DIKU forskere modtager Best Paper Award ved PEPM 2017 – Københavns Universitet

Videresend til en ven Resize Print Bookmark and Share

Datalogisk Institut, DIKU > Nyheder > DIKU-nyheder 2017 > DIKU forskere modtager...

18. januar 2017

DIKU forskere modtager Best Paper Award ved PEPM 2017

Best Paper Award

Ved Workshop on Partial Evaluation and Program Manipulation (PEPM) som blev afholdt den 16.-17. januar 2017, blev Ulrik Terp Rasmussen, ph.d.-studerende på DIKU, med sin vejleder professor Fritz Henglein fra forskningsprojektet Kleene Meets Church, tildelt en Best Paper Award for artiklen 'PEG Parsing in Less Space Using Progressive Tabling and Dynamic Analysis'.

PEPM er det førende forum til diskussion af semantikbaseret programmanipulation. Det har kørt i mere end 25 år og er udsprunget af pionerarbejdet med partiel evaluering, som i stor grad fandt sted på DIKU. PEPM serien har til formål at samle forskere og udøvere, der arbejder inden for områderne program manipulation, partiel evaluering og programudvikling og fokuserer på teknikker, teori, værktøjer og anvendelser inden for analyse og manipulation af programmer.

Abstract


PEG Parsing in Less Space Using Progressive Tabling and Dynamic Analysis
Tabular top-down parsing and its lazy variant, Packrat, are linear-time execution models for the TDPL family of recursive descent parsers with limited backtracking. Exponential work due to backtracking is avoided by tabulating the result of each (nonterminal, offset)-pair at the expense of always using space proportional to the product of the input length and grammar size. Current methods for limiting the space usage relies either on manual annotations or on static analyses which are sensitive to the syntactic structure of the grammar. 

We present progressive tabular parsing (PTP), a new execution model which progressively computes parse tables for longer prefixes of the input and simultaneously generates a leftmost expansion of the parts of the parse tree that can be resolved. Table columns can be discarded on-the-fly as the expansion progresses through the input string, providing best-case constant and worst-case linear memory use. Furthermore, semantic actions are scheduled before the parser has seen the end of the input. The scheduling is conservative in the sense that no action has to be ``undone’’ in the case of backtracking.

The time complexity is O(dmn) where m is the size of the parser specification, n is the size of the input string, and d is either a configured constant or the maximum parser stack depth.

For common data exchange formats such as JSON, we demonstrate practically constant space usage.