Hybridizing and applying computational intelligence techniques

As computers are increasingly relied upon to perform tasks of increasing complexity affecting many aspects of society, it is imperative that the underlying computational methods performing the tasks have high performance in terms of effectiveness and scalability. A common solution employed to perform such complex tasks are computational intelligence (CI) techniques. CI techniques use approaches influenced by nature to solve problems in which traditional modeling approaches fail due to impracticality, intractability, or mathematical ill-posedness. While CI techniques can perform considerably better than traditional modeling approaches when solving complex problems, the scalability performance of a given CI technique alone is not always optimal. Hybridization is a popular process by which a better performing CI technique is created from the combination of multiple existing techniques in a logical manner. In the first paper in this thesis, a novel hybridization of two CI techniques, accuracy-based learning classifier systems (XCS) and cluster analysis, is presented that improves upon the efficiency and, in some cases, the effectiveness of XCS. A number of tasks in software engineering are performed manually, such as defining expected output in model transformation testing. Especially since the number and size of projects that rely on tasks that must be performed manually, it is critical that automated approaches are employed to reduce or eliminate manual effort from these tasks in order to scale efficiently. The second paper in this thesis details a novel application of a CI technique, multi-objective simulated annealing, to the task of test case model generation to reduce the resulting effort required to manually update expected transformation output --Abstract, page iv

Lightweight and static verification of UML executable models

Executable models play a key role in many development methods (such as MDD and MDA) by facilitating the immediate simulation/implementation of the software system under development. This is possible because executable models include a fine-grained specification of the system behaviour using an action language. Executable models are not a new concept but are now experiencing a comeback. As a relevant example, the OMG has recently published the first version of the “Foundational Subset for Executable UML Models” (fUML) standard, an executable subset of the UML that can be used to define, in an operational style, the structural and behavioural semantics of systems. The OMG has also published a beta version of the “Action Language for fUML” (Alf) standard, a concrete syntax conforming to the fUML abstract syntax, that provides the constructs and textual notation to specify the fine-grained behaviour of systems. The OMG support to executable models is substantially raising the interest of software companies for this topic. Given the increasing importance of executable models and the impact of their correctness on the final quality of software systems derived from them, the existence of methods to verify the correctness of executable models is becoming crucial. Otherwise, the quality of the executable models (and in turn the quality of the final system generated from them) will be compromised. Despite the number of research works targetting the verification of software models, their computational cost and poor feedback makes them difficult to integrate in current software development processes. Therefore, there is the need for efficient and useful methods to check the correctness of executable models and tools integrated to the modelling tools used by designers. In this thesis we propose a verification framework to help the designers to improve the quality of their executable models. Our framework is composed of a set of lightweight static methods, i.e. methods that do not require to execute the model in order to check the desired property. These methods are able to check several properties over the behavioural part of an executable model (for instance, over the set of operations that compose a behavioural executable model) such as syntactic correctness (i.e. all the operations in the behavioural model conform to the syntax of the language in which it is described), non-redundancy (i.e. there is no another operation with exactly the same behaviour), executability (i.e. after the execution of an operation, the reached system state is -in case of strong executability- or may be -in case of weak executability- consistent with the structural model and its integrity constraints) and completeness (i.e. all possible changes on the system state can be performed through the execution of the operations defined in the executable model). For incorrect models, the methods that compose our verification framework return a meaningful feedback that helps repairing the detected inconsistencies

Integration and Test of MOF/UML-based Domain-specific Modeling Languages

In model-driven development (MDD), domain-specific modeling languages (DSMLs) are used as tailor-made software languages targeting dedicated application domains. Due to the narrow domain coverage of DSMLs, demands to integrate their individual functionality into a consolidated DSML arise (e.g., developing a software product combining two or more pre-existing DSMLs). However, in order to realize the benefits of integrated DSMLs, it must be ensured that the integrated DSML is correctly implemented and behaves as specified. To support the integration and the test of DSMLs, this thesis presents an approach targeting the Meta Object Facility (MOF) and the Unified Modeling Language (UML)- a metamodeling infrastructure frequently employed for the MDD of software systems. The integration of DSMLs is based on a rewriting technique for model-to-text (M2T) transformations. This method allows for the reuse as well as for the automatic refactoring of M2T transformation templates to fix important syntactical mismatches between templates and the integrated DSML. To test an integrated DSML, scenarios are used to define domain requirements on an abstract level (via structured text descriptions). In a subsequent step, executable scenario tests are derived from the requirements-level scenarios. These executable scenario specifications are then employed to test the integrated DSML for compliance with corresponding domain requirements. Empirical evaluations of the approach (case studies, controlled experiment) demonstrate its successful application, collect evidence for its usefulness, and quantify its benefits. The integrated proof-of-concept implementations build on the Eclipse Modeling Framework (EMF), making use of and extending well-known Eclipse-based projects. All accompanying developments are placed into the public domain as free/libre open source software. Within the framework of this thesis, research results were originally published as individual contributions (workshop, conference, and journal articles). All research contributions are results of applying a design science research approach. (author's abstract