On the empirical evaluation of similarity coefficients for spreadsheets fault localization

• Type: Article in International Scientific Journal
• Date: 2015

Authors

Birgit Hofer (Author) Other; Alexandre Perez (Author) Other; Rui Abreu (Author) FEUP; Franz Wotawa (Author) Other

Journal

Title: Automated Software Engineering

Vol. 22

Pages: 47-74

ISSN: 0928-8910

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 14 Citations

Scopus - 24 Citations

Scientific classification

FOS: Natural sciences > Computer and information sciences

Other information

Authenticus ID: P-00A-63Y

DOI: 10.1007/s10515-014-0145-3

Abstract (EN): Spreadsheets are by far the most prominent example of end-user programs of ample size and substantial structural complexity. They are usually not thoroughly tested so they often contain faults. Debugging spreadsheets is a hard task due to the size and structure, which is usually not directly visible to the user, i.e., the functions are hidden and only the computed values are presented. A way to locate faulty cells in spreadsheets is by adapting software debugging approaches for traditional procedural or object-oriented programming languages. One of such approaches is spectrum-based fault localization (SFL). In this paper, we study the impact of different similarity coefficients on the accuracy of SFL applied to the spreadsheet domain. Our empirical evaluation shows that three of the 42 studied coefficients (Ochiai, Jaccard and Sorensen-Dice) require less effort by the user while inspecting the diagnostic report, and can also be used interchangeably without a loss of accuracy. In addition, we illustrate the influence of the number of correct and incorrect output cells on the diagnostic report.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 28