M
Michael A. Martin
Researcher at Australian National University
Publications - 73
Citations - 3744
Michael A. Martin is an academic researcher from Australian National University. The author has contributed to research in topics: Confidence interval & Jackknife resampling. The author has an hindex of 25, co-authored 73 publications receiving 3590 citations. Previous affiliations of Michael A. Martin include Stanford University.
Papers
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Journal ArticleDOI
Bootstrap confidence intervalsCommentCommentCommentCommentRejoinder
Proceedings ArticleDOI
Finding application errors and security flaws using PQL: a program query language
TL;DR: This paper presents a language called PQL (Program Query Language) that allows programmers to express such questions easily in an application-specific context and develops both static and dynamic techniques to find solutions to PQL queries.
Journal ArticleDOI
On bootstrap resampling and iteration
Peter Hall,Michael A. Martin +1 more
TL;DR: In this paper, a single unifying approach to bootstrap resampling, applicable to a very wide range of statistical problems, has been proposed, including bias reduction, shrinkage, hypothesis testing and confidence interval construction.
Journal ArticleDOI
The transformational dimension in the realization of business value from information technology
TL;DR: Investigation of the concept of IT-enabled organizational transformation as a component of the value realized from IT at the firm level found it to exist as a distinct benefit category and to be closely related to other forms ofIT-generated business benefits.
Proceedings Article
Automatic generation of XSS and SQL injection attacks with goal-directed model checking
Michael A. Martin,Monica S. Lam +1 more
TL;DR: This paper presents QED, a goal-directed model-checking system that automatically generates attacks exploiting taint-based vulnerabilities in large Java web applications, for the first time where model checking has been used successfully on real-life Java programs to create attack sequences that consist of multiple HTTP requests.