Abstract State Machines 1988-1998: Commented ASM Bibliography

An annotated bibliography of papers which deal with or use Abstract State Machines (ASMs), as of January 1998.Comment: Also maintained as a BibTeX file at http://www.eecs.umich.edu/gasm

Quantitative Verification: Formal Guarantees for Timeliness, Reliability and Performance

Computerised systems appear in almost all aspects of our daily lives, often in safety-critical scenarios such as embedded control systems in cars and aircraft or medical devices such as pacemakers and sensors. We are thus increasingly reliant on these systems working correctly, despite often operating in unpredictable or unreliable environments. Designers of such devices need ways to guarantee that they will operate in a reliable and efficient manner. Quantitative verification is a technique for analysing quantitative aspects of a system's design, such as timeliness, reliability or performance. It applies formal methods, based on a rigorous analysis of a mathematical model of the system, to automatically prove certain precisely specified properties, e.g. ``the airbag will always deploy within 20 milliseconds after a crash'' or ``the probability of both sensors failing simultaneously is less than 0.001''. The ability to formally guarantee quantitative properties of this kind is beneficial across a wide range of application domains. For example, in safety-critical systems, it may be essential to establish credible bounds on the probability with which certain failures or combinations of failures can occur. In embedded control systems, it is often important to comply with strict constraints on timing or resources. More generally, being able to derive guarantees on precisely specified levels of performance or efficiency is a valuable tool in the design of, for example, wireless networking protocols, robotic systems or power management algorithms, to name but a few. This report gives a short introduction to quantitative verification, focusing in particular on a widely used technique called model checking, and its generalisation to the analysis of quantitative aspects of a system such as timing, probabilistic behaviour or resource usage. The intended audience is industrial designers and developers of systems such as those highlighted above who could benefit from the application of quantitative verification,but lack expertise in formal verification or modelling

A Comparison of Information Systems Coverage in the CPA, CIA and CMA Examinations for the Period 1987-1991

In recent years, three major accounting professional organizations, the American Institute of Certified Public Accountants (AICPA), Institute of Management Accountants (IMA) and Internal Auditors Institute (IIA) have considered and issued statements on the body of knowledge deemed necessary for practice as a Certified Public Accountant, Certified Management Accountant and Certified Internal Auditor. In each instance, knowledge and skills in information systems technology were included. This is not surprising, in view of the fact that changes in technology have dramatically altered the way in which accounting data is gathered, processed, stored, accessed and reported. Each of these professional organizations also requires or recommends the passing of an organization-sponsored certification examination for entry into or recognition within the various practice areas. While the examinations are not the only means of assessing the knowledge and skills necessary for certification, they are an important tool in evaluating the extent of the qualifications presented by a candidate. In view of the above, one may postulate that the certification examination, in each instance, would include coverage of the areas of knowledge included in the prerequisite body of knowledge. In particular, since each of the professional groups cite information systems (IS) knowledge as an important knowledge component, one would expect to observe test items addressing current IS in each exam

Robot Autonomy for Surgery

Autonomous surgery involves having surgical tasks performed by a robot operating under its own will, with partial or no human involvement. There are several important advantages of automation in surgery, which include increasing precision of care due to sub-millimeter robot control, real-time utilization of biosignals for interventional care, improvements to surgical efficiency and execution, and computer-aided guidance under various medical imaging and sensing modalities. While these methods may displace some tasks of surgical teams and individual surgeons, they also present new capabilities in interventions that are too difficult or go beyond the skills of a human. In this chapter, we provide an overview of robot autonomy in commercial use and in research, and present some of the challenges faced in developing autonomous surgical robots