EXPLORATORY EXPERIMENTAL STUDIES COMPARING ONLINE AND OFFLINE PROGRAMING PERFORMANCE

Abstract

Two exploratory experiments compared debugging performance of programers working under conditions of online and offline access to a computer. These are the first known studies measuring the performance of programers under controlled conditions for standard tasks. Statistically significant results indicated substantially faster debugging under online conditions in both studies. The results were ambiguous for central processor time--one study showed less computer time for debugging, and the other showed more time in the online mode. Perhaps the most important practical finding, overshadowing online/offline differences, involves the large and striking individual differences in programer performance. Attempts were made to relate observed individual differences to objective measures of programer experience and proficiency through factorial techniques. In line with the exploratory objectives of these studies, methodological problems encountered in designing and conducting these types of experiments are described, limitations of the findings are pointed out, hypotheses are presented to account for results, and suggestions are made for further research.

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Document Details

Document Type
Technical Report
Publication Date
Dec 20, 1966
Accession Number
AD0645438

Entities

People

  • E. E. Grant
  • H. Sackman
  • W. J. Erikson

Organizations

  • System Development Corporation

Tags

Communities of Interest

  • C4I
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Abstracts
  • Analysis Of Variance
  • Combinatorial Analysis
  • Computer Communications
  • Computer Programming
  • Computer Programs
  • Computer Science
  • Computers
  • Contracts
  • Data Processing
  • Data Science
  • Debugging
  • Experimental Design
  • Information Processing
  • Information Science
  • Standards
  • Statistical Analysis

Fields of Study

  • Psychology

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Brain and Cognitive Science; Experimental Psychology; Cognitive Neuroscience
  • Systems Analysis and Design