Improving Quality of Data Exchange Files. An Industrial Case Study

Günter Fleck, Michael Moser, Josef Pichler

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

1 Citation (Scopus)


In the development of electrical machines users run a batch of command line programs by providing text-based data exchange files as input. The required structure and content of these files is often only informally documented and implicitly enforced by programs. Therefore, users are forced to execute programs without prior syntactic and semantic verification. To improve the quality of data exchange files, users need editor support that allows syntactic and semantic verification using grammar-based analyzers. In order to reduce the effort for creating grammars, we use grammar recovery which analyzes software artifacts and makes the retrieved knowledge visible as a language grammar. The assessment and completion of the extracted grammar requires both knowledge in software-language engineering and in the application domain. This paper examines whether the integration of grammar recovery with domain-specific languages is suitable for creating editor support for data exchange files. In particular, we are interested in whether we can recover (1) a grammar and validation rules from documentation and a corpus of example files. Furthermore, we are interested in whether (2) a domain-specific language (DSL) allows domain experts to provide missing details and evolve grammars. To answer these questions, we conducted an industrial case study on three different types of data exchange files. Results show that about 45% of the grammar rules could be recovered automatically and that the completion of the extracted grammars by end-users is a promising means to provide correct and maintainable grammars for data exchange files.
Original languageEnglish
Title of host publicationProduct-Focused Software Process Improvement - 20th International Conference, PROFES 2019, Proceedings
EditorsXavier Franch, Tomi Männistö, Silverio Martínez-Fernández
Place of PublicationCham
Number of pages15
ISBN (Print)9783030353322
Publication statusPublished - 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11915 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


  • Data quality
  • Domain-specific languages
  • Grammar recovery
  • Software evolution


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