used expensive dedicated hardware acceleration techniques. Recent software and hardware developments have greatly eased the development burden of realtime image analysis leading to the development of portable systems using cheap PC hardware and software exploiting the Multimedia Extension (MMX) instruction set of the Intel Pentium chip. This paper describes the implementation of a computationally efficient computer vision system for recognizing hand gestures using efficient coding and MMX-acceleration to achieve real-time performance on low cost hardware.