Project Details
Description
9308773 Minsky Regularities, or the conformity to unifying principles, are essential to the comprehensibility, manageability and reliability of large software systems. Unfortunately, regularities are difficult to implement, unless they are imposed on a system by some kind of 'higher authority,' such as the programming language. The problem with implementing regularities stems from their intrinsic globality. Unlike an algorithm or a data structure that can be built into specific modules, a regularity is a principle that must be observed everywhere in the system, and cannot be localized. One can, of course, implement a desired regularity by painstakingly building all components of the system in accordance with it. But such a 'manual' implementation of regularities is laborious, unreliable, and unstable and difficult to verify and to change. The goal of this work is to develop and explore an approach to regularities which greatly simplifies their implementation, making them more easily employable for taming of the complexities of large systems. This approach, which is based on the concept of law-governed architecture (LGA), provides system designers and builders with the means for establishing regularities simply by declaring them formally and explicitly as the law of the system. Once such a law-governed regularity is declared, it is enforced by the environment in which the system is developed. The efficient enforcement of such regularities is a central objective of this research. Although not all desirable regularities can be established this way, the approach should be able to support a wide range of 'law-governed regularities'--which can be formally defined, and efficiently enforced--including module- interconnection frameworks, access-control schemes, variety of object-oriented regularities, various protocols for distributed systems, regularities that help in unifying heterogeneous systems, and others. ***
Status | Finished |
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Effective start/end date | 8/15/93 → 1/31/97 |
Funding
- National Science Foundation: $271,579.00