Policy-based autonomic control service

Recently, there has been a considerable interest in policy-based, goal-oriented service management and autonomic computing. Much work is still required to investigate designs and policy models and associate meta-reasoning systems for policy-based autonomic systems. In this paper we outline a proposed autonomic middleware control service used to orchestrate selfhealing of distributed applications. Policies are used to adjust the systems autonomy and define self-healing strategies to stabilize/correct a given system in the event of failures

Quality Assurance of Software Applications Using the In Vivo Testing Approach

Software products released into the field typically have some number of residual defects that either were not detected or could not have been detected during testing. This may be the result of flaws in the test cases themselves, incorrect assumptions made during the creation of test cases, or the infeasibility of testing the sheer number of possible configurations for a complex system; these defects may also be due to application states that were not considered during lab testing, or corrupted states that could arise due to a security violation. One approach to this problem is to continue to test these applications even after deployment, in hopes of finding any remaining flaws. In this paper, we present a testing methodology we call in vivo testing, in which tests are continuously executed in the deployment environment. We also describe a type of test we call in vivo tests that are specifically designed for use with such an approach: these tests execute within the current state of the program (rather than by creating a clean slate) without affecting or altering that state from the perspective of the end-user. We discuss the approach and the prototype testing framework for Java applications called Invite. We also provide the results of case studies that demonstrate Invite's effectiveness and efficiency

Verifying total correctness of graph programs

GP 2 is an experimental nondeterministic programming language based on graph transformation rules, allowing for visual programming and the solving of graph problems at a high-level of abstraction. In previous work we demonstrated how to verify graph programs using a Hoare-style proof calculus, but only partial correctness was considered. In this paper, we add new proof rules and termination functions, which allow for proofs to additionally guarantee that program executions always terminate (weak total correctness), or that programs always terminate and do so without failure (total correctness). We show that the new proof rules are sound with respect to the operational semantics of GP 2, complete for termination, and demonstrate their use on some example programs