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ERIC Number: ED563340
Record Type: Non-Journal
Publication Date: 2013
Pages: 159
Abstractor: As Provided
Reference Count: N/A
ISBN: 978-1-3035-1419-7
ISSN: N/A
A Theory of Information Quality and a Framework for Its Implementation in the Requirements Engineering Process
Grenn, Michael W.
ProQuest LLC, D.Sc. Dissertation, The George Washington University
This dissertation introduces a theory of information quality to explain macroscopic behavior observed in the systems engineering process. The theory extends principles of Shannon's mathematical theory of communication [1948] and statistical mechanics to information development processes concerned with the flow, transformation, and meaning of information. The meaning of requirements information in the systems engineering context is estimated or measured in terms of the cumulative requirements quality Q which corresponds to the distribution of the requirements among the available quality levels. The requirements entropy framework (REF) implements the theory to address the requirements engineering problem. The REF defines the relationship between requirements changes, requirements volatility, requirements quality, requirements entropy and uncertainty, and engineering effort. The REF is evaluated via simulation experiments to assess its practical utility as a new method for measuring, monitoring and predicting requirements trends and engineering effort at any given time in the process. The REF treats the requirements engineering process as an open system in which the requirements are discrete information entities that transition from initial states of high entropy, disorder and uncertainty toward the desired state of minimum entropy as engineering effort is input and requirements increase in quality. The distribution of the total number of requirements R among the N discrete quality levels is determined by the number of defined quality attributes accumulated by R at any given time. Quantum statistics are used to estimate the number of possibilities P for arranging R among the available quality levels. The requirements entropy H[subscript R] is estimated using R, N and P by extending principles of information theory and statistical mechanics to the requirements engineering process. The information I increases as HR and uncertainty decrease, and the change in information ÄI needed to reach the desired state of quality is estimated from the perspective of the receiver. The HR may increase, decrease or remain steady depending on the degree to which additions, deletions and revisions impact the distribution of R among the quality levels. Current requirements trend metrics generally treat additions, deletions and revisions the same and simply measure the quantity of these changes over time. The REF evaluates the quantity of requirements changes over time, distinguishes between their positive and negative effects by calculating their impact on H[subscript R], Q, and ÄI, and forecasts when the desired state will be reached, enabling more accurate assessment of the status and progress of the requirements engineering effort. Results from random variable simulations suggest the REF is an improved leading indicator of requirements trends that can be readily combined with current methods. The increase in I, or decrease in H[subscript R] and uncertainty, is proportional to the engineering effort E input into the requirements engineering process. The REF estimates the ÄE needed to transition R from their current state of quality to the desired end state or some other interim state of interest. Simulation results are compared with measured engineering effort data for Department of Defense programs published in the SE literature, and the results suggest the REF is a promising new method for estimation of ÄE. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]
ProQuest LLC. 789 East Eisenhower Parkway, P.O. Box 1346, Ann Arbor, MI 48106. Tel: 800-521-0600; Web site: http://www.proquest.com/en-US/products/dissertations/individuals.shtml
Publication Type: Dissertations/Theses - Doctoral Dissertations
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A