Zoltán Ujhelyi

EMF-IncQuery

As model management platforms are gaining industrial attention, the importance of automated model querying techniques is also increasing. Several important engineering tasks supported by model-based tools - such as well-formedness constraint validation or model transformations - rely on efficiently evaluating model queries. If the models change rapidly or frequently, it is beneficial to provide live and incrementally evaluated queries that automatically propagate model changes to keep query results consistent.The current paper reports on the of EMF-IncQuery framework focusing on new features of its integrated development environment (such as query validation and visualization) and its support for integrating queries to existing applications (e.g. by auto-generated data bindings) built on top of the industry standard Eclipse Modeling Framework (EMF). Our approach is illustrated on a case study integrating well-formedness constraints to the Papyrus UML tool by live model queries of EMF-IncQuery with negligible additional manual programming effort.

A graph query language for EMF models

While model queries are important components in modeldriven tool chains, they are still frequently implemented using traditional programming languages, despite the availability of model query languages due to performance and expressiveness issues. In the current paper, we propose EMF-INCQUERY as a novel, graph-based query language for EMF models by adapting the query language of the VIATRA2 model transformation framework to inherit its concise, declarative nature, but to properly tailor the new query language to the modeling specificities of EMF. The EMF-INCQUERY language includes (i) structural restrictions for queries imposed by EMF models, (ii) syntactic sugar and notational shorthand in queries, (iii) true semantic extensions which introduce new query features, and (iv) a constraint-based static type checking method to detect violations of EMF-specific type inference rules.

Viatra 3: A Reactive Model Transformation Platform

Model-driven tools frequently rely on advanced technologies to support model queries, view maintenance, design rule validation, model transformations or design space exploration. Some of these features are initiated explicitly by domain engineers batch execution while others are executed automatically when certain trigger events are detected live execution. Unfortunately, their integration into a complex industrial modeling environment is difficult due to hidden interference and unspecified interaction between different features. In this paper, we present a reactive, event-driven model transformation platform over EMF models, which captures tool features as model queries and transformations, and provides a systematic, well-founded integration between a variety of such tool features. Viatra 3 offers a family of internal DSLs i.e. dedicated libraries to specify advanced tool features built on top of existing languages like EMF-IncQuery and Xtend. Its main innovation is a source incremental execution scheme built on the reactive programming paradigm ssupported by an event-driven virtual machine.

Query-driven incremental synchronization of view models

Views are key concepts of domain-specific modeling in order to provide specific focus of the designers by abstracting from unnecessary details of the underlying abstract model. Usually, these views are represented as models themselves (view models), computed from the source model. However, the efficient maintenance of views when the source model changes is challenging, as recalculation from scratch has to be avoided to achieve scalability. In the paper, we propose an approach to define view models in a highly automated way, based on declarative model queries. The views are automatically populated in accordance with the lifecycle of regular model elements - however, their existence is entirely bound to the underlying abstract model. This means that view models are automatically and incrementally maintained. Our contribution can also be interpreted as extending the concepts of derived features to derived objects, specified and maintained by incremental queries.

Performance comparison of query-based techniques for anti-pattern detection

ContextProgram queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Abstract Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries. ObjectiveOur paper investigates the costs and benefits of using the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by four different general-purpose model query techniques based on native Java code, OCL evaluation and (incremental) graph pattern matching. MethodWe provide in-depth comparison of these techniques on the source code of 28 Java projects using anti-pattern queries taken from refactoring operations in different usage profiles. ResultsOur results show that general purpose model queries can outperform hand-coded queries by 2-3 orders of magnitude, with the trade-off of an increased in memory consumption and model load time of up to an order of magnitude. ConclusionThe measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.

