Екатерина Вербицкая


В 2015 году получила диплом на кафедре системного программирования математико-механического факультета СПбГУ.

Профессиональная деятельность

I am currently working on program transformations for the relational programming language miniKanren; developing a generic programming framework for dealing with terms and applying parsing for the Context-Free Path Querying problem.

Научное руководство

Рустам Азимов, «Диагностика синтаксических ошибок в динамически формируемом коде». Бакалаврская работа защищена на кафедре системного программирования СПбГУ в 2016 году.



  • Proceedings of the 2019 miniKanren and Relational Programming Workshop, 2019
  • Ekaterina Verbitskaia, Ilya Kirillov, Ilya Nozkin, Semyon Grigorev

    Transparent integration of a domain-specific language for specification of context-free path queries (CFPQs) into a general-purpose programming language as well as static checking of errors in queries may greatly simplify the development of applications using CFPQs. LINQ and ORM can be used for the integration, but they have issues with flexibility: query decomposition and reusing of subqueries are a challenge. Adaptation of parser combinators technique for paths querying may solve these problems. Conventional parser combinators process linear input, and only the Trails library is known to apply this technique for path querying. We demonstrate that it is possible to create general parser combinators for CFPQ which support arbitrary context-free grammars and arbitrary input graphs. We implement a library of such parser combinators and show that it is applicable for realistic tasks.

    Proceedings of the 9th ACM SIGPLAN International Symposium on Scala, Сентябрь 2018
  • Ekaterina Verbitskaia , Semyon Grigorev, Dmitry Avdyukhin

    We present a technique for syntax analysis of a regular set of input strings. This problem is relevant for the analysis of string-embedded languages when a host program generates clauses of embedded language at run time. Our technique is based on a generalization of RNGLR algorithm, which, inherently, allows us to construct a finite representation of parse forest for regularly approximated set of input strings. This representation can be further utilized for semantic analysis and transformations in the context of reengineering, code maintenance, program understanding etc. The approach in question implements relaxed parsing: non-recognized strings in approximation set are ignored with no error detection.

    Perspectives of System Informatics, Июнь 2016
  • Ekaterina Verbitskaia, Semyon Grigorev and Dmitry Avdyukhin
    Proceedings of 10th International Andrei Ershov Memorial Conference on Perspectives of System Informatics, 2015
  • Semen Grigorev, Ekaterina Verbitskaia, Andrei Ivanov, Marina Polubelova, and Ekaterina Mavchun
    Proceedings of the 10th Central and Eastern European Software Engineering Conference in Russia 2014, 2014