Regular expressions are routinely used in a variety of different application domains. But building a regular expression involves a considerable amount of skill, expertise, and creativity. In this work, the authors investigate whether a machine can surrogate these qualities and automatically construct regular expressions for tasks of realistic complexity. They discuss a large-scale experiment involving more than 1,700 users on 10 challenging tasks. The authors compare the solutions constructed by these users to those constructed by a tool based on genetic programming that they recently developed and made publicly available. The quality of automatically constructed solutions turned out to be similar to the quality of those constructed by the most skilled user group; the time for automatic construction was likewise similar to the time required by human users.

Can a Machine Replace Humans in Building Regular Expressions? A Case Study

BARTOLI, Alberto;DE LORENZO, ANDREA;MEDVET, Eric;TARLAO, FABIANO
2016-01-01

Abstract

Regular expressions are routinely used in a variety of different application domains. But building a regular expression involves a considerable amount of skill, expertise, and creativity. In this work, the authors investigate whether a machine can surrogate these qualities and automatically construct regular expressions for tasks of realistic complexity. They discuss a large-scale experiment involving more than 1,700 users on 10 challenging tasks. The authors compare the solutions constructed by these users to those constructed by a tool based on genetic programming that they recently developed and made publicly available. The quality of automatically constructed solutions turned out to be similar to the quality of those constructed by the most skilled user group; the time for automatic construction was likewise similar to the time required by human users.
2016
Pubblicato
File in questo prodotto:
File Dimensione Formato  
ieee-is-editoriale.pdf

Accesso chiuso

Descrizione: Articolo principale
Tipologia: Documento in Versione Editoriale
Licenza: Digital Rights Management non definito
Dimensione 465.32 kB
Formato Adobe PDF
465.32 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
2016-IEEEIS-CanAMachineBuildRegexes.pdf

accesso aperto

Descrizione: Articolo principale
Tipologia: Bozza finale post-referaggio (post-print)
Licenza: Digital Rights Management non definito
Dimensione 451.49 kB
Formato Adobe PDF
451.49 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2885868
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 15
  • ???jsp.display-item.citation.isi??? 12
social impact