Integrating efficient model queries in state-of-the-art EMF tools

Model-driven development tools built on industry standard platforms, such as the Eclipse Modeling Framework (EMF), heavily use model queries in various use cases, such as model transformation, well-formedness constraint validation and domain-specific model execution. As these queries are executed rather frequently in interactive modeling applications, they have a significant impact on the runtime performance of the tool, and also on the end user experience. However, due to their complexity, they can also be time consuming to implement and optimize on a case-by-case basis. The aim of the EMF-IncQuery framework is to address these shortcomings by using declarative queries over EMF models and executing them effectively using a caching mechanism. In the current paper, we present the new and significantly extended version of the EMF-IncQuery Framework, with new features and runtime extensions that speed up the development and testing of new queries by both IDE and API improvements. We demonstrate how our high performance queries can be easily integrated with other EMF tools using an entirely new case study in which EMF-IncQuery is deeply integrated into the EMF modeling infrastructure to facilitate the incremental evaluation of derived EAttributes and EReferences.

Towards dynamic backward slicing of model transformations

Model transformations are frequently used means for automating software development in various domains to improve quality and reduce production costs. Debugging of model transformations often necessitates identifying parts of the transformation program and the transformed models that have causal dependence on a selected statement. In traditional programming environments, program slicing techniques are widely used to calculate control and data dependencies between the statements of the program. Here we introduce program slicing for model transformations where the main challenge is to simultaneously assess data and control dependencies over the transformation program and the underlying models of the transformation. In this paper, we present a dynamic backward slicing approach for both model transformation programs and their transformed models based on automatically generated execution trace models of transformations.

Local Search-Based Pattern Matching Features in EMF-IncQuery

Graph patterns provide a declarative formalism to describe model queries used for several important engineering tasks, such as well-formedness constraint validation or model transformations. As different pattern matching approaches, such as local search or incremental evaluation, have different performance characteristics (smaller memory footprint vs. smaller runtime), a wider range of practical problems can be addressed. The current paper reports on a novel feature of the EMF-IncQuery framework supporting local search-based pattern matching strategy to complement the existing incremental pattern matching capabilities. The reuse of the existing pattern language and query development environment of EMF-IncQuery enables to select the most appropriate strategy separately for each pattern without any modifications to the definitions of existing patterns. Furthermore, a graphical debugger component is introduced that visualizes the execution of the search process, helping to understand how complex patterns behave. This tool paper presents the new pattern matching feature from an end users viewpoint while the scientific details of the pattern matching strategy itself are omitted. The approach is illustrated on a case study of automated identification of anti-patterns over program models created from Java source code.

Anti-pattern detection with model queries: A comparison of approaches

Program queries play an important role in several software evolution tasks like program comprehension, impact analysis, or the automated identification of anti-patterns for complex refactoring operations. A central artifact of these tasks is the reverse engineered program model built up from the source code (usually an Semantic Graph, ASG), which is traditionally post-processed by dedicated, hand-coded queries. Our paper investigates the use of the popular industrial Eclipse Modeling Framework (EMF) as an underlying representation of program models processed by three general-purpose model query techniques based on native Java code, local-search and incremental evaluation. We provide in-depth comparison of these techniques on the source code of 17 Java projects using queries taken from refactoring operations in different usage profiles. Our results show that general purpose model queries outperform hand-coded queries by 2-3 orders of magnitude, while there is a 5-10 times increase in memory consumption and model load time. In addition, measurement results of usage profiles can be used as guidelines for selecting the appropriate query technologies in concrete scenarios.

Implementing efficient model validation in EMF tools

Model-driven development tools built on industry standard platforms, such as the Eclipse Modeling Framework (EMF), heavily use model queries in various use cases, such as model transformation, well-formedness constraint validation and domain-specific model execution. As these queries are executed rather frequently in interactive modeling applications, they have a significant impact on the runtime performance of the tool, and also on the end user experience. However, due to their complexity, they can be time consuming to implement and optimize on a case-by-case basis. To address these shortcomings, we developed the EMF-INCQUERY framework for defining declarative queries over EMF models and executing them effectively using a caching mechanism. In the current paper, we demonstrate how our framework can be easily integrated with other EMF tools. We describe a case study in which EMF-INCQUERY is integrated into the open source Papyrus UML environment to provide on-the-fly validation of well-formedness criteria in UML models.