Λεπτομέρειες βιβλιογραφικής εγγραφής
| Τίτλος: |
SEDMR: A spreadsheet error detection approach based on metamorphic testing. |
| Συγγραφείς: |
Yang, Bo1 (AUTHOR) yangbo@bjfu.edu.cn, Hu, Xuelian1 (AUTHOR) 3205273851@qq.com, Ma, Jiatong1 (AUTHOR) JiaTongMa@bjfu.edu.cn |
| Πηγή: |
Information & Software Technology. Jun2026, Vol. 194, pN.PAG-N.PAG. 1p. |
| Θεματικοί όροι: |
*Defect tracking (Computer software development), Computer software testing |
| Reviews & Products: |
Microsoft Excel (Computer software) |
| Περίληψη: |
Spreadsheets are ubiquitous in modern society, used in various domains such as corporate finance, market analysis, and personal budgeting. Despite their widespread use, spreadsheets are prone to errors, which can lead to significant issues, including financial losses. While numerous efforts have been made to detect these errors, existing methods often fail to provide a comprehensive, systematic approach to error detection. The primary goal of this research is to develop a more effective and systematic method for detecting errors in spreadsheets. This involves exploring a new research direction using Metamorphic Testing (MT), specifically focusing on defining Metamorphic Relations (MRs) between formula cells and reference cells in spreadsheets. We introduce a novel spreadsheet error detection approach called SEDMR (Spreadsheet Error Detection using MRs). SEDMR leverages expanded and tailored MRs that consider both cell data values and formula patterns, offering a comprehensive framework for error detection. The approach includes systematic steps such as extracting spreadsheet cell arrays, selecting MRs, detecting errors, and marking error cells. SEDMR's effectiveness is demonstrated through large-scale experiments on extensive datasets, including the EUSES and Enron corpora. The experiments, conducted on 160 spreadsheets, show that SEDMR outperforms state-of-the-art techniques in terms of error detection effectiveness. The SEDMR approach significantly enhances the efficiency and accuracy of spreadsheet error detection compared to traditional ad-hoc methods. Its scalability and applicability to a wide range of spreadsheet structures make it a versatile solution for real-world scenarios. This research not only provides a robust method for spreadsheet error detection but also opens up promising avenues for future research in this area. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: |
Business Source Index |