Towards the Formal Verification of Model Transformations: An Application to Kermeta

Model-Driven Engineering (MDE) is becoming a popular engineering methodology for developing large-scale software applications, using models and transformations as primary principles. MDE is now being successfully applied to domain-specific languages (DSLs), which target a narrow subject domain like process management, telecommunication, product lines, smartphone applications among others, providing experts high-level and intuitive notations very close to their problem domain. More recently, MDE has been applied to safety-critical applications, where failure may have dramatic consequences, either in terms of economic, ecologic or human losses. These recent application domains call for more robust and more practical approaches for ensuring the correctness of models and model transformations. Testing is the most common technique used in MDE for ensuring the correctness of model transformations, a recurrent, yet unsolved problem in MDE. But testing suffers from the so-called coverage problem, which is unacceptable when safety is at stake. Rather, exhaustive coverage is required in this application domain, which means that transformation designers need to use formal analysis methods and tools to meet this requirement. Unfortunately, two factors seem to limit the use of such methods in an engineer’s daily life. First, a methodological factor, because MDE engineers rarely possess the effective knowledge for deploying formal analysis techniques in their daily life developments. Second, a practical factor, because DSLs do not necessarily have a formal explicit semantics, which is a necessary enabler for exhaustive analysis. In this thesis, we contribute to the problem of formal analysis of model transformations regarding each perspective. On the conceptual side, we propose a methodological framework for engineering verified model transformations based on current best practices. For that purpose, we identify three important dimensions: (i) the transformation being built; (ii) the properties of interest ensuring the transformation’s correctness; and finally, (iii) the verification technique that allows proving these properties with minimal effort. Finding which techniques are better suited for which kind of properties is the concern of the Computer-Aided Verification community. Consequently in this thesis, we focus on studying the relationship between transformations and properties. Our methodological framework introduces two novel notions. A transformation intent gathers all transformations sharing the same purpose, abstracting from the way the transformation is expressed. A property class captures under the same denomination all properties sharing the same form, abstracting away from their underlying property languages. The framework consists of mapping each intent with its characteristic set of property classes, meaning that for proving the correctness of a particular transformation obeying this intent, one has to prove properties of these specific classes. We illustrate the use and utility of our framework through the detailed description of five common intents in MDE, and their application to a case study drawn from the automative software domain, consisting of a chain of more than thirty transformations. On a more practical side, we study the problem of verifying DSLs whose behaviour is expressed with Kermeta. Kermeta is an object-oriented transformation framework aligned with Object Management Group standard specification MOF (Meta-Object Facility). It can be used for defining metamodels and models, as well as their behaviour. Kermeta lacks a formal semantics: we first specify such a semantics, and then choose an appropriate verification domain for handling the analysis one is interested in. Since the semantics is defined at the level of Kermeta’s transformation language itself, our work presents two interesting features: first, any DSL whose behaviour is defined using Kermeta (more precisely, any transformation defined with Kermeta) enjoys a de facto formal underground for free; second, it is easier to define appropriate abstractions for targeting specific analysis for this full-fledged semantics than defining specific semantics for each possible kind of analysis. To illustrate this point, we have selected Maude, a powerful rewriting system based on algebraic specifications equipped with model-checking and theorem-proving capabilities. Maude was chosen because its underlying formalism is close to the mathematical tools we use for specifying the formal semantics, reducing the implementation gap and consequently limiting the possible implementation mistakes. We validate our approach by illustrating behavioural properties of small, yet representative DSLs from the literature

An integration framework for managing rich organisational process knowledge

The problem we have addressed in this dissertation is that of designing a pragmatic framework for integrating the synthesis and management of organisational process knowledge which is based on domain-independent AI planning and plan representations. Our solution has focused on a set of framework components which provide methods, tools and representations to accomplish this task.In the framework we address a lifecycle of this knowledge which begins with a methodological approach to acquiring information about the process domain. We show that this initial domain specification can be translated into a common constraint-based model of activity (based on the work of Tate, 1996c and 1996d) which can then be operationalised for use in an AI planner. This model of activity is ontologically underpinned and may be expressed with a flexible and extensible language based on a sorted first-order logic. The model combines perspectives covering both the space of behaviour as well as the space of decisions. Synthesised or modified processes/plans can be translated to and from the common representation in order to support knowledge sharing, visualisation and mixed-initiative interaction.This work united past and present Edinburgh research on planning and infused it with perspectives from design rationale, requirements engineering, and process knowledge sharing. The implementation has been applied to a portfolio of scenarios which include process examples from business, manufacturing, construction and military operations. An archive of this work is available at: http://www.aiai.ed.ac.uk/~oplan/cpf

Fundamental Approaches to Software Engineering

This open access book constitutes the proceedings of the 24th International Conference on Fundamental Approaches to Software Engineering, FASE 2021, which took place during March 27–April 1, 2021, and was held as part of the Joint Conferences on Theory and Practice of Software, ETAPS 2021. The conference was planned to take place in Luxembourg but changed to an online format due to the COVID-19 pandemic. The 16 full papers presented in this volume were carefully reviewed and selected from 52 submissions. The book also contains 4 Test-Comp contributions