Army Vehicle Software Complexity Prediction Metric - Five Factors (Preprint)

Abstract

Army vehicle software provides mission critical complex functions. It interacts with complex electronics from multiple vendors and has unique software interfaces. The software structure complexity is influenced by many factors prior to software development. Understanding, predicting and resolving complexity of vehicle software prior to its development is a necessity for army mission success. Current complexity metrics are historical data distribution dependent. It focuses on software and its technical structure with no consideration of its influencing factors. Non-technical metrics related to software complexity are required to address diverse skill set including the management. Using non-technical metrics prior to software development enables management to spend resources early to resolve issues faster. In this paper, the authors propose five non-technical factor metrics based on the current software development process to predict future Army vehicle software complexity. Factor analysis and fuzzy logic techniques are used for developing, modeling and analyzing the software complexity prediction metric. The proposed metric is independent of software, programming language, and domain. This metric is data distribution independent.

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Document Details

Document Type
Technical Report
Publication Date
Apr 14, 2010
Accession Number
ADA538879

Entities

People

  • Harpreet Singh
  • Macam S. Dattathreya

Organizations

  • United States Army Tank Automotive Research, Development and Engineering Center

Tags

Communities of Interest

  • Cyber
  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computer Programming
  • Computer Programs
  • Configuration Management
  • Data Science
  • Engineering
  • Factor Analysis
  • Fuzzy Logic
  • Fuzzy Sets
  • Information Science
  • Language
  • Logic
  • Maintenance
  • Programming Languages
  • Reliability
  • Software Development
  • United States Government

Fields of Study

  • Computer science
  • Engineering

Readers

  • Computer Science.
  • Distributed Systems and Data Platform Development
  • Life Cycle Cost Analysis

Technology Areas

  • Microelectronics