Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach

Historically, software production methods and tools have a unique goal: to produce high quality software. Since the goal of Model-Driven Development (MDD) methods is no different, MDD methods have emerged to take advantage of the benefits of using conceptual models to produce high quality software. In such MDD contexts, conceptual models are used as input to automatically generate final applications. Thus, we advocate that there is a relation between the quality of the final software product and the quality of the models used to generate it. The quality of conceptual models can be influenced by many factors. In this thesis, we focus on the accuracy of the techniques used to predict the characteristics of the development process and the generated products. In terms of the prediction techniques for software development processes, it is widely accepted that knowing the functional size of applications in order to successfully apply effort models and budget models is essential. In order to evaluate the quality of generated applications, defect detection is considered to be the most suitable technique. The research goal of this thesis is to provide an accurate measurement procedure based on COSMIC for the automatic sizing of object-oriented OO-Method MDD applications. To achieve this research goal, it is necessary to accurately measure the conceptual models used in the generation of object-oriented applications. It is also very important for these models not to have defects so that the applications to be measured are correctly represented. In this thesis, we present the OOmCFP (OO-Method COSMIC Function Points) measurement procedure. This procedure makes a twofold contribution: the accurate measurement of objectoriented applications generated in MDD environments from the conceptual models involved, and the verification of conceptual models to allow the complete generation of correct final applications from the conceptual models involved. The OOmCFP procedure has been systematically designed, applied, and automated. This measurement procedure has been validated to conform to the ISO 14143 standard, the metrology concepts defined in the ISO VIM, and the accuracy of the measurements obtained according to ISO 5725. This procedure has also been validated by performing empirical studies. The results of the empirical studies demonstrate that OOmCFP can obtain accurate measures of the functional size of applications generated in MDD environments from the corresponding conceptual models.Marín Campusano, BM. (2011). Functional Size Measurement and Model Verification for Software Model-Driven Developments: A COSMIC-based Approach [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11237Palanci

Using PDCA as a General Framework for Teaching and Evaluating the Learning of Software Engineering Disciplines

Software engineering disciplines need to be taught in contexts as diverse as undergraduate courses and large corporations training programs. A primary challenge in teaching such disciplines, in any context, is to quickly and effectively evaluate the students learning and measure their strengths and weaknesses. Another challenge is to make students of different instances of a discipline end up with the same basic foundations, making the knowledge independent of the instructor. To overcome these challenges we propose an approach for software engineering teaching based on adapted PDCA cycles and checklists as instruments of evaluation. We also report a case study which shows the implementation of this approach in teaching a first year undergraduate software engineering course. With a careful definition of checklists, the use of the adapted version of PDCA as a methodology for software engineering teaching is promising, allowing an efficient form of evaluation

Investigating Effective Inspection of Object-Oriented Code

Since the development of software inspection over twenty-five years ago it has become established as an effective means of detecting defects. Inspections were originally developed at a time when the procedural paradigm was dominant but, with the Object- Oriented (OO) paradigm growing in influence and use, there now exists a lack of guidance on how to apply inspections to OO systems. Object-oriented and procedural languages differ not only in their syntax but also in a number of more profound ways - the encapsulation of data and associated functionality, the common use of inheritance, and the concepts of polymorphism and dynamic binding. These factors influence the way that modules (classes) are created in OO systems, which in turn influences the way that OO systems are structured and execute. Failure to take this into account may hinder the application of inspections to OO code. This thesis shows that the way in which the objectoriented paradigm distributes related functionality can have a serious impact on code inspection and, to address this problem, it develops and empirically evaluates three code reading techniques

A Process Model for the Integrated Reasoning about Quantitative IT Infrastructure Attributes

