Prescriptive Semantics For Big-Step Modelling Languages

With the popularity of model-driven methodologies and the abundance of modelling languages, a major question for a modeller is: Which language is suitable for modelling a system under study? To answer this question, one not only needs to know the range of relevant languages for modelling the system under study, but also needs to be able to compare these languages. In this dissertation, I consider these challenges from a semantic point of view for a diverse range of behavioural modelling languages that I refer to as the family of Big-Step Modelling Languages (BSMLs). There is a plethora of BSMLs, including statecharts, its variants, SCR, un-clocked variants of synchronous languages (e.g., Esterel and Argos), and reactive modules. BSMLs are often used to model systems that continuously interact with their environments. In a BSML model, the reaction of the model to an environmental input is a big step, which consists of a sequence of small steps, each of which can be the concurrent execution of a set of transitions. To provide a systematic method to understand and compare the semantics of BSMLs, this dissertation introduces the big-step semantic deconstruction framework that deconstructs the semantic design space of BSMLs into eight high-level, independent semantic aspects together with the enumeration of the common semantic options of each semantic aspect. The dissertation also presents a comparative analysis of the semantic options of each semantic aspect to assist one to choose one semantic option over another. A key idea in the big-step semantic deconstruction is that the high-level semantic aspects in the deconstruction recognize a big step as a whole, rather than only considering its constituent transitions operationally. A novelty of the big-step semantic deconstruction is that it lends itself to a systematic semantic formalization of most of the languages in the deconstruction. The dissertation presents a parametric, formal semantic definition method whose parameters correspond to the semantic aspects of the deconstruction, and thus it produces prescriptive semantics: The manifestation of a semantic option in the semantics of a BSML can be clearly identified. The way transitions are ordered to form a big step in a BSML is a source of semantic complexity: A modeller needs to be aware of the possible orders of the execution of transitions when constructing and analyzing a model. The dissertation introduces three semantic quality attributes that each exempts a modeller from considering an aspect of ordering in big steps. The ranges of BSMLs that support each of these semantic quality attributes are formally specified. These specifications indicate that achieving a semantic quality attribute in a BSML is a cross-cutting concern over the choices of its different semantic options. The semantic quality attributes together with the semantic analysis of individual semantic options can be used in tandem to assist a modeller or a semanticist to compare two BSMLs or to create a new, desired BSML from scratch. Through the big-step semantic deconstruction, I have discovered that some of the semantic aspects of BSMLs can be uniformly described as forms of synchronization. The dissertation presents a general synchronization framework for behavioural modelling languages. This framework is based on a notion of synchronization between transitions of complementary roles. It is parameterized by the number of interactions a transition can take part in, i.e., one vs. many, and the arity of the interaction mechanisms, i.e., exclusive vs. shared, which are considered for the complementary roles to result in 16 synchronization types. To enhance BSMLs with the capability to use the synchronization types, a synchronizer syntax is introduced for BSMLs, resulting in the family of Synchronizing Big-Step Modelling Languages (SBSMLs). Using the expressiveness of SBSMLs, the dissertation describes how underlying the semantics of many modelling constructs, such as multi-source, multi-destination transitions, various composition operators, and workflow patterns, there is a notion of synchronization that can be systematically modelled in SBSMLs

A Notion of Dynamic Interface for Depth-Bounded Object-Oriented Packages

Programmers using software components have to follow protocols that specify when it is legal to call particular methods with particular arguments. For example, one cannot use an iterator over a set once the set has been changed directly or through another iterator. We formalize the notion of dynamic package interfaces (DPI), which generalize state-machine interfaces for single objects, and give an algorithm to statically compute a sound abstraction of a DPI. States of a DPI represent (unbounded) sets of heap configurations and edges represent the effects of method calls on the heap. We introduce a novel heap abstract domain based on depth-bounded systems to deal with potentially unboundedly many objects and the references among them. We have implemented our algorithm and show that it is effective in computing representations of common patterns of package usage, such as relationships between viewer and label, container and iterator, and JDBC statements and cursors

Interface Automata with Complex Actions

AbstractMany formalisms use interleaving to model concurrency. To describe some system behaviours appropriately, we need to limit interleaving. For example, in component-based systems, we wish to limit interleaving to force the inputs to a method to arrive together in order. We introduce interface automata with complex actions (IACA), which add complex actions to de Alfaro and Henzinger's interface automata (IA). A complex action is a sequence of actions that may not be interleaved with actions from other components. The composition and refinement operations are more involved in IACA compared to IA, and we must sacrifice associativity of composition. However, we argue that the advantages of having complex actions make it a useful formalism

Big-Step Semantics

With the popularity of model-driven methodologies, and the abundance of modelling languages, a major question for a requirements engineer is: which language is suitable for modelling a system under study? We address this question from a semantic point-of-view for big-step modelling languages (BSMLs). BSMLs are a popular class of behavioural modelling languages in which a model can respond to an environmental input by executing multiple, possibly concurrent, transitions. We deconstruct the semantics of a large class of BSMLs into high-level, orthogonal semantic aspects and discuss the relative advantages and disadvantages of the semantic options for each of these aspects to allow a requirements engineer to compare and choose the right BSML. We accompany our presentation with many modelling examples that illustrate the differences between a set of relevant semantic options.

