The ability of data mining to provide predictive information
derived from huge databases became an effective tool in the hands
of companies and individuals، allowing them to focus on areas that
are important to them from the massive data generated
by the
march of their daily lives. Along with the increasing importance of
this science there was a rapidly increasing in the tools that produced
to implement the theory concepts as fast as possible. So it will be
hard to take a decision on which of these tools is the best to
perform the desired task. This study provides a comparison
between the two most commonly used data mining tools according
to opinion polls، namely: Rapidminer and R programming language
in order to help researchers and developers to choose the best suited
tool for them between the two. Adopted the comparison on seven
criteria: platform، algorithms، input/output formats، visualization،
user’s evaluation، infrastructure and potential development، and
performance by applying a set of classification algorithms on a
number of data sets and using two techniques to split data set: cross
validation and hold-out to make sure of the results. The Results
show that R supports the largest number of algorithms، input/output
formats، and visualization. While Rapidminer superiority in terms
of ease of use and support for a greater number of platforms. In
terms of performance the accuracy of classification models that
were built using the R packages were higher. That was not true in
some cases imposed by the nature of the data because we did not
added any pre-processing stage. Finally the preference option in
any tool is depending on the extent of the user experience and
purpose that the tool is used for
Through our study, the HadoopOperationTesting software library
has been developed to provide Big Data applications labs with a
mechanism to test their applications in a simulated environment for
the Hadoop environment with a similar mechanism to test
traditional applications using the JUnit library.
This study will put spot light on web applications testing methods
and tools from the security aspects, and we will explain the details
about using these tools, after we have explained the most famous
weak points and vulnerabilities that web appli
cations suffer from.
At the end we will evaluate these tools.
By this study we try to help developers to choose the most
suitable method and tool for their needs.