z-logo
open-access-imgOpen Access
A Rollback Mechanism to Recover from Software Failures in Role-based Adaptive Software Systems
Author(s) -
Nguonly Taing,
Thomas Springer,
Nicolás Cardozo,
Alexander Schill
Publication year - 2017
Publication title -
qucosa (saxon state and university library dresden)
Language(s) - English
Resource type - Conference proceedings
ISBN - 978-1-4503-4836-2
DOI - 10.1145/3079368.3079388
Subject(s) - rollback , computer science , adaptation (eye) , context (archaeology) , software bug , distributed computing , mechanism (biology) , software , software engineering , embedded system , operating system , programming language , database transaction , paleontology , philosophy , physics , epistemology , optics , biology
Context-dependent applications are relatively complex due to their multiple variations caused by context activation, especially in the presence of unanticipated adaptation. Testing these systems is challenging, as it is hard to reproduce the same execution environments. Therefore, a software failure caused by bugs is no exception. This paper presents a rollback mechanism to recover from software failures as part of a role-based runtime with support for unanticipated adaptation. The mechanism performs checkpoints before each adaptation and employs specialized sensors to detect bugs resulting from recent configuration changes. When the runtime detects a bug, it assumes that the bug belongs to the latest configuration. The runtime rolls back to the recent checkpoint to recover and subsequently notifies the developer to fix the bug and re-applying the adaptation through unanticipated adaptation. We prototype the concept as part of our role-based runtime engine LyRT and demonstrate the applicability of the rollback recovery mechanism for unanticipated adaptation in erroneous situations.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom