Generation of Relevant Spreadsheet Repair Candidates

• Type: Article in International Conference Proceedings Book
• Date: 2014

Authors

Hofer, B (Author) Other; Abreu, R (Author) FEUP; Perez, A (Author) Other; Wotawa, F (Author) Other

Conference proceedings International

Title: 21ST EUROPEAN CONFERENCE ON ARTIFICIAL INTELLIGENCE (ECAI 2014)

Pages: 1027-+

21st European Conference on Artificial Intelligence (ECAI)

Prague, CZECH REPUBLIC, AUG 18-22, 2014

Indexing

ISI Web of Knowledge - 1 Citation

Scopus - 1 Citation

Other information

Authenticus ID: P-00A-6P3

DOI: 10.3233/978-1-61499-419-0-1027

Abstract (EN): Spreadsheets are amongst the most successful examples of end user programming. Because of their, still increasing, importance for companies, spreadsheets have drastic economical and societal impact. Hence, locating and fixing spreadsheet faults is important and deserves attention from the research community. A state-of-the-art technique uses genetic programming for generating repair candidates, but a limitation that hinders real-world application is that it still computes too many repair candidates. In this paper, we discuss a novel technique based on constraint solving that uses distinguishing test cases to narrow down the number of repair candidates.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 2