By Topic

Dynamic Customization of Data Structures Instances Using an Agent Based Approach

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

3 Author(s)
Istvan Gergely Czibula ; Dept. of Comput. Sci., Babes-Bolyai Univ., Cluj-Napoca, Romania ; Gabriela Czibula ; Adriana Mihaela Guran

Abstract data types (ADTs) represent the core for any software application, and a proper use of them is an essential requirement for developing a robust and efficient system. Moreover, a proper instantiation of a data structure that implements an abstract data type can greatly impact the performance of the system. In this paper we propose a learning approach for the dynamic configuration of data structures instances in a software system. In order to adapt a data structure to the system's current execution context, a neural network will be used and an agent based system is proposed. We experimentally evaluate our system on a case study, emphasizing the advantages of the proposed approach.

Published in:

Symbolic and Numeric Algorithms for Scientific Computing (SYNASC), 2009 11th International Symposium on

Date of Conference:

26-29 Sept. 2009