Metric-Based Fault Prediction for Spreadsheets
| Autor: | Dietmar Jannach, Patrick Koch, Franz Wotawa, Konstantin Schekotihin, Birgit Hofer |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
business.industry
Computer science 020207 software engineering 02 engineering and technology Machine learning computer.software_genre Fault (power engineering) Fault detection and isolation Random forest Range (mathematics) Software Metric (mathematics) 0202 electrical engineering electronic engineering information engineering Data analysis Artificial intelligence Isolation (database systems) business computer |
| Zdroj: | IEEE Transactions on Software Engineering. 47:2195-2207 |
| ISSN: | 2326-3881 0098-5589 |
| Popis: | Electronic spreadsheets are widely used in organizations for various data analytics and decision-making tasks. Even though faults within such spreadsheets are common and can have significant negative consequences, today's tools for creating and handling spreadsheets provide limited support for fault detection, localization, and repair. Being able to predict whether a certain part of a spreadsheet is faulty or not is often central for the implementation of such supporting functionality. In this work, we propose a novel approach to fault prediction in spreadsheet formulas, which combines an extensive catalog of spreadsheet metrics with modern machine learning algorithms. An analysis of the individual metrics from our catalog reveals that they are generally suited to discover a wide range of faults. Their predictive power is, however, limited when considered in isolation. Therefore, in our approach we apply supervised learning algorithms to obtain fault predictors that utilize all data provided by multiple spreadsheet metrics from our catalog. Experiments on different datasets containing faulty spreadsheets show that particularly Random Forests classifiers are often effective. As a result, the proposed method is in many cases able to make highly accurate predictions whether a given formula of a spreadsheet is faulty. 1 1. Results of a preliminary study were published in [1] . |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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