Improving Spectrum-Based Fault Localization for Spreadsheet Debugging

Spreadsheets often contain faults that are difficult to localize. Spectrum-based Fault Localization (SFL) assists users in the fault localization process by ranking cells by their suspiciousness to contain a fault. Since the ranking of the basic SFL approach is often imprecise, we propose three techniques to improve it, i.e., dynamic cones, grouping, and tie-breaking. We evaluate these techniques with three spreadsheet corpora comprising more than 1,000 faulty spreadsheets of different size and structure. While dynamic cones do not come with large improvements, grouping and tie-breaking do. Grouping has a positive impact on about 50% of the spreadsheets with almost no negative effects. The same holds for tie-breaking, where some of the strategies offer high positive impact while keeping the risk of negative influences low.

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