Topic
Dynamic software updating
About: Dynamic software updating is a research topic. Over the lifetime, 125 publications have been published within this topic receiving 4860 citations.
Papers published on a yearly basis
Papers
11 Jun 2006
TL;DR: Ginseng, a DSU implementation for C that performs a series of analyses that when combined with some simple runtime support ensure that an update will not violate type-safety while guaranteeing that data is kept up-to-date.
Abstract: Software updates typically require stopping and restarting an application, but many systems cannot afford to halt service, or would prefer not to. Dynamic software updating (DSU) addresses this difficulty by permitting programs to be updated while they run. DSU is appealing compared to other approaches for on-line upgrades because it is quite general and requires no redundant hardware. The challenge is in making DSU practical: it should be flexible, and yet safe, efficient, and easy to use.In this paper, we present Ginseng, a DSU implementation for C that aims to meet this challenge. We compile programs specially so that they can be dynamically patched, and generate most of a dynamic patch automatically. Ginseng performs a series of analyses that when combined with some simple runtime support ensure that an update will not violate type-safety while guaranteeing that data is kept up-to-date. We have used Ginseng to construct and dynamically apply patches to three substantial open-source server programs---Very Secure FTP daemon, OpenSSH sshd daemon, and GNU Zebra. In total, we dynamically patched each program with three years' worth of releases. Though the programs changed substantially, the majority of updates were easy to generate. Performance experiments show that all patches could be applied in less than 5 ms, and that the overhead on application throughput due to updating support ranged from 0 to at most 32%.
252 citations
TL;DR: This work describes a formal framework for studying online software version change, gives a general definition of validity of an online change, shows that it is in general undecidable and develops sufficient conditions for ensuring validity for a procedural language.
Abstract: The usual way of installing a new version of a software system is to shut down the running program and then install the new version. This necessitates a sometimes unacceptable delay during which service is denied to the users of the software. An online software replacement system replaces parts of the software while it is in execution, thus eliminating the shutdown. While a number of implementations of online version change systems have been described in the literature, little investigation has been done on its theoretical aspects. We describe a formal framework for studying online software version change. We give a general definition of validity of an online change, show that it is in general undecidable and then develop sufficient conditions for ensuring validity for a procedural language.
247 citations
1 Apr 2009
TL;DR: Ksplice allows system administrators to apply patches to their operating system kernels without rebooting and can correct 88% of the Linux kernel vulnerabilities from this interval without the need for reboots and without writing any new code.
Abstract: Ksplice allows system administrators to apply patches to their operating system kernels without rebooting. Unlike previous hot update systems, Ksplice operates at the object code layer, which allows Ksplice to transform many traditional source code patches into hot updates with little or no programmer involvement. In the common case that a patch does not change the semantics of persistent data structures, Ksplice can create a hot update without a programmer writing any new code.Security patches are one compelling application of hot updates. An evaluation involving all significant x86-32 Linux security patches from May 2005 to May 2008 finds that most security patches-56 of 64-require no new code to be performed as a Ksplice update. In other words, Ksplice can correct 88% of the Linux kernel vulnerabilities from this interval without the need for rebooting and without writing any new code.If a programmer writes a small amount of new code to assist with the remaining patches (about 17 lines per patch, on average), then Ksplice can apply all 64 of the security patches from this interval without rebooting.
222 citations
TL;DR: Several dynamic software-based updating systems that are in the research and production stages are described, including the procedure-oriented dynamic updating system (PODUS), which updates a program by replacing each old procedure with its corresponding new procedure during execution.
Abstract: Several dynamic software-based updating systems that are in the research and production stages are described. In particular, the procedure-oriented dynamic updating system (PODUS) is discussed. In PODUS, a program is updated by loading the new version of the program and replacing each old procedure with its corresponding new procedure during execution. Updating a procedure involves changing the binding from its current version to the new version. When all procedures have been replaced by their corresponding new versions, the program update is completed. >
216 citations
15 Jun 2009
TL;DR: The design and implementation of Jvolve, a DSU-enhanced Java VM that can support 20 of 22 updates to three open-source programs--Jetty web server, JavaEmailServer, and CrossFTP server--based on actual releases occurring over 1 to 2 years are presented.
Abstract: Software evolves to fix bugs and add features. Stopping and restarting programs to apply changes is inconvenient and often costly. Dynamic software updating (DSU) addresses this problem by updating programs while they execute, but existing DSU systems for managed languages do not support many updates that occur in practice and are inefficient. This paper presents the design and implementation of Jvolve, a DSU-enhanced Java VM. Updated programs may add, delete, and replace fields and methods anywhere within the class hierarchy. Jvolve implements these updates by adding to and coordinating VM classloading, just-in-time compilation, scheduling, return barriers, on-stack replacement, and garbage collection. Jvolve, is safe: its use of bytecode verification and VM thread synchronization ensures that an update will always produce type-correct executions. Jvolve is flexible: it can support 20 of 22 updates to three open-source programs--Jetty web server, JavaEmailServer, and CrossFTP server--based on actual releases occurring over 1 to 2 years. Jvolve is efficient: performance experiments show that incurs no overhead during steady-state execution. These results demonstrate that this work is a significant step towards practical support for dynamic updates in virtual machines for managed languages.
210 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2020 | 2 |
| 2019 | 4 |
| 2018 | 7 |
| 2017 | 10 |
| 2016 | 14 |
| 2015 | 3 |