Comparison Of Requirements Understanding In Model Based Systems Engineering Versus Traditional Methods

Abstract

Today, Model-Based Systems Engineering (MBSE) is used to meet the fast completion of complex projects and products. Yet, little research has been performed on the cognitive process involved in utilizing models to represent specifications. This thesis studies how well systems engineers can understand requirements in an MBSE environment. Systems engineers using models were tested to determine whether they understand a system in the same way or differently from systems engineers using text-based requirements for the same system. Subjects comprehension on model-based versus text-based tactical sling specifications was measured based on the accuracy of the answers provided by the subjects in an online survey. The subjects responses were used to evaluate experiment hypotheses and determine the effectiveness, efficiency, usefulness, and usability of modeling languages. Due to the low number of participants, the study could not definitively show whether the systems engineers using models understand system requirements in the same way or differently from systems engineers using text-based versions of the requirements. The study, however, did substantiate that models were more effective for eliciting correct responses to multiple-answer questions, suggesting that systems engineers and stakeholders can comprehend complex system requirements better in an MBSE environment.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 2018
Accession Number
AD1065274

Entities

People

  • Yong J. Chia

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Biomedical
  • Human Systems
  • Weapons Technologies

DTIC Thesaurus Topics

  • Accuracy
  • Cognition
  • Complex Systems
  • Comprehension
  • Data Analysis
  • Department Of Defense
  • Digital Engineering
  • Efficiency
  • Engineering
  • Engineers
  • Environment
  • Hypotheses
  • Industrial Engineering
  • Information Exchange
  • Information Processing
  • Information Science
  • Information Systems
  • Institutional Review Board
  • Language
  • Model Based Systems Engineering
  • Specifications
  • Standards
  • Surveys
  • Systems Engineering
  • Systems Modeling Language
  • Theses

Fields of Study

  • Computer science
  • Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Software Engineering.
  • Systems Analysis and Design