J
Joanne E. Hale
Researcher at University of Alabama
Publications - 45
Citations - 1463
Joanne E. Hale is an academic researcher from University of Alabama. The author has contributed to research in topics: Software development & Software evolution. The author has an hindex of 11, co-authored 45 publications receiving 1357 citations.
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Types of software evolution and software maintenance
TL;DR: The paper provides a classified list of maintenance activities and a condensed decision tree as a summary guide to the proposed evidence-based classification of the types of software evolution and software maintenance.
Posted Content
Information Disclosure on Mobile Devices: Re- examining Privacy Calculus with Actual User Behavior
TL;DR: A more realistic experimental methodology designed to replicate real perceptions of privacy risk and capture the effects of actual information disclosure decisions is proposed and tested, finding that only a weak, albeit significant, relationship exists between information disclosure intentions and actual disclosure.
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Crisis Response Communication Challenges: Building Theory From Qualitative Data
TL;DR: In this article, the authors report results of a qualitative study that examined communication challenges decision makers experience during the response stage of crisis management, concluding that response is perhaps the most critical phase of decision making.
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Information disclosure on mobile devices: Re-examining privacy calculus with actual user behavior
TL;DR: In this paper, a more realistic experimental methodology was proposed and tested to replicate real perceptions of privacy risk and capture the effects of actual information disclosure decisions, and the results of a controlled experiment involving consumers (n=1025) in a range of ages, levels of education, and employment experience.
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Cyclomatic Complexity and Lines of Code: Empirical Evidence of a Stable Linear Relationship
TL;DR: Evidence is presented that not only that the linear relationship between LOC and CC is stable, but the aspects of code complexity that CC measures, such as the size of the test case space, grow linearly with source code size across languages and programming paradigms.