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Method and process for configuration file name mining to clone subsystems and create new file names based on rule analysis

IP.com Disclosure Number: IPCOM000203101D
Publication Date: 2011-Jan-19
Document File: 5 page(s) / 95K

Publishing Venue

The IP.com Prior Art Database

Abstract

Method and process for configuration file name mining to clone subsystems and create new file names based on rule analysis

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Method and process for configuration file name mining to clone subsystems and create new file names based on rule analysis

In some software environments or application servers configuration files are often used to define the rules by which a system starts and initializes itself. To create a new system one has to define new configuration files and execute commands to bring up the new system. The names of the files are typically related to the subsystem they initiate - there is no explicit standard enforced by the application server - it is left up to an individual or an organization to define and enforce the rules.

    This creates a problem for software that has to create new subsystems and new sets of configuration files as this software must have knowledge of the naming convention used by a particular organization.

    The problem addressed in this article is to analyze the names of the configuration files used to bring up a given subsystem and create a new set that follow the existing standards. Without this solution software either has to:

    Ask the user to manually define all of the new names of their configuration files, a process which de-values the automated clone as it requires manual invention by the user which also introduces the risk of errors;or

    Enforce a new set of rules that the clone software knows, which means organizations have to change long established standards for one offered by the clone software which causes confusion and inconsistencies

    This article describes a technique to clone software systems and determine the naming convention used by a given organization or installation of systems, based on pattern name matching of Data Sets.

The advantage of this solution - described in a set of steps

    
Full Mappings
Partial Mappings
Common Qualifiers
Symbolic Values
Mid Level Qualifier
Low Level Qualifier
is that different sets of standards typically in use at software installations can be absorbed by tools whose value is to provide automation of cloning and provisioning of new subsystems.

    Without this approach the skill level required to clone and provision new systems is high - this is expensive to staff and must be centrally maintained so off-shoring and cost reduction of the task of cloning and provisioning new systems becomes difficult and expensive - developers cannot provision new systems using automated software and must request new systems adding a delay to their workload which slows down development of code and costs time and money, and manual cloning when left to experts to do manually can be done with errors that can cause downstream problems in the new systems that have not been provisioned correctly which introduce hard to fix runtime errors and potentially loss of and corruption of customer data.

    Apply a String comparison to the new & old start policies (Dataset name and optional member name or command (typically start) and parameters. The old values would be those already defined for the existing system, these new v...