DASH: Declarative Modelling with Control State Hierarchy (Preliminary Version)

We present a new language, called DASH, for describing formal behavioural models. DASH combines common modelling constructs to describe abstractly both data and control in an integrated manner. DASH uses the Alloy language for describing data and its operations declaratively, and adds syntax for labelled control state hierarchy common in Statecharts descriptions of transition systems. In addition, DASH accommodates multiple factoring paradigms for modelling (control states, events, and conditions) and includes syntactic sugar (e.g., transition comprehension, transition templates) to write models that are concise and easy to understand. We describe the formal semantics of DASH, which carefully mix the usual semantic understanding of control state hierarchy with the declarative perspective, for creating abstract models early in system development. We implement these semantics in a translator from DASH to Alloy taking advantage of Alloy language features. We demonstrate DASH, our tool, and model checking analysis in the Alloy Analyzer using several case studies. The key novel insight of our work is in combining seamlessly common data and control modelling paradigms in a way that will be intuitive for those used to either paradigm, and enabling automatic analysis of the integrated model

Dash: declarative behavioural modelling in Alloy with control state hierarchy

This is a post-peer-review, pre-copyedit version of an article published in Software and Systems Modeling. The final authenticated version is available online at: https://doi.org/10.1007/s10270-022-01012-1We present Dash, an extension to the Alloy language to model dynamic behaviour using the labelled control state hierarchy of Statecharts. From Statecharts, Dash borrows the concepts to specify hierarchy, concurrency, and communication for describing behaviour in a compositional manner. From Alloy, Dash uses the expressiveness of relational logic and set theory to abstractly and declaratively describe structures, data, and operations. We justify our semantic design decisions for Dash, which carefully mix the usual semantic understanding of control state hierarchy with the declarative perspective. We describe and implement the semantics of a Dash model by translating it to Alloy, taking advantage of Alloy language features. We evaluate our Dash translation and perform model checking analysis, enabled by our translation, in the Alloy Analyzer using several case studies. Dash provides modellers with a language that seamlessly combines the semantics of control-modelling paradigms with Alloy’s existing strengths in modelling data and operations abstractly

BSML-mbeddr: Integrating Semantically Congurable State-Machine Models in a C Programming Environment

In model-driven engineering, developers express their solutions in domain-specific modelling languages (DSLs) that support domain-specific abstractions. Big-Step Modelling Languages (BSML) is a family of extended state-machine DSLs for creating executable models that have a complex execution semantics. In this paper, we present BSML-mbeddr, which imbeds a large subset of BSML within the mbeddr C programming environment, thereby extending mbeddr with language constructs for extended, semantically configurable state-machines. We also report on three case studies that exercise the expressiveness of BSML-mbeddr, assess the integrability of BSML-mbeddr into mbeddr, and demonstrate the need to provide support for state-machine models with different execution semantics.NSERC Discovery Grant, 155243-12 || Ontario Research Fund, RE05-04

ABSTRACT Online Pricing for Web Service Providers

We consider Web service providers, which have a finite capacity, and requests for their services, which arrive sequentially over time, and propose an online algorithm for selecting from such requests and charging for such requests. We show that different variations of this problem, both as online and offline (when we know all requests a priori), are hard problems. We initially start with two naive variations of the problem and show these variations are too hard to be solved. Then, we propose an online algorithm for a variation of the problem where we make some statistical assumptions about the requests that Web service providers receive over time

Engage: A Deployment Management System

Many modern applications are built by combining independently developed packages and services that are distributed over many machines with complex inter-dependencies. The assembly, installation, and management of such applications is hard, and usually performed either manually or by writing customized scripts. We present Engage, a system for configuring, installing, and managing complex application stacks. Engage consists of three components: a domain-specific model to describe component metadata and intercomponent dependencies; a constraint-based algorithm that takes a partial installation specification and computes a full installation plan; and a runtime system that co-ordinates the deployment of the application across multiple machines and manages the deployed system. By explicitly modeling configuration metadata and intercomponent dependencies, Engage enables static checking of application configurations and automated, constraint-driven, generation of installation plans across multiple machines. This reduces the tedious manual process of application configuration, installation, and management. We have implemented Engage and we have used it to successfully host a number of applications. We describe our experiences in using Engage to manage a generic platform that hosts Django applications in the cloud or on premises