* ICSE 2018 *
Sun 27 May - Sun 3 June 2018 Gothenburg, Sweden
Wed 30 May 2018 14:00 - 14:15 at E3 room - Programming and Code Analysis Chair(s): Thorsten Berger

Spreadsheets are commonly used in organizations as a programming tool for business-related calculations and decision making. Since faults in spreadsheets can have severe business impacts, a number of approaches from general software engineering have been applied to spreadsheets in recent years, among them the concept of code smells. Smells can in particular be used for the task of fault prediction. An analysis of existing spreadsheet smells, however, revealed that the predictive power of individual smells can be limited. In this work we therefore propose a machine learning based approach which combines the predictions of individual smells by using an AdaBoost ensemble classifier. Experiments on two public datasets containing real-world spreadsheet faults show significant improvements in terms of fault prediction accuracy.

Wed 30 May

icse-2018-New-Ideas-and-Emerging-Results
14:00 - 15:30: NIER - New Ideas and Emerging Results - Programming and Code Analysis at E3 room
Chair(s): Thorsten BergerChalmers University of Technology, Sweden
icse-2018-New-Ideas-and-Emerging-Results14:00 - 14:15
Talk
DOI Pre-print File Attached
icse-2018-New-Ideas-and-Emerging-Results14:15 - 14:30
Talk
Marcelino Rodriguez-Cancio, Benoit BaudryKTH Royal Institute of Technology, Sweden, Jules WhiteVanderbilt University
icse-2018-New-Ideas-and-Emerging-Results14:30 - 14:45
Short-paper
Nghi Duy Quoc BuiSingapore Management University, Singapore, Lingxiao JiangSingapore Management University
Pre-print
icse-2018-New-Ideas-and-Emerging-Results14:45 - 15:00
Talk
Fernando Lopez de La MoraUniversity of Alberta, Sarah NadiUniversity of Alberta
Pre-print
icse-2018-New-Ideas-and-Emerging-Results15:00 - 15:15
Talk
Federico CiccozziMalardalen University
Link to publication
icse-2018-New-Ideas-and-Emerging-Results15:15 - 15:30
Talk
Eric BoddenHeinz Nixdorf Institut, Paderborn University and Fraunhofer IEM
Pre-print