Safe and Verifiable Design of Concurrent Java Programs

The design of concurrent programs has a reputation for being difficult, and thus potentially dangerous in safetycritical real-time and embedded systems. The recent appearance of Java, whilst cleaning up many insecure aspects of OO programming endemic in C++, suffers from a deceptively simple threads model that is an insecure variant of ideas that are over 25 years old [1]. Consequently, we cannot directly exploit a range of new CASE tools -- based upon modern developments in parallel computing theory -- that can verify and check the design of concurrent systems for a variety of dangers\ud such as deadlock and livelock that otherwise plague us during testing and maintenance and, more seriously, cause catastrophic failure in service. \ud Our approach uses recently developed Java class\ud libraries based on Hoare's Communicating Sequential Processes (CSP); the use of CSP greatly simplifies the design of concurrent systems and, in many cases, a parallel approach often significantly simplifies systems originally approached sequentially. New CSP CASE tools permit designs to be verified against formal specifications\ud and checked for deadlock and livelock. Below we introduce CSP and its implementation in Java and develop a small concurrent application. The formal CSP description of the application is provided, as well as that of an equivalent sequential version. FDR is used to verify the correctness of both implementations, their\ud equivalence, and their freedom from deadlock and livelock

Parallel data compression

Data compression schemes remove data redundancy in communicated and stored data and increase the effective capacities of communication and storage devices. Parallel algorithms and implementations for textual data compression are surveyed. Related concepts from parallel computation and information theory are briefly discussed. Static and dynamic methods for codeword construction and transmission on various models of parallel computation are described. Included are parallel methods which boost system speed by coding data concurrently, and approaches which employ multiple compression techniques to improve compression ratios. Theoretical and empirical comparisons are reported and areas for future research are suggested