This thesis investigates the building of a textual tracing language that operates at the model level to allow trace specification of textually modeled UML constructs. Current tracing approaches focus on manually injecting tracepoints into targeted systems at the source code level. Such approaches are useful in code-centric development styles where the majority of the code is handwritten. However, in the case of Model Driven Development (MDD), where models are utilized to generate some or all of the code, current tracing technology results in low level trace specification and generation of execution traces that are not aware of or linked to the originating model-level constructs. Dynamic analysis hence becomes harder for a modeler adopting an MDD approach. This field, which we call model-oriented tracing, is currently immature, with little pre-existing research. In this thesis, we present a textual model-level tracing language, implemented as part of Umple, that overcomes some of the limitations of existing tracing methods. The language facilitates model-level tracing, in a fashion very similar to code tracing. The language, which we call MOTL (Model-Oriented Tracing Language) allows tracing of UML associations, attributes and state machines. Constraints can be imposed to limit the scope of tracing. As a result of this work, modelers will gain the ability to specify traces of UML constructs at the model level without the need to modify the generated code, and then generate execution traces when the generated system is run. The resulting trace links back to the model constructs. Modelers can choose from among several tracing technologies including basic file or console output, Java logging framework, Log4J and LTTng. This thesis defines the language syntactically and semantically. Model-Driven Development (MDD) and Test-Driven Development (TDD) were followed to implement the language architecture to ensure high quality code generation. MOTL was used in the development in two of Umple subprojects. An empirical evaluation was conducted to evaluate the language’s usability.

In this thesis we present a language and technique to facilitate model-based testing. The core of our approach is an xUnit-like language that allows tests to refer to model entities such as associations. This language can be used by developers to describe tests based on an existing UML model. The tests might even be written before creating a UML model, and be based on requirements. The testing language, including its parser and generators, is written entirely in Umple, an open-source textual modeling tool with semantics closely based on UML, and which generates Java, PHP and several other target languages. Tests in our language can be embedded in Umple or in standalone files. The test language compiler converts our abstract testing language into JUnit, PHPUnit and other domain-language testing environments. In addition to allowing developers to write tests manually, we have created generators that create abstract tests for any Umple model. These generators can be used to verify the Umple compiler and to give Umple users extra confidence in their models. User-defined tests can be standalone or embedded in methods; they can be generic, referring to metamodel elements. Tests can also be located in traits or mixsets to allow testing of separate concerns or product lines. To test our language and the tests written in it, we have created an extensive test suite. We have also implemented mutation testing, that enables varying of features of the models to ensure that runs of the pre-mutation tests then fail.

This thesis investigates a novel approach to reverse engineering, in which modeling information such as UML associations, state machines and attributes is incrementally added to code written in Java or C++, while maintaining the system in a textual format. Umple is a textual representation that blends modeling in UML with programming language code. The approach, called umplification, produces a program with behavior identical to the original one, but written in Umple and enhanced with model-level abstractions. As the resulting program is Umple code, our approach eliminates the distinction between code and model. We implemented automated umplification in a tool called the Umplificator. The tool is rule-driven: code, including Umple code, is parsed and processed into an internal representation, which is then operated on by rules; transformed textual code and model, in Umple, is then generated. The rules used to transform code to model have been iteratively refined by using the tool on a variety of open-source software systems. The thesis consists of three main parts. The first part (Chapters 1 and 2) present the research questions and research methodology, as well as introducing Umple and the background necessary to understand the rest of the thesis. The umplification method is presented at increasing levels of detail through Chapters 3 and 4. Chapters 5 and 6 present the tool and evaluation of our approach, respectively. An analysis of related work, and comparison to our own, appears in Chapter 7. Finally, conclusions and future work directions are presented in Chapter 8.

Traits are primitive units of code reuse that serve as building blocks of classes. In this research, we enhance reuse by extending the capabilities of traits; in particular, we add modeling abstractions to them. Traits have a variety of benefits, including facilitating reuse and separation of concerns. They have appeared in several programming languages, particularly derivatives of Smalltalk. However, there is still no support for traits that contain modeling abstractions, and no straightforward support for them in general-purpose programming languages. The latter is due to structural concerns that exist for them at runtime, especially traits that contain modeling abstractions. Model-driven technologies are making inroads into the development community, albeit slowly. Modeling abstractions such as state machines and associations provide new opportunities for reuse, and can be combined with inheritance for even greater reusability. However, issues with inheritance apply also when these new abstractions are inheritable units. This suggests that traits and models ought to be able to be synergistically combined. We perform a comprehensive analysis of using modeling elements in traits. We implement such traits in Umple, which is a model-oriented programming language that permits embedding of programming concepts into models. The contributions of the thesis are: a) Adding new elements including state machines and associations into traits, hence bringing more reusability, modularity, and applications to traits; b) Developing an algorithm that allows reusing, extending, and composing state machines through traits; c) Extending traits with required interfaces so dependencies at the semantic level become part of their usage, rather than simple syntactic capture; d) Adding template parameters with associations in traits, offering new applications for traits in which it is possible to define design patterns and to have a library of most-used functionality; e) The implementation of all the above concepts, including generating code in multiple general-purpose programming languages through automatic model transformation.

