Proceedings of the ACM on Programming Languages, 6(OOPSLA2), 758-785

MINIKANREN is a lightweight embedded language for logic and relational programming. Many of its useful features come from a distinctive search strategy, called interleaving search. However, with interleaving search conventional ways of reasoning about the complexity and performance of logical programs become irrelevant. We identify an important key component—scheduling—which makes the reasoning for MINIKANREN so different, and present a semi-automatic technique to estimate the scheduling impact via symbolic execution for a reasonably wide class of programs.

49th ACM SIGPLAN Symposium on Principles of Programming Languages (POPL 2012)

Scientific and Technical Journal of Information Technologies, Mechanics and Optics

Syrcose'21

TFPIE-2021

Distinguished Paper Award at OOPSLA'21

OOPSLA

Programming and Computer Software Journal

We present a new, fair, conjunction evaluation strategy for relational programming language miniKanren. Unlike the original left-biased conjunction, our approach controls the order of conjunct execution based on the intrinsic properties of relation definitions. We present both the formal study of conjunction fairness and practical evaluation, which demonstrates the essential improvement in terms of both performance and convergence.

SEIM-2021

ICPP-2021

We present a formal study of semantics for the relational programming language MINIKANREN. First, we formulate a denotational semantics which corresponds to the minimal Herbrand model for definite logic programs. Second, we present operational semantics which models interleaving, the distinctive feature of MINIKANREN implementation, and prove its soundness and completeness w.r.t. the denotational semantics. Our development is supported by a COQ specification, from which a reference interpreter can be extracted. We also derive from our main result a certified semantics (and a reference interpreter) for SLD resolution with cut and prove its soundness.

We present a completely declarative approach to synthesizing pattern matching construct implementations based on application of relational programming, a specific form of constraint logic programming. Our approach is based on relational representations of both the high-level semantics of pattern matching and the semantics of an intermediate-level implementation language. This choice makes our approach, in principle, very scalable as we only need to modify the high-level semantics in order to synthesize the implementation of a pattern matching new feature. Our evaluation on a set of small samples, partially taken from existing literature shows that our framework is capable of synthesizing optimal implementations quickly. Our in-depth stress evaluation on a number of artificial benchmarks, however, has shown the need for future improvements.

Context-free path queries (CFPQ) extend the regular path queries (RPQ) by allowing context-free grammars to be used as constraints for paths. Algorithms for CFPQ are actively developed, but J. Kuijpers et al. have recently concluded, that existing algorithms are not performant enough to be used in real-world applications. Thus the development of new algorithms for CFPQ is justified. In this paper, we provide a new CFPQ algorithm which is based on such linear algebra operations as Kronecker product and transitive closure and handles grammars presented as recursive state machines. Thus, the proposed algorithm can be implemented by using high-performance libraries and modern parallel hardware. Moreover, it avoids grammar growth which provides the possibility for queries optimization.

ADBIS 2020. Advances in Databases and Information Systems. Lecture Notes in Computer Science.

Regular expressions are used in SPARQL property paths to query RDF graphs. However, regular expressions can only define the most limited class of languages, called regular languages. Context-free languages are a wider class containing all regular languages. There are no context-free expressions to define them, so it is necessary to write grammars. We propose an extension of regular expressions, called recursive expressions, to support the definition of a subset of context-free languages. The goal of our work is therefore to provide simple operators allowing the definition of languages as close as possible to context-free languages.

ADBIS, TPDL and EDA 2020 Common Workshops and Doctoral Consortium

The European Conference on Object-Oriented Programming (ECOOP)

Context-free path querying (CFPQ) is widely used for graph-structured data analysis in different areas. It is crucial to develop highly efficient algorithms for CFPQ since the size of the input data is typically large. We show how to reduce CFPQ evaluation to solving systems of matrix equations over R --- a problem for which there exist high-performance solutions. Also, we demonstrate the applicability of our approach to real-world data analysis.

Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data

This paper aims to present Valiant’s algorithm modification, which main advantage is the possibility to divide the parsing table into successively computed layers of disjoint submatrices where each submatrix of the layer can be processed independently. Moreover, our approach is easily adapted for the string-matching problem.

Proceedings of the Institute for System Programming

A recent study showed that the applicability of context-free path querying (CFPQ) algorithms with relational query semantics integrated with graph databases is limited because of low performance and high memory consumption of existing solutions. In this work, we implement a matrix-based CFPQ algorithm by using appropriate high-performance libraries for linear algebra and integrate it with RedisGraph graph database. Also, we introduce a new CFPQ algorithm with single-path query semantics that allows us to extract one found path for each pair of nodes. Finally, we provide the evaluation of our algorithms for both semantics which shows that matrix-based CFPQ implementation for Redis-Graph database is performant enough for real-world data analysis.

GRADES-NDA'20: Proceedings of the 3rd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

41st ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2020)

41st ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI 2020)

While GPU utilization allows one to speed up computations to the orders of magnitude, memory management remains the bottleneck making it often a challenge to achieve the desired performance. Hence, different memory optimizations are leveraged to make memory being used more effectively. We propose an approach automating memory management utilizing partial evaluation, a program transformation technique that enables data accesses to be pre-computed, optimized, and embedded into the code, saving memory transactions. An empirical evaluation of our approach shows that the transformed program could be up to 8 times as efficient as the original one in the case of CUDA C naïve string pattern matching algorithm implementation.

PPoPP '20: Proceedings of the 25th ACM SIGPLAN Symposium on Principles and Practice of Parallel Programming

Proceedings of ISP RAS

Path querying with conjunctive grammars is known to be undecidable. There is an algorithm for path querying with linear conjunctive grammars which provides an over-approximation of the result, but there is no algorithm for arbitrary conjunctive grammars. We propose the first algorithm for path querying with arbitrary conjunctive grammars. The proposed algorithm is matrix-based and allows us to efficiently apply GPGPU computing techniques and other optimizations for matrix operations.

