Lowcomote — Heterogeneous Low-Code Model Query Optimisation

Contact:

ESR 12: Heterogeneous Low-Code Model Query Optimisation

Qurat ul ain Ali
University of York (United-Kingdom)

Objectives

As software systems become more complex, underlying models in LCEPs grow proportionally in both size and complexity. Such models can be persisted in a variety of proprietary or standard formats (such as XMI), and in different types of back-ends (e.g. file systems, relational databases, document databases). High-level, concise and tailored model query languages such as OCL and EOL can be used to shield query developers from the intricacies of the underlying model formats/back-ends but this typically has a significant impact on performance. Recently, we have shown how sophisticated runtime query optimisation can be used to drastically improve the execution time of high-level OCL-style queries executed over models stored in relational and non-relational databases. The objectives of this project are to: (1) investigate the applicability of runtime query optimisation techniques to a wide range of model persistence formats and back-ends, (2) identify reusable optimisation primitives and patterns across different formats and back-ends, and (3) evaluate the obtained benefits in terms of performance and memory footprint.

Expected Results

This project will produce novel techniques and algorithms for optimisation of queries operating on low-code systemmodels captured using differentmodelling languages andmodel representation formats. It will also produce an open-source prototype that will implement the identified algorithms and techniques on top of existing model query languages. While the precise performance benefits will depend on the nature of individual queries and the underlying model representation formats, based on our preliminary results in we expect an increase of at least one order of magnitude in query execution time for certain classes of queries (e.g. filtering all instances of a type).

Publications

Selective Traceability for Rule-Based Model-to-Model Transformations. Qurat ul ain Ali, Dimitris Kolovos, Konstantinos Barmpis, Nov. 2022. 15th ACM SIGPLAN International Conference on Software Language ENgineering (SLE'2022)
Heterogeneous Model Query Optimisation. Qurat ul ain Ali, Dec. 2021. Doctoral Symposium at MODELS 2021.
Identification and Optimisation of Type-Level Model Queries. Qurat ul ain Ali, Dimitris Kolovos, Konstantinos Barmpis, Dec. 2021. SAM2021 - System Analysis and Modelling Agility and DevOps, Co-located with MODELS 2021.
Towards Scalable Validation of Low-Code System Models. Mapping EVL to VIATRA Patterns. Qurat ul ain Ali, Benedek Horváth, Dimitris Kolovos, Konstantinos Barmpis, Ákos Horváth, Oct. 2021. 2nd Low-code workshop at MODELS 2021
Efficiently Querying Large-Scale Heterogeneous Models. Qurat ul ain Ali, Dimitris Kolovos, Konstantinos Barmpis, Oct. 2020. ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems, (Virtual Conference) (MODELS 2020)