The recent proliferation of inexpensive electroencephalography (EEG) devices is fueling a rising interest in associating detectable indicators of brain activity with human performance factors. In this thesis, the focus is on programmer effort in program comprehension tasks. Traditionally, measures of effort are made using self-reported surveys (NASA-TLX), task timing, and task accuracy. This work explores the feasibility of using EEG to produce a more direct and quantitative measure of effort. Effort is measured across a number of tasks with varying difficulty and comparisons are made between traditional and EEG measures of effort. Initially, the program comprehension tasks are ranked in order of complexity as computed by a number of classic software complexity metrics, such as Halstead’s complexity metrics and McCabe’s cyclomatic complexity. Likewise, we compute a ranking of tasks based on observed effort as a basis of comparison between EEG and complexity measures.
|Commitee:||Bouvier, Dennis, McKenney, Mark|
|School:||Southern Illinois University at Edwardsville|
|School Location:||United States -- Illinois|
|Source:||MAI 57/01M(E), Masters Abstracts International|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be