Programming and Computer Software

BMC Bioinformatics

Proceedings of 19th International Conference on Formal Methods in Computer-Aided Design, FMCAD 2019

33rd European Conference on Object-Oriented Programming (ECOOP 2019)

Recently proposed matrix multiplication based algorithm for context-free path querying (CFPQ) offloads the most performance-critical parts onto boolean matrices multiplication. Thus, it is possible to achieve high performance of CFPQ by means of modern parallel hardware and software. In this paper, we provide results of empirical performance comparison of different implementations of this algorithm on both real-world data and synthetic data for the worst cases.

Proceedings of the 2nd Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

The Bar-Hillel theorem states that context-free languages are closed under intersection with a regular set. This theorem has a constructive proof and thus provides a formal justification of correctness of the algorithms for applications mentioned above. Mechanization of the Bar-Hillel theorem, therefore, is both a fundamental result of formal language theory and a basis for the certified implementation of the algorithms for applications. In this work, we present the mechanized proof of the Bar-Hillel theorem in Coq.

Logic, Language, Information, and Computation

We propose a way to combine formal grammars and artificial neural networks for biological sequences processing. Formal grammars encode the secondary structure of the sequence and neural networks deal with mutations and noise. In contrast to the classical way, when probabilistic grammars are used for secondary structure modeling, we propose to use arbitrary (not probabilistic) grammars which simplifies grammar creation. Instead of modeling the structure of the whole sequence, we create a grammar which only describes features of the secondary structure. Then we use matrix-based parsing to extract features: the fact that some substring can be derived from some nonterminal is a feature. After that, we use a dense neural network to process features.

Proceedings of the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOINFORMATICS

One of the problems in graph data analysis is querying for specific paths. Such queries are usually performed by means of a formal grammar that describes the allowed edge-labeling of the paths. Path query is said to be calculated using relational query semantics if it is evaluated to triple (A,v1,v2), such that there is a path from v1 to v2 such that the labels on the edges of this path form a string derivable from the nonterminal A. We focus on the Boolean languages that use Boolean grammars to describe the labeling of paths. Although path querying using relational query semantics and Boolean grammars is known to be undecidable, in this work we propose a path querying algorithm on acyclic graphs which uses relational query semantics and Boolean grammars and approximates the exact solution. To achieve better performance in compare with the naive algorithm, considered classes of graphs were limited to acyclic graphs.

Proceedings of the Institute for System Programming

Proceedings of the 2019 miniKanren and Relational Programming Workshop

SEIM-19

Preliminary Proceedings of the 13 rd Spring/Summer Young Researchers’ Colloquium on Software Engineering (SYRCoSE 2019), May 29-31, 2019 – Saratov, Russian Federation

Proceedings of the 2019 miniKanren and Relational Programming Workshop

Proceedings of the 2019 miniKanren and Relational Programming Workshop

Programming and Computer Software

Extended abstract at TyDe 2018 (at ICFP).

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

NTV SPbSTU

GRADES-NDA '18 Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA)

18th International Symposium on Trends in Functional Programming

Proceedings of the 20th International Symposium on Principles and Practice of Declarative Programming

Proceedings ML/OCAML 2016

40th ACM/IEEE International Conference on Software Engineering, ICSE 2018

NTV SPbSTU

There are several solutions for CFPQ, but how to provide structural representation of query result which is practical for answer processing and debugging is still an open problem. In this paper we propose a graph parsing technique which allows one to build such representation with respect to given grammar in polynomial time and space for arbitrary context-free grammar and graph. Proposed algorithm is based on generalized LL parsing algorithm, while previous solutions are based mostly on CYK or Earley algorithms, which reduces time complexity in some cases.

Proceedings of the 13th Central & Eastern European Software Engineering Conference in Russia (CEE-SECR '17)

Proceedings of ISP RAS

arXiv

The European Conference on Object-Oriented Programming (ECOOP)

Proceedings of the 2017 ACM SIGPLAN Workshop on Partial Evaluation and Program Manipulation

St. Petersburg State Polytechnical University Journal. Computer Science. Telecommunications and Control Systems

Izvestia vuzov. North Caucasus Region. Technical Sciences, 2017, no. 4, P. 5-12.

Proceedings of the Institute for System Programming

arXiv

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

Systems and Means of Informatics

META 2016 Fifth International Valentin Turchin Workshop on Metacomputation

SEIM-16

NTV SPbSTU 4 (224)

Systems and Means of Informatics

Science of Computer Programming

Proceedings of the 11th Central & Eastern European Software Engineering Conference in Russia

Proceedings of 9th International Andrei Ershov Memorial Conference on Perspectives of System Informatics

Proceedings of the 10th Central and Eastern European Software Engineering Conference in Russia 2014

Proceedings of the 10th Central and Eastern European Software Engineering Conference in Russia

Proceedings of the 9th Central & Eastern European Software Engineering Conference in Russia

Workshop on ML

Proceedings of the 2010 East-West Design & Test Symposium

Proceedings of 6th International Andrei Ershov Memorial Conference on Perspectives of System Informatics

Workshop on Multiparadigm Programming with Object-Oriented Languages

System Informatics

System Programming

System Programming

Proceedings of the European Conference on Software Maintenance and Reengineering, CSMR 995802, pp. 177-185

Proceedings of 4th International Andrei Ershov Memorial Conference on Perspectives of System Informatics

Automated Reengeneering of Programs, Saint Petersburg