

{\bf Benefits to Society:} Software has become a
critical enabling technology for realization of
functions central to the realization of
information society.  Yet, software engineering as
a discipline continues to lags behind in terms of
its ability to provide engineering processes which
deliver artifacts of predictable quality within
the required time frame.  Our proposed research
addresses an interrelated set of key technical
barriers which, when resolved, will serve to
advance the accuracy and usefulness of defect
prediction models in large software development
projects. This understanding is an essential step
in minimizing the cost of software development
while, at the same time, achieving predictable
levels of reliability, necessary for maintaining
the US technological leadership in a global,
interconnected economy.

The PI and the Co-PI are active members of the
software engineering research team at West
Virginia University.   Over a number of years,
they have had a chance to analyze and improve the
development practices of large safety and mission
critical software systems at federal agencies
(NASA, DHS) as well as major commercial companies
(Computer Science Corporation, Northrop Grumman,
etc.). They plan to continue the interactions with
their research partners and organizations, as
these external research suggestions will help the
results of this research to be transferred into
the practice (see Section I, support letters).




In addition, in recent years the PI has been one
of the leaders and main promoters in the
grassroots development of public software
engineering repositories.  As the founding chair
of the PROMISE Workshop, Dr. Menzies advocated
that the submission of empirical papers to the
workshop be accompanied with the parallel
repository submission of the dataset used in the
study.  As the result, since 2005, PROMISE
repository (\url{http://promisedata.org/repository/})
has grown to include over 50 software engineering
datasets, allowing researchers to compare their
modeling techniques and repeat (or dispute) each
others results.  While the proposed research will
utilize PROMISE datasets, our plan is to enhance
some of the datasets by providing the
meta-knowledge related to the business environment
in which the datasets were generated, as described
in the proposal.

{\bf Dissemination of Results:} In addition to
traditional dissemination of our results in
journal and conference publications, through the
anticipated project website and regular
contributions to PROMISE repository (including our
modeling tools), alternate means will be explored
in order to inform non-technical audiences of the
work and the impact of software engineering
practices to society. Assisted by our graduate
assistants, we plan to participate in West
Virginia high school science days and technology
fairs organized periodically by the WV EPSCoR
office.  We will pay special attention to present
our work at the meetings of student chapters of
professional societies at West Virginia University
in hope of motivating their members to pursue
graduate education.


{\bf Impact on Education:}  West Virginia University and
Lane Department of Computer Science and Electrical
Engineering provide extensive educational
opportunities in the field of software
engineering.  The projects educational activities
will include involvement of undergraduates
(through a planned REU application to NSF) and
graduate students in research, and the development
of new and the enhancement of existing courses.
Undergraduate students will participate in the
research activities through their involvement in
the new program called LEAD, which includes
undergraduates into research program early in
their student careers. In the past, both PI and
co-PI monitored projects in which students
designed software based applications and systems.
LEAD framework is ideal for the introduction of
predictive methods in software engineering because
the projects span over multiple years and involve
2-3 successive generations of students.  This will
create the opportunity to analyze software
artifacts delivered in precious years and, thus,
apply and test the prediction models developed in
our research.   Overall project budget will cover
the expenses of these undergraduate LEAD/research
teams, including the cost of computers and summer
research stipends.

Research topics for graduate students will be
strongly correlated with the objectives of the
proposed project. Funding is requested for three
graduate students throughout the duration of the
project. We anticipate that the interaction
between undergraduate and graduate students will
be beneficial for both.  Women and minority
students will be encouraged to apply for
undergraduate research stipends and for graduate
assistantships.  Both the PI and the co-PI have a
record of successfully involving women and
minority students in research projects.

Curriculum development will closely follow
research topics covered by this proposal. Typical
teaching load for a research active faculty member
on a tenure-track position in the Department of
Computer Science and Electrical Engineering at WVU
is 3 courses per year.  The PI and co-PI offer
undergraduate and graduate classes in software
engineering (Advanced Software Engineering,
Software Reliability, Open Source Software) and
artificial intelligence (data mining).  In the
second project year, they plan to jointly develop
a new course, Predictive Models in Software
Engineering,, and include the research material
into existing undergraduate and graduate classes
and labs, which they regularly teach.  The PIs
will maintain a web page for each individual
course where all related course materials,
including class notes and reading lists will be
regularly posted.  Together with the dissemination
of research results through peer reviewed
publications, this will serve to promote and
publicize the results of this project.

{\bf Impact on Historically Underrepresented Groups in
Science and Engineering:} The PI and the Co-PI have
a successful record of including women and
minority students into undergraduate and graduate
research.  Among the 7 PhD graduates advised by
the Co-PI so far, three have been female. One of
our undergraduate advisees advisees, Ms. Kelly
Smith, has been named 2006 Academic All American
Third Team by USA Today. Our research labs
continue to maintain close to 50\% participation
of women/minority graduate research assistants
(for example,
\url{http://www.csee.wvu.edu/~cukic/students.html}).  We remain
strongly committed to bringing research and
educational opportunities to students from the
underrepresented groups.
