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Tool Support for Data Validation by End-User Programmers

Tool Support for Data Validation by End-User Programmers. Christopher Scaffidi Brad Myers, Mary Shaw Carnegie Mellon University. Target audience: End-user programmers. In 2012, in American workplaces 90 million computer end users 55 million of whom will create Spreadsheets Databases

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Tool Support for Data Validation by End-User Programmers

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  1. Tool Support for Data Validationby End-User Programmers Christopher Scaffidi Brad Myers, Mary Shaw Carnegie Mellon University

  2. Target audience:End-user programmers • In 2012, in American workplaces • 90 million computer end users • 55 million of whom will create • Spreadsheets • Databases • Web applications Introduction Topes  Demonstration  Conclusion

  3. An input validation problemobserved during contextual inquiry Valid? “EDSH 225” Questionable? “EDXH 225” Valid but wrong format? “Smith 225” Or obviously invalid? “Robotics Institute” Introduction Topes  Demonstration  Conclusion

  4. Underlying problem: abstraction mismatch • Tools support strings, ints, floats, sometimes dates. • Problem domain involves higher-level categories: • University names • Person names • CMU phone numbers • CMU room numbers • These data categories are: • Short human-readable strings • Multi-format • Sometimes ambiguous (non-binary scale of validity) • Often particular to certain groups of people Introduction Topes  Demonstration  Conclusion

  5. Limitations of existing approaches • Types do not support questionable values • Grammars do not, either, nor can they reformat • Information extraction algorithms rely on grammatical cues that are absent during validation • Cues, Forms/3, -calculus, Slate, pollution markers, etc, infer numerical constraints but not constraints on strings, nor are they platform-independent Introduction Topes  Demonstration  Conclusion

  6. New Approach: Topes • A tope = a platform-independent abstraction describing how to recognize and transformstrings in one category of data • Greek word for “place,” because each corresponds to a data category with a natural place in the problem domain Introduction Topes Demonstration  Conclusion

  7. A tope is a graph.Node = format, edge = transformation Notional representation for a CMU room number tope… Formal building name& room number Elliot Dunlap Smith Hall 225 Building abbreviation& room number EDSH 225 Colloquial building name& room number Smith 225 Introduction Topes Demonstration  Conclusion

  8. A tope is a conceptual abstraction.A tope implementation is code. • Each tope implementation has executable functions: • 1 isa:string[0,1] function per format, for recognizing instances of the format (a fuzzy set) • 0 or more trf:stringstring functions linking formats, for transforming values from one format to another • Validation function: (str) = max(isaf(str)) where f ranges over tope’s formats • Valid when (str) = 1 • Invalid when (str) = 0 • Questionable when 0 < (str) < 1 Introduction Topes Demonstration  Conclusion

  9. Today’s demonstration(using our latest version) • Create phone number tope • Infer boilerplate from examples • What are formats, parts, and constraints? • Label parts, add/fix constraints, test in tool • Validate spreadsheet data • Transform spreadsheet data • Reuse phone number tope • Create web application • Attach tope-based validator, configure, execute • Valid / invalid / questionable / valid-but-misformatted Introduction Topes Demonstration  Conclusion

  10. Contributions highlighted today • A model for data... • Short, human-readable strings • Ambiguous categories • Multiple formats • Implementation features: • Inference of customizable formats from examples • Soft constraints • Human-readable error messages • Validation code is reusable across platforms Introduction Topes Demonstration  Conclusion

  11. Other contributionsnot highlighted today • Validating with topes (quantitatively) improves… • Accuracy of validation • Reusability of validation code • Subsequent duplicate identification • Additional tool features: • Inter-tope reference (ie: “topes in topes”) • Whitelists • Various additional auto-transformation features • Overriding auto-transformation with JavaScript Introduction Topes Demonstration  Conclusion

  12. Validation and Tool Maturity • Expressiveness • Have implemented dozens of topes • Usability • Fast creation of accurate formats by users in study • Usefulness • Integrated w/ Excel, Visual Studio, and an XML library • Integrated by IBM & Univ. Nebraska into other tools Introduction Topes Demonstration  Conclusion

  13. Thank You… • To Jeff Magee, Betty Cheng, Barbara Ryder, Margaret Burnett, and others at ICSE 2007 for early feedback • To NSF for funding • To ICSE 2008 for this opportunity to present Introduction Topes Demonstration  Conclusion

  14. Available for download http://www.cs.cmu.edu/~cscaffid/software.shtml Or Google for "Topes SDK" Introduction Topes Demonstration  Conclusion

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