Using the genetic algorithm to build optimal neural networks for fault-prone module detection

被引：12
|
作者：
Hochman, R [1 ]
Khoshgoftaar, TM [1 ]
Allen, EB [1 ]
Hudepohl, JP [1 ]
机构：
[1] FLORIDA ATLANTIC UNIV,DEPT COMP SCI & ENGN,BOCA RATON,FL 33431
来源：
SEVENTH INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING, PROCEEDINGS | 1996年
关键词：
backpropagation; classification problem; fault-prone module; fitness function; genetic algorithm; neural network; simulated evolution; software engineering problem; software metrics; software quality;
D O I：
10.1109/ISSRE.1996.558759
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
引用
收藏
页码：152 / 162
页数：11
相关论文
共 50 条
  • [1] Early prediction of software fault-prone module using artificial neural network
    Bisi, Manjubala
    Goyal, Neeraj Kumar
    International Journal of Performability Engineering, 2015, 11 (01) : 43 - 52
  • [2] Identifying fault-prone function blocks using the neural networks - An empirical study
    Hong, SB
    Kim, K
    1997 IEEE PACIFIC RIM CONFERENCE ON COMMUNICATIONS, COMPUTERS AND SIGNAL PROCESSING, VOLS 1 AND 2: PACRIM 10 YEARS - 1987-1997, 1997, : 790 - 793
  • [3] THE DETECTION OF FAULT-PRONE PROGRAMS
    MUNSON, JC
    KHOSHGOFTAAR, TM
    IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 1992, 18 (05) : 423 - 433
  • [4] Experimental Study of Discriminant Method with Application to Fault-prone Module Detection
    Guo, Gege
    Guo, Ping
    2008 INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND SECURITY, VOLS 1 AND 2, PROCEEDINGS, 2008, : 204 - 209
  • [5] Result Evaluation of Acceptance Testing using Predicting Fault-Prone Module
    Shrivastava, Ananya
    Rajavat, Anand
    2016 SYMPOSIUM ON COLOSSAL DATA ANALYSIS AND NETWORKING (CDAN), 2016,
  • [6] Assessing the Differences of Clone Detection Methods Used in the Fault-Prone Module Prediction
    Tsunoda, Masateru
    Kamei, Yasutaka
    Sawada, Atsushi
    2016 IEEE 23RD INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER), VOL 3, 2016, : 15 - 16
  • [7] Fault-Prone Module Prediction Approaches Using Identifiers in Source Code
    Mizuno, Osamu
    Kawashima, Naoki
    Kawamoto, Kimiaki
    INTERNATIONAL JOURNAL OF SOFTWARE INNOVATION, 2015, 3 (01) : 36 - 49
  • [8] Fault-Prone Module Prediction Using a Prediction Model and Manual Inspection
    Kasai, Norimitsu
    Morisaki, Shuji
    Matsumoto, Kenichi
    2013 20TH ASIA-PACIFIC SOFTWARE ENGINEERING CONFERENCE (APSEC 2013), VOL 1, 2013, : 106 - 115
  • [9] Outlier Elimination Technique Using Deletion-Imputation Iteration for Fault-Prone Module Detection
    Toda, Koji
    Tsunoda, Masateru
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2023, 18 (10) : 1653 - 1663
  • [10] Fault-prone module detection using large-scale text features based on spam filtering
    Hideaki Hata
    Osamu Mizuno
    Tohru Kikuno
    Empirical Software Engineering, 2010, 15 : 147 - 165
12345