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Technique to measure the frequency of application of business rules used in deriving value of a field in an output from ageing IT app

IP.com Disclosure Number: IPCOM000239308D
Publication Date: 2014-Oct-28
Document File: 3 page(s) / 53K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a technique for determining the currency of the business rules used in an existing IT application. It also describes a technique to identify obsolete business rules/software code vs the business rules/software code that is used very frequently and that needs increased focus.

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Technique to measure the frequency of application of business rules used in deriving value of a field in an output from ageing IT app

Currently, there are numerous aging IT applications accessed by customer thru various devices - mobile, PC, terminals, etc. Most of these IT applications extract data from various heterogeneous sources (example - sensors, social media, data repositories, IT packages, etc) using specific data selection business rules. Then, the data is sanitized, translated using set of data transformation business rules. The transformed data is exposed to the end user on various types of devices in various visualization methods using data visualization business rules. All these business rules act on individual data field within a data source or on multiple data fields involving multiple data sources. As the IT application's age (time passage), some of the business rules may become obsolete while deriving the value for a data field. Over a period of time, large number of business rules that were relevant when the application was new may no longer apply. The code executing these business rules will continue to consume resources (storage, CPU) and can slow down the net response time to the end user action (example - search, dashboard, transaction, etc).

There many existing IT tools that measure the quality and quantity of the code, but none of them measure the frequency of its execution that is tied back to the business rules.

The solution disclosed is to measure the frequency at which a business rule or a business rule set (combination of business rules) is applied to either extract, transform or visualize the data at the data field level.

Some of the advantages of this solution are -
1) Easy identification of the business rules that are obsolete/less relevant or that need changes - by measuring the frequency with which they are executed.

2) Identification of the business rules that are used at high frequency and are critical for business - by measuring the frequency with which they are executed.

3) Reduction in resource drain (storage and CPU) in applying non-relevant business rules - by measuring the resource consumption...