3,270 research outputs found
Reasoning and Improving on Software Resilience against Unanticipated Exceptions
In software, there are the errors anticipated at specification and design
time, those encountered at development and testing time, and those that happen
in production mode yet never anticipated. In this paper, we aim at reasoning on
the ability of software to correctly handle unanticipated exceptions. We
propose an algorithm, called short-circuit testing, which injects exceptions
during test suite execution so as to simulate unanticipated errors. This
algorithm collects data that is used as input for verifying two formal
exception contracts that capture two resilience properties. Our evaluation on 9
test suites, with 78% line coverage in average, analyzes 241 executed catch
blocks, shows that 101 of them expose resilience properties and that 84 can be
transformed to be more resilient
Automatic Software Repair: a Bibliography
This article presents a survey on automatic software repair. Automatic
software repair consists of automatically finding a solution to software bugs
without human intervention. This article considers all kinds of repairs. First,
it discusses behavioral repair where test suites, contracts, models, and
crashing inputs are taken as oracle. Second, it discusses state repair, also
known as runtime repair or runtime recovery, with techniques such as checkpoint
and restart, reconfiguration, and invariant restoration. The uniqueness of this
article is that it spans the research communities that contribute to this body
of knowledge: software engineering, dependability, operating systems,
programming languages, and security. It provides a novel and structured
overview of the diversity of bug oracles and repair operators used in the
literature
Adaptive service discovery on service-oriented and spontaneous sensor systems
Service-oriented architecture, Spontaneous networks, Self-organisation, Self-configuration, Sensor systems, Social patternsNatural and man-made disasters can significantly impact both people and environments. Enhanced effect can be achieved through dynamic networking of people, systems and procedures and seamless integration of them to fulfil mission objectives with service-oriented sensor systems. However, the benefits of integration of services will not be realised unless we have a dependable method to discover all required services in dynamic environments. In this paper, we propose an Adaptive and Efficient Peer-to-peer Search (AEPS) approach for dependable service integration on service-oriented architecture based on a number of social behaviour patterns. In the AEPS network, the networked nodes can autonomously support and co-operate with each other in a peer-to-peer (P2P) manner to quickly discover and self-configure any services available on the disaster area and deliver a real-time capability by self-organising themselves in spontaneous groups to provide higher flexibility and adaptability for disaster monitoring and relief
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