This thesis presents our method to integrate formal methods with model-driven engineering. Although a large amount of literature exists with the goal of facilitating the adoption of formal methods for educational and industrial practice, yet the adoption of formal methods in academia and industry is poor. The goal of this research is to improve the adoption of formal methods by automating the generation of formal methods code while maintaining scalability and bridging the gaps between formal analysis and actual implementation of the complete system. Our approach is based on generating formal representations of software abstractions expressed in a textual language, called Umple, which is derived from UML. Software abstractions of interest include class models and state machines. For state machines, we address concerns such as composite and concurrent states separately. The resulting systems are analyzable by back-end analysis engines such as Alloy and nuXmv or NuSMV for model checking. To ensure correctness of our approach, we have adopted simulation, empirical studies and rigorous test-driven development (TDD) methodologies. To guarantee correctness of state machine systems under analysis (SSUAs), we present methods to automatically generate specifications to analyze domain-independent properties such as non-determinism and reachability analysis. We apply these methods in various case studies; certify their conformance with sets of requirements and uncover certain flaws. Our contributions include a) The overall approach, involving having the developer write the system in Umple and generating both the formal system for analysis and the final code from the same model; b) a novel approach to encode SSUAs even in the presence of and-cross transitions; c) a fully automated approach to certify an SSUA to be free from nondeterminism even in the presence of unbounded domains and multiple and-cross transitions within the same enclosing orthogonal state; d) an empirical study of the impact of abstraction on some performance parameters; and e) a translator from Umple to Alloy and SMV.

For a long time, the development of component-based systems has been a crucial part of real-time software development required for embedded and automotive domains. However, most of the existing tools used in these fields are not only proprietary, but also expensive and not research-friendly. Open-source tools in this domain are so far quite limited in terms of the features supported, especially, code generation. In this thesis, we demonstrate how we can improve the development of real-time and concurrent systems by the introduction of component-based modelling into Umple, an open-source modelling tool. Our work enables component-based modelling to be performed both textually and visually, as is the case with other Umple features. We introduce a number of major features into Umple. First, we introduce support for real-time C++ code generation. This includes supporting all Umple features, such as class diagrams, associations, state machines, and attributes. In order to achieve this, we also introduce Umple Template Language (Umple-TL), which helps Umple developers to use Umple itself to emit text using easy-to-use constructs, such that the text emitted can be in different target languages such Java and C++. Umple-TL provides additional capabilities relying on Umple being a model-oriented and object-oriented language. Umple-TL has become the technology for all code generation in Umple, not just our real-time C++ generators. Umple-TL also plays a vital role easing writing component descriptions Second, we support concurrency, which is crucial for the underlying architecture of composite structure. We have to avoid relying on any third-party libraries in order to make sure that the code generated will be deployable on embedded devices, which are limited and do not provide a lot of options. The concurrency pattern we follow extends the active object pattern aiming to enhance communication among active objects. Concurrency development in general, even if a programming language used is not real-time, is not easy. Hence, we simplify active object concepts, such as future, promise, and delay, using new Umple keywords. We also add composite structure support to Umple, we believe that our syntax and language constructs are comprehensive, and do not require a wide knowledge of modelling and UML concepts. Additionally, we introduce a novel protocol-free approach that dynamically extracts communication protocols from ports, bindings, and active objects as a way to simplify development, and to lead to concise and optimized code generation. We demonstrate the effectiveness of our work using cases studies, in which we implement Umple models using our new composite structure and concurrency constructs. We show that the amount of code required to specify complex concepts is reduced, and the generated systems are effective.

In this thesis, we present mixsets, an approach to combine annotative and compositional fragments for specifying code variants to form software product lines (SPLs). There are three key contributions of our research: introducing mixsets to represent software variability, extending mixsets to construct feature models, and improving software composition to achieve fine-grained variability. The concept of mixsets is introduced in Umple as a conditional unit and a first-class entity to allow smoothly transitioning software to compositional SPLs. A mixset is a named set of mixins; each mixin belonging to the mixset is called a fragment. A mixset fragment can be a top-level entity that contains nested entities or can be embedded as a conditional fragment in other entities such as methods. Mixset content normally includes code blocks or statements of any type, and may include require statements, which describe explicit dependencies among mixsets. Mixsets can be used to specify product lines using code composition, code annotation or both. A strength of mixsets lies on the straightforward mechanism to transform annotated segments into compositional segments when used in a combined approach. Therefore, preplanning effort and time to transform annotative SPLs to compositional SPLs can be reduced. Mixsets can provide a backbone structure to realize product line features in a feature-based SPL. Hence, a feature model can be formed using a subset of specific dependent mixsets. Feature interactions within an SPL can be identified and separated in specific modules by mixset nesting. Furthermore, product configuration, feature modeling analysis and generation of feature diagrams can be accomplished based on mixsets. The thesis also demonstrates a method to enable the granularity of compositional approaches to be expressed at the statement level. This is achieved by allowing aspects to inject code into labelled places, or points of variation, within method code. Such injected code has a full access to the context in which its placed, such as access to local variables. Mixsets are implemented in Umple, a model-driven development (MDD) technology that allows combining abstract models, such as associations and state machines, with pure code, and generating code in multiple programming languages. Mixsets can thus be used to describe variations in models, not just code. The thesis uses a design science approach as its research methodology. The mixset concept is evaluated through three case studies. The first applies mixsets to the Oracle Berkeley Database SPL, which is used in other literature to evaluate SPL concepts. This study shows that the mixset implementation improves on the state of the art in several respects, such as elimination of complex workarounds that are required by other approaches. In the second study, mixsets help to refactor Umple into feature-oriented SPL. The case study shows how annotative fragments can be easily transformed into compositional counterparts. In the third study, mixsets help to present two alternative solutions the to the Rover Control Challenge Problem of the MDETools 2018 workshop.

