Eric A. Hardisty

dblp:19/2364 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Software engineering, systems software and programming languages · 1Human-computer interaction and ubiquitous computing · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Software engineering, system software, and programming languages
1 paper
Software maintenance and evolution · 50% Software testing · 50%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Software maintenance and evolution
dynamic software updating
0.112012
Evaluating Dynamic Software Update Safety Using Systematic Testing · IEEE Trans. Software Eng. 2012
Software testing
systematic testing
0.112012
Evaluating Dynamic Software Update Safety Using Systematic Testing · IEEE Trans. Software Eng. 2012

Methods — techniques the papers use, named apart from their topics

type safety analysis · 0.1empirical evaluation · 0.1
YearPublicationVenuePosition
2012 Evaluating Dynamic Software Update Safety Using Systematic Testing
abstract
Dynamic software updating (DSU) systems patch programs on the fly without incurring downtime. To avoid failures due to the updating process itself, many DSU systems employ timing restrictions. However, timing restrictions are theoretically imperfect, and their practical effectiveness is an open question. This paper presents the first significant empirical evaluation of three popular timing restrictions: activeness safety (AS), which prevents updates to active functions; con-freeness safety (CFS), which only allows modifications to active functions when doing so is provably type-safe; and manual selection, which permits updates at developer chosen program points. We evaluated these timing restrictions using a series of DSU patches to three programs: OpenSSH, vsftpd, and ngIRCd. We systematically applied updates at each distinct update point reached during execution of a suite of system tests for these programs to determine which updates pass and which fail. We found that all three timing restrictions prevented most failures, but only manual selection allowed none. Further, although CFS and AS allowed many more update points, manual selection still supported updates with minimal delay. Finally, we found that manual selection required the least developer effort. Overall, we conclude that manual selection is most effective.
Christopher M. Hayden, Edward K. Smith, Eric A. Hardisty, Michael Hicks 0001, Jeffrey S. Foster
IEEE Trans. Software Eng.3
2007 RegeXeX: an interactive system providing regular expression exercises
abstract
This paper presents RegeXeX (Regular expression exercises), an interactive system for teaching students to write regular expressions. The system poses problems (prose descriptions of languages), students enter solutions (regular expressions defining these languages), and the system provides feedback. What is novel in this system is the type of feedback: students are not merely told that a submitted regular expression is wrong, they are given examples of strings that the expression either matches and shouldn't or does not match and should, and asked to try again. Additionally, student responses need only be equivalent to the solution, not identical. Results of classroom experience with this system are also reported, and demonstrate its effectiveness in teaching students to write regular expressions with little or no instructor interaction.RegeXeX is a freely available, portable system, written in C++ and using the Qt library for its GUI. It is distributed with several exercise sets, but is designed so instructors can easily write their own. The system logs student work and offers facilities for submitting log-files to instructors as well, allowing for automatic grading, or in-depth analysis of student performance and evolution of responses throughout the exercise set.
Christopher W. Brown 0001, Eric A. Hardisty
SIGCSE2