Inferring Attributed Grammars from Parser Implementations
This program is tentative and subject to change.
Software systems that process structured inputs often lack complete and up-to-date specifications, which specify the input syntax and the semantics of input processing. While grammar mining techniques have focused on recovering syntactic structures, the semantics of input processing remain largely unexplored. In this paper, we introduce a novel approach for inferring attributed grammars from parser implementations. Given an input grammar, our technique dynamically analyzes the implementation of recursive descent parsers to reconstruct the semantic aspects of input handling, resulting in specifications in the form of attributed grammars. By observing program executions and mapping the program’s runtime behavior to the grammar, we systematically extract and embed semantic actions into the grammar rules. This enables comprehensive specification recovery. We demonstrate the feasibility of our approach using an initial set of programs, showing that it can accurately reproduce program behavior through the generated attributed grammars.
This program is tentative and subject to change.
Fri 12 SepDisplayed time zone: Auckland, Wellington change
10:30 - 12:00 | Session 13 - Reuse 1NIER Track / Research Papers Track / Industry Track / Registered Reports at Case Room 3 260-055 Chair(s): Banani Roy University of Saskatchewan | ||
10:30 15m | From Release to Adoption: Challenges in Reusing Pre-trained AI Models for Downstream Developers Research Papers Track Peerachai Banyongrakkul The University of Melbourne, Mansooreh Zahedi The Univeristy of Melbourne, Patanamon Thongtanunam University of Melbourne, Christoph Treude Singapore Management University, Haoyu Gao The University of Melbourne Pre-print | ||
10:45 15m | Are Classical Clone Detectors Good Enough For the AI Era? Research Papers Track Ajmain Inqiad Alam University of Saskatchewan, Palash Ranjan Roy University of Saskatchewan, Farouq Al-Omari Thompson Rivers University, Chanchal K. Roy University of Saskatchewan, Banani Roy University of Saskatchewan, Kevin Schneider University of Saskatchewan | ||
11:00 10m | Can LLMs Write CI? A Study on Automatic Generation of GitHub Actions Configurations NIER Track Taher A. Ghaleb Trent University, Dulina Rathnayake Department of Computer Science, Trent University, Peterborough, Canada Pre-print | ||
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11:45 10m | Inferring Attributed Grammars from Parser Implementations NIER Track Andreas Pointner University of Applied Sciences Upper Austria, Hagenberg, Austria, Josef Pichler University of Applied Sciences Upper Austria, Herbert Prähofer Johannes Kepler University Linz Pre-print | ||