On dynamically updating a computer program: From concept to prototype

Frieder, Ophir; Segal, Mark E.

doi:10.1016/0164-1212(91)90096-o

Cited by 73 publications

(43 citation statements)

References 9 publications

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“…Updating Functionality A large number of compiler-or library-based systems have been developed for C [13,16,9,2], C++ [18,20], Java [7,27,11,24], and functional languages like ML [12,14] and Erlang [3]. Many do not support all of the changes needed to make dynamic updates in practice.…”

Section: Related Workmentioning

confidence: 99%

“…For example, updates cannot change type definitions or function prototypes [27,11,18,20,2], or else only permit such changes for abstract types or encapsulated objects [20,14]. In many cases, updates to active code (e.g., long-running loops) are disallowed [14,24,13,16,20], and data stored in local variables may not be transformed [17,16,13,18]. Some approaches are intentionally less full-featured, targeting "fix and continue" development [19,15] or dynamic instrumentation [9].…”

Section: Related Workmentioning

confidence: 99%

“…Many of the systems reviewed make no safety guarantees, which can lead to, among other things, run-time type errors [3,13,18]. One way to avoid run-time type errors is to sacrifice representation-consistency, as we did in our prior work, mentioned above.…”

Section: Related Workmentioning

confidence: 99%

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Practical dynamic software updating for C

Neamtiu

Hicks

Stoyle

et al. 2006

Proceedings of the 27th ACM SIGPLAN Conference on Programming Language Design and Implementation

141

174

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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 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. Our compiler 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 our system to construct and dynamically apply patches to three substantial open-source server programs-Very Secure FTP daemon, OpenSSH 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%.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Practical dynamic software updating for C

Neamtiu

Hicks

Stoyle

et al. 2006

Proceedings of the 27th ACM SIGPLAN Conference on Programming Language Design and Implementation

141

174

View full text Add to dashboard Cite

show abstract

“…[7,23,15] to name a few) although in general the focus has been on code maintenance rather than evolving distributed system functionality. The specific system we are using [11] was initially inspired by the difficulties of crafting a plug-in interface for the packet scheduler in PLANet [10,12].…”

Section: Update Extensionsmentioning

confidence: 99%

Evolution in Action: Using Active Networking to Evolve Network Support for Mobility

et al. 2002

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Abstract.A key early objective of Active Networking (AN) was to support on-the-fly network evolution. Although AN has been used relatively extensively to build application-customized protocols and even whole networking systems, demonstrations of evolution have been limited. This paper examines three AN mechanisms and how they enable evolution: active packets and plug-in extensions, well-known to the AN community, and update extensions, which are novel to AN. We devote our presentation to a series of demonstrations of how each type of evolution can be applied to the problem of adding support for mobility to a network. This represents the most large-scale demonstration of AN evolution to date. These demonstrations show what previous AN research has not: that AN technology can, in fact, support very significant changes to the network, even while the network is operational.

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“…In this case there is existing data that may need to be transformed even though it is not necessarily persistent data. Existing systems (such as Fabry [1976], Frieder and Segal [1991]) recognize the need for such transformation functions, but leave the development of those functions to the maintainer. Tess's comparison algorithms could be used to generate these transformation functions.…”

Section: Future Workmentioning

confidence: 99%

A model for compound type changes encountered in schema evolution

Lerner

2000

ACM Trans. Database Syst.

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Schema evolution is a problem that is faced by long-lived data. When a schema changes, existing persistent data can become inaccessible unless the database system provides mechanisms to access data created with previous versions of the schema. Most existing systems that support schema evolution focus on changes local to individual types within the schema, thereby limiting the changes that the database maintainer can perform. We have developed a model of type changes incorporating changes local to individual types as well as compound changes involving multiple types. The model describes both type changes and their impact on data by defining derivation rules to initialize new data based on the existing data. The derivation rules can describe local and nonlocal changes to types to capture the intent of a large class of type change operations. We have built a system called Tess (Type Evolution Software System) that uses this model to recognize type changes by comparing schemas and then produces a transformer that can update data in a database to correspond to a newer version of the schema.

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On dynamically updating a computer program: From concept to prototype

Cited by 73 publications

References 9 publications

Practical dynamic software updating for C

Practical dynamic software updating for C

Evolution in Action: Using Active Networking to Evolve Network Support for Mobility

A model for compound type changes encountered in schema evolution

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