By Topic

Static Analysis of Data-Intensive Applications

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
Csaba Nagy ; Dept. of Software Eng., Univ. of Szeged, Szeged, Hungary

Data-intensive systems are designed to handle data at massive scale, and during the years they might evolve to very large, complex systems. In order to support maintenance tasks of these systems several techniques have been developed to analyze the source code of applications or to analyze the underlying databases for the purpose of reverse engineering, e.g. quality assurance or program comprehension. However, only a few techniques take into account the specialties of data-intensive systems (e.g. dependencies arising via database accesses). In this thesis we conducted research to analyze and to improve data-intensive applications via different methods based on static analysis: methods for recovering architecture of data-intensive systems and a quality assurance methodology for applications developed in Magic 4GL. We targeted SQL as the most widespread databases are relational databases using certain dialect of SQL for their queries. With the proposed techniques we were able to analyze large scale industrial projects, such as banking systems with more than 3 million lines of code, and we successfully recovered architecture maps and quality issues of these systems.

Published in:

Software Maintenance and Reengineering (CSMR), 2013 17th European Conference on

Date of Conference:

5-8 March 2013