ACM Home Page
Please provide us with feedback. Feedback
An empirical study of fault localization for end-user programmers
Full text PdfPdf (252 KB)
Source International Conference on Software Engineering archive
Proceedings of the 27th international conference on Software engineering table of contents
St. Louis, MO, USA
SESSION: Fault localization table of contents
Pages: 352 - 361  
Year of Publication: 2005
ISBN:1-59593-963-2
Authors
Joseph R. Ruthruff  University of Nebraska-Lincoln, Lincoln, Nebraska
Margaret Burnett  Oregon State University, Corvallis, Oregon
Gregg Rothermel  University of Nebraska-Lincoln, Lincoln, Nebraska
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 67,   Citation Count: 10
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1062455.1062523
What is a DOI?

ABSTRACT

End users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been little research on finding ways to help these programmers with the dependability of their software. We have been addressing this problem in several ways, one of which includes supporting end-user debugging activities through fault localization techniques. This paper presents the results of an empirical study conducted in an end-user programming environment to examine the impact of two separate factors in fault localization techniques that affect technique effectiveness. Our results shed new insights into fault localization techniques for end-user programmers and the factors that affect them, with significant implications for the evaluation of those techniques.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
H. Agrawal, J. Horgan, S. London, and W. Wong. Fault localization using execution slices and dataflow tests. In Proceedings of the Sixth IEEE International Symposium on Software Reliability Engineering, pages 143--151, Toulouse, France, October 1995.
 
3
Y. Ahmad, T. Antoniu, S. Goldwater, and S. Krishnamurthi. A type system for statically detecting spreadsheet errors. In Proceedings of the 18th IEEE International Conference on Automated Software Engineering, pages 174--183, Montreal, Quebec, Canada, October 2003.
 
4
C. Allwood. Error detection processes in statistical problem solving. Cognitive Science, 8(4):413--437, 1984.
 
5
 
6
Y. Ayalew and R. Mittermeir. Spreadsheet debugging. In Proceedings of the European Spreadsheet Risks Interest Group, Dublin, Ireland, July 2003.
7
 
8
 
9
 
10
P. Bunus and P. Fritzson. Semi-automatic fault localization and behavior verification for physical system simulation models. In Proceedings of the 18th IEEE International Conference on Automated Software Engineering, pages 253--258, Montreal, Quebec, Canada, October 2003.
 
11
 
12
C. Corritore, B. Kracher, and S. Wiedenbeck. Trust in the online environment. In HCI International, volume 1, pages 1548--1552, New Orleans, Louisiana, USA, August 2001.
13
 
14
D. Hilzenrath. Finding errors a plus, Fannie says; mortgage giant tries to soften effect of $1 billion in mistakes. The Washington Post, October 31, 2003.
15
16
 
17
J. Lyle and M. Weiser. Automatic program bug location by program slicing. In Proceedings of the 2nd International Conference on Computers and Applications, pages 877--883, 1987.
18
 
19
H. Pan and E. Spafford. Toward automatic localization of software faults. In Proceedings of the 10th Pacific Northwest Software Quality Conference, October 1992.
 
20
R. Panko. Finding spreadsheet errors: Most spreadsheet errors have design flaws that may lead to long-term miscalculation. Information Week, page 100, May 1995.
 
21
22
 
23
M. Renieris and S. Reiss. Fault localization with nearest neighbor queries. In Proceedings of the 18th IEEE International Conference on Automated Software Engineering, pages 30--39, Montreal, Quebec, Canada, October 2003.
 
24
G. Robertson. Officials red-faced by $24m gaffe: Error in contract bid hits bottom line of TransAlta Corp. Ottawa Citizen, June 5, 2003.
25
26
 
27
J. Ruthruff, S. Prabhakararao, J. Reichwein, C. Cook, E. Creswick, and M. Burnett. Interactive, visual fault localization support for end-user programmers. Journal of Visual Languages and Computing, 2005 (to appear).
 
28
J. Sajaniemi. Modeling spreadsheet audit: A rigorous approach to automatic visualization. Journal on Visual Languages and Computing, 11(1):49--82, February 2000.
 
29
S. Siegel and N. Castellan Jr. Non-parametric Statistics for the Behavioral Sciences. McGraw Hill, Boston, Massachusetts, USA, 1998.
 
30
F. Tip. A survey of program slicing techniques. Journal on Programming Languages, 3(3):121--189, 1995.
 
31
J. Voas. Software testability measurement for assertion placement and fault localization. In Proceedings of the International Workshop on Automated and Algorithmic Debugging, pages 133--144, 1995.
32
33
 
34

CITED BY  10

Collaborative Colleagues:
Joseph R. Ruthruff: colleagues
Margaret Burnett: colleagues
Gregg Rothermel: colleagues