Evolutionary induced decision trees for dangerous software modules prediction

被引：17

作者：

Podgorelec, V ^{[1
]}

Kokol, P ^{[1
]}

机构：

[1] Univ Maribor, FERI, Lab Syst Design, SI-2000 Maribor, Slovenia

来源：

INFORMATION PROCESSING LETTERS | 2002年 / 82卷 / 01期

关键词：

software engineering; decision making; decision trees; evolutionary algorithms; software fault prediction;

D O I：

10.1016/S0020-0190(01)00284-8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We study the possibility of constructing decision trees with evolutionary algorithms in order to increase their predictive accuracy. We present a self-adapting evolutionary algorithm for the induction of decision trees and describe the principle of decision making based on multiple evolutionary induced decision trees-decision forest. The developed model is used as a fault predictive approach to foresee dangerous software modules, which identification can largely enhance the reliability of software. (C) 2001 Elsevier Science B.V. All rights reserved.

引用

页码：31 / 38

页数：8

共 50 条

[1] Evolutionary Decision Trees and Software Metrics for Module Defects Identification
Chis, Monica
PROCEEDINGS OF WORLD ACADEMY OF SCIENCE, ENGINEERING AND TECHNOLOGY, VOL 28, 2008, 28 : 273 - 277
[2] Classification and Prediction of Software Cost through Fuzzy Decision Trees
Papatheocharous, Efi
Andreou, Andreas S.
ENTERPRISE INFORMATION SYSTEMS-BK, 2009, 24 : 234 - 247
[3] Improving the reliability of medical software by predicting the dangerous software modules
Podgorelec V.
Heričko M.
Jurič M.B.
Rozman I.
Journal of Medical Systems, 2005, 29 (1) : 3 - 11
[4] Evolutionary design of decision trees
Podgorelec, Vili
Sprogar, Matej
Pohorec, Sandi
WILEY INTERDISCIPLINARY REVIEWS-DATA MINING AND KNOWLEDGE DISCOVERY, 2013, 3 (02) : 63 - 82
[5] A novel approach for software defect prediction using fuzzy decision trees
Marian, Zsuzsanna
Mircea, Ioan-Gabriel
Czibula, Istvan-Gergely
Czibula, Gabriela
PROCEEDINGS OF 2016 18TH INTERNATIONAL SYMPOSIUM ON SYMBOLIC AND NUMERIC ALGORITHMS FOR SCIENTIFIC COMPUTING (SYNASC), 2016, : 240 - 247
[6] Evolutionary Learning of Interpretable Decision Trees
Custode, Leonardo L.
Iacca, Giovanni
IEEE ACCESS, 2023, 11 : 6169 - 6184
[7] Evolutionary induction of mixed decision trees
Bialystok Technical University, Bialystok, Poland
不详
不详
Int. J. Data Warehouse. Min., 2007, 4 (68-82):
[8] Evolutionary construction of medical decision trees
Podgorelec, V
Kokol, P
PROCEEDINGS OF THE 20TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOL 20, PTS 1-6: BIOMEDICAL ENGINEERING TOWARDS THE YEAR 2000 AND BEYOND, 1998, 20 : 1202 - 1205
[9] Mixed decision trees: An evolutionary approach
Kretowski, Marek
Grzes, Marek
DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS, 2006, 4081 : 260 - 269
[10] Evolving Decision Trees for the Categorization of Software
Hosic, Jasenko
Tauritz, Daniel R.
Mulder, Samuel A.
2014 38TH ANNUAL IEEE INTERNATIONAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE WORKSHOPS (COMPSACW 2014), 2014, : 337 - 342

← 1 2 3 4 5 →