24,447 research outputs found
AS-943-22 Resolution on the Creation of a School of Applied Computing
Adopts the mission, vision, and structure of the School of Applied Computing contained in the attachment to this resolution, and approves the creation of the School of Applied Computing
An Analysis of Scripting Languages for Research in Applied Computing
There are several scripting languages that exist
today. However, some are used more frequently and popular
than others. This is due to certain characteristics and features
that they possess. Particularly in applied computing fields like
software engineering, bioinformatics and computational biology,
scripting languages are gaining popularity. This paper presents a
comparative study of ten popular scripting languages that are
used in the above mentioned fields/area. For making comparison,
we have identified the factors against which these languages are
evaluated. Accordingly, based on selected criteria we determine
their suitability in the fields of software engineering,
bioinformatics and computational biology research. This will
serve as a guide to researchers to choose the appropriate
scripting language in the various fields
Personalized Ranking for Context-Aware Venue Suggestion
Making personalized and context-aware suggestions of venues to the users is
very crucial in venue recommendation. These suggestions are often based on
matching the venues' features with the users' preferences, which can be
collected from previously visited locations. In this paper we present a novel
user-modeling approach which relies on a set of scoring functions for making
personalized suggestions of venues based on venues content and reviews as well
as users context. Our experiments, conducted on the dataset of the TREC
Contextual Suggestion Track, prove that our methodology outperforms
state-of-the-art approaches by a significant margin.Comment: The 32nd ACM SIGAPP Symposium On Applied Computing (SAC), Marrakech,
Morocco, April 4-6, 201
Interview with Robert Van Spyk
Interview with Robert Van Spyk, Professor Emeritus, Telecommunications, Multimedia and Applied Computing, Science, Technology and Information Resources Centerhttps://digitalcommons.csumb.edu/oralhist_founding-faculty/1025/thumbnail.jp
Where are your Manners? Sharing Best Community Practices in the Web 2.0
The Web 2.0 fosters the creation of communities by offering users a wide
array of social software tools. While the success of these tools is based on
their ability to support different interaction patterns among users by imposing
as few limitations as possible, the communities they support are not free of
rules (just think about the posting rules in a community forum or the editing
rules in a thematic wiki). In this paper we propose a framework for the sharing
of best community practices in the form of a (potentially rule-based)
annotation layer that can be integrated with existing Web 2.0 community tools
(with specific focus on wikis). This solution is characterized by minimal
intrusiveness and plays nicely within the open spirit of the Web 2.0 by
providing users with behavioral hints rather than by enforcing the strict
adherence to a set of rules.Comment: ACM symposium on Applied Computing, Honolulu : \'Etats-Unis
d'Am\'erique (2009
Improving Function Coverage with Munch: A Hybrid Fuzzing and Directed Symbolic Execution Approach
Fuzzing and symbolic execution are popular techniques for finding
vulnerabilities and generating test-cases for programs. Fuzzing, a blackbox
method that mutates seed input values, is generally incapable of generating
diverse inputs that exercise all paths in the program. Due to the
path-explosion problem and dependence on SMT solvers, symbolic execution may
also not achieve high path coverage. A hybrid technique involving fuzzing and
symbolic execution may achieve better function coverage than fuzzing or
symbolic execution alone. In this paper, we present Munch, an open source
framework implementing two hybrid techniques based on fuzzing and symbolic
execution. We empirically show using nine large open-source programs that
overall, Munch achieves higher (in-depth) function coverage than symbolic
execution or fuzzing alone. Using metrics based on total analyses time and
number of queries issued to the SMT solver, we also show that Munch is more
efficient at achieving better function coverage.Comment: To appear at 33rd ACM/SIGAPP Symposium On Applied Computing (SAC). To
be held from 9th to 13th April, 201
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