2018 IEEE 25th International Conference on Software Analysis, Evolution and Reengineering (SANER)
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Abstract

Complex engineering problems are typically solved by running a batch of software programs. Data exchange between these software programs is frequently based on semi-structured text files. These files are edited by text editors providing basic input support, however without proper input validation prior program execution. Consequently, even minor lexical or syntactic errors cause software programs to stop without delivering a result. To tackle these problems a more specific editor support, which is aware of language concepts of data exchange files, needs to be provided. In this paper, we investigate if and in what quality a language grammar can be inferred from a set of existing text files, in order to provide a basis for the desired editing support. For this experiment, we chose a Minimal Adequate Teacher (MAT) method together with specific preprocessing of the existing text files. Thereby, we were able to construct complete grammar rules for most of the language constructs found in a corpus of semi-structured text files. The inferred grammar, however, requires refactoring towards a suitable and maintainable basis for the desired editor support.
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