Model-driven software development can help tackle complexity when developing large software systems. Model-driven development tools facilitate this. Such tools support multiple features and languages; some are multi-platform and support multi-language code generation from models. Umple is a full-featured open source language and modelling tool that we used as a basis for this thesis. Distribution concerns have become a critical part of modern software systems. In this thesis, we present how we extended Umple to support the development of model-driven synchronous or asynchronous distributed systems. Our contributions provide simple syntax, model analysis capabilities, and programming APIs, which allow users to change the configuration of systems both at development and deployment stages. We also demonstrate how a system can be modeled without distribution concerns and easily be transformed to a distributed system through our approach. The contributions of this thesis are: a) Creating a mechanism to distribute objects in Umple; b) Developing new semantics for modelling of distributed objects and providing supporting syntax for this in Umple; c) Investigating different patterns and technologies to implement code generation for distributed systems; d) Implementation, testing, and comparison of the distributed feature in Umple for executable Java code; and e) implementing a mechanism to dynamically modify the distribution plan at runtime.

This thesis describes extensions to state machines in the Umple model-oriented programming language to offer queued state machines (QSM), pooled state machines (PSM) and handing of the arrival of unexpected events. These features allow for modeling the behavior of a system or protocol in a more accurate way in Umple because they enable detecting and fixing common design errors such as unspecified receptions. In addition, they simplify the communication between communicating state machines by allowing for asynchronous calls of events and passing of messages between state machines. Also, a pooled state machine (PSM) has been developed to provide a different policy of handling events that avoid unspecified receptions. This mechanism has similar semantics as a queued state machine, but it differs in the way of detecting unspecified receptions because it helps handling these errors. Another mechanism has been designed to use the keyword ‘unspecified’ in whatever state of a state machine the user wants to detect these errors. In this thesis, the test-driven development (TDD) process has been followed to first modify the Umple syntax to add ‘queued,’ ‘pooled,’ and ‘unspecified’ keywords to Umple state machine’s grammar; and second, to make a change to the Umple semantics in order to implement these extensions in Umple. Then, additional modifications have been made to allow for Java code generation from those types of state machines. Finally, more test cases have been written to ensure that these models are syntactically and semantically correct. In order to show the usefulness and usability of these new features, an example is shown as a case study that is modeled using the queued state machine (QSM) besides other small tests cases.

We present a set of easy-to-use methods and tools to analyze human attention, behaviour, and physiological responses. A potential application of our work is evaluating user interfaces being used in a natural manner. Our approach is designed to be scalable and to work remotely on regular personal computers using expensive and noninvasive equipment. The data sources our tool processes are nonintrusive, and captured from video; i.e. eye tracking, and facial expressions. For video data retrieval, we use a basic webcam. We investigate combinations of observation modalities to detect and extract affective and mental states. Our tool provides a pipeline-based approach that 1) collects observational, data 2) incorporates and synchronizes the signal modality mentioned above, 3) detects users' affective and mental state, 4) records user interaction with applications and pinpoints the parts of the screen users are looking at, 5) analyzes and visualizes results. We describe the design, implementation, and validation of a novel multimodal signal fusion engine, Deep Temporal Credence Network (DTCN). The engine uses Deep Neural Networks to provide 1) a generative and probabilistic inference model, and 2) to handle multimodal data such that its performance does not degrade due to the absence of some modalities. We report on the recognition accuracy of basic emotions for each modality. Then, we evaluate our engine in terms of effectiveness of recognizing basic six emotions and six mental states, which are agreeing, concentrating, disagreeing, interested, thinking, and unsure. Our principal contributions include the implementation of a 1) multimodal signal fusion engine, 2) real time recognition of affective and primary mental states from nonintrusive and inexpensive modality, 3) novel mental state-based visualization techniques, 3D heatmaps, 3D scanpaths, and widget heatmaps that find parts of the user interface where users are perhaps unsure, annoyed, frustrated, or satisfied.