Searching repositories of web application models

Alessandro Bozzon*, Marco Brambilla, Piero Fraternali

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

11 Citations (Scopus)

Abstract

Project repositories are a central asset in software development, as they preserve the technical knowledge gathered in past development activities. However, locating relevant information in a vast project repository is problematic, because it requires manually tagging projects with accurate metadata, an activity which is time consuming and prone to errors and omissions. This paper investigates the use of classical Information Retrieval techniques for easing the discovery of useful information from past projects. Differently from approaches based on textual search over the source code of applications or on querying structured metadata, we propose to index and search the models of applications, which are available in companies applying Model-Driven Engineering practices. We contrast alternative index structures and result presentations, and evaluate a prototype implementation on real-world experimental data.
Original languageEnglish
Title of host publicationWeb Engineering - 10th International Conference, ICWE 2010, Proceedings
Place of PublicationBerlin
PublisherSpringer
Pages1-15
Number of pages15
Volume6189 LNCS
ISBN (Print)3642139108, 9783642139109
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event10th International Conference on Web Engineering, ICWE 2010 - Berlin, Vienna, Austria
Duration: 5 Jul 20109 Jul 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6189 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Conference on Web Engineering, ICWE 2010
Country/TerritoryAustria
CityVienna
Period5/07/109/07/10

Keywords

  • Business Process
  • Index Structure
  • Query Language
  • Index Size
  • Content Processing

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