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An Integrated Systems Appliance for the Collection, Classification and Scoring of Software Lifecycle Quality Data Sets

IP.com Disclosure Number: IPCOM000228552D
Publication Date: 2013-Jun-18
Document File: 7 page(s) / 296K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a Requirements Quality Scoring Appliance (RQSA), a tool which uniquely integrates technology components with user defined data sets and/or scoring algorithms in order to improve the efficiency and effectiveness of capturing and scoring requirements in software lifecycle quality data sets.

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An Integrated Systems Appliance for the Collection , Classification and Scoring of Software Lifecycle Quality Data Sets

Quality Data Sets such as Issues, Risks, and Defects are created by nearly every role along the Software Life Cycle and most, if not all, of that data is stored in varying media and locations. This data is often used to produce quality statements or scores, which are in turn used to determine the ultimate quality of the artifacts that initially generated the data. The problem with this method arises when attempting to leverage these sets of quality data to drive Business Analytics across the software lifecycle. Harvesting the raw data sets or the end product scoring data associated with those data sets involves querying multiple sources, performing manual processes, and utilizing creative transformation in order to arrive at usable sets of analytics input.

Businesses need a method to enhance communication and collaboration with Quality Data Sets, where raw Quality Data Sets and scoring information is easily accessible by all interested users or systems. The method must enable descriptive and predictive analytics on quality data. For storing diverse types of quality data sets produced across the software lifecycle, businesses need a common repository. In addition, integration with quality data sets and scoring information through services that expose the data to consumers must be improved. The collection and classification of Quality Data Sets across the software lifecycle requires standardization. Based on historical and undisputable data, there must be transparency and accuracy in the development of predictive models. A standardized, extensible, and reusable approach to quality data analysis and assessments is needed. Finally, analytics tools and sources must be able to harvest scoring definitions and intelligence in order to build or refine newer models

Currently, third party vendors create integrations between tools and/or data sources using Open Services for Lifecycle Collaboration (OSLC) for information-sharing purposes; however, this approach does not easily lend itself to the capture of data sets that are the by-products of human intelligence and manual processes applied to the information within those existing systems.

Current tooling is focused on integrations with like or related tools, and as such limits the pool of analytic data sources to only those tools where integrations have been developed. These approaches do not allow for user defined or derived data sets to be easily integrated back into the tooling for use in broader analytic activities.

The present invention uniquely integrates technology components with user defined data sets and/or scoring algorithms to form the Requirements Quality Scoring Appliance (RQSA). The RQSA is a self-contained software appliance that improves the efficiency and effectiveness of capturing and scoring requirements in software lifecycle quality data sets. The RQSA...