IT infrastructures can be quantitatively described by attributes, like performance or energy efficiency. Ever-changing user demands and economic attempts require varying short-term and long-term decisions regarding the alignment of an IT infrastructure and particularly its attributes to this dynamic surrounding. Potentially conflicting attribute goals and the central role of IT infrastructures presuppose decision making based upon reasoning, the process of forming inferences from facts or premises. The focus on specific IT infrastructure parts or a fixed (small) attribute set disqualify existing reasoning approaches for this intent, as they neither cover the (complex) interplay of all IT infrastructure components simultaneously, nor do they address inter- and intra-attribute correlations sufficiently. This thesis presents a process model for the integrated reasoning about quantitative IT infrastructure attributes. The process model’s main idea is to formalize the compilation of an individual reasoning function, a mathematical mapping of parametric influencing factors and modifications on an attribute vector. Compilation bases upon model integration to benefit from the multitude of existing specialized, elaborated, and well-established attribute models. The achieved reasoning function consumes an individual tuple of IT infrastructure components, attributes, and external influencing factors to expose a broad applicability. The process model formalizes a reasoning intent in three phases. First, reasoning goals and parameters are collected in a reasoning suite, and formalized in a reasoning function skeleton. Second, the skeleton is iteratively refined, guided by the reasoning suite. Third, the achieved reasoning function is employed for What-if analyses, optimization, or descriptive statistics to conduct the concrete reasoning. The process model provides five template classes that collectively formalize all phases in order to foster reproducibility and to reduce error-proneness. Process model validation is threefold. A controlled experiment reasons about a Raspberry Pi cluster’s performance and energy efficiency to illustrate feasibility. Besides, a requirements analysis on a world-class supercomputer and on the European-wide execution of hydro meteorology simulations as well as a related work examination disclose the process model’s level of innovation. Potential future work employs prepared automation capabilities, integrates human factors, and uses reasoning results for the automatic generation of modification recommendations.IT-Infrastrukturen können mit Attributen, wie Leistung und Energieeffizienz, quantitativ beschrieben werden. Nutzungsbedarfsänderungen und ökonomische Bestrebungen erfordern Kurz- und Langfristentscheidungen zur Anpassung einer IT-Infrastruktur und insbesondere ihre Attribute an dieses dynamische Umfeld. Potentielle Attribut-Zielkonflikte sowie die zentrale Rolle von IT-Infrastrukturen erfordern eine Entscheidungsfindung mittels Reasoning, einem Prozess, der Rückschlüsse (rein) aus Fakten und Prämissen zieht. Die Fokussierung auf spezifische Teile einer IT-Infrastruktur sowie die Beschränkung auf (sehr) wenige Attribute disqualifizieren bestehende Reasoning-Ansätze für dieses Vorhaben, da sie weder das komplexe Zusammenspiel von IT-Infrastruktur-Komponenten, noch Abhängigkeiten zwischen und innerhalb einzelner Attribute ausreichend berücksichtigen können. Diese Arbeit präsentiert ein Prozessmodell für das integrierte Reasoning über quantitative IT-Infrastruktur-Attribute. Die grundlegende Idee des Prozessmodells ist die Herleitung einer individuellen Reasoning-Funktion, einer mathematischen Abbildung von Einfluss- und Modifikationsparametern auf einen Attributvektor. Die Herleitung basiert auf der Integration bestehender (Attribut-)Modelle, um von deren Spezialisierung, Reife und Verbreitung profitieren zu können. Die erzielte Reasoning-Funktion verarbeitet ein individuelles Tupel aus IT-Infrastruktur-Komponenten, Attributen und externen Einflussfaktoren, um eine breite Anwendbarkeit zu gewährleisten. Das Prozessmodell formalisiert ein Reasoning-Vorhaben in drei Phasen. Zunächst werden die Reasoning-Ziele und -Parameter in einer Reasoning-Suite gesammelt und in einem Reasoning-Funktions-Gerüst formalisiert. Anschließend wird das Gerüst entsprechend den Vorgaben der Reasoning-Suite iterativ verfeinert. Abschließend wird die hergeleitete Reasoning-Funktion verwendet, um mittels “What-if”–Analysen, Optimierungsverfahren oder deskriptiver Statistik das Reasoning durchzuführen. Das Prozessmodell enthält fünf Template-Klassen, die den Prozess formalisieren, um Reproduzierbarkeit zu gewährleisten und Fehleranfälligkeit zu reduzieren. Das Prozessmodell wird auf drei Arten validiert. Ein kontrolliertes Experiment zeigt die Durchführbarkeit des Prozessmodells anhand des Reasonings zur Leistung und Energieeffizienz eines Raspberry Pi Clusters. Eine Anforderungsanalyse an einem Superrechner und an der europaweiten Ausführung von Hydro-Meteorologie-Modellen erläutert gemeinsam mit der Betrachtung verwandter Arbeiten den Innovationsgrad des Prozessmodells. Potentielle Erweiterungen nutzen die vorbereiteten Automatisierungsansätze, integrieren menschliche Faktoren, und generieren Modifikationsempfehlungen basierend auf Reasoning-Ergebnissen

A Value-Driven Framework for Software Architecture

Software that is not aligned with the business values of the organization for which it was developed does not entirely fulfill its raison d’etre. Business values represent what is important in a company, or organization, and should influence the overall software system behavior, contributing to the overall success of the organization. However, approaches to derive a software architecture considering the business values exchanged between an organization and its market players are lacking. Our quest is to address this problem and investigate how to derive value-centered architectural models systematically. We used the Technology Research method to address this PhD research question. This methodological approach proposes three steps: problem analysis, innovation, and validation. The problem analysis was performed using systematic studies of the literature to obtain full coverage on the main themes of this work, particularly, business value modeling, software architecture methods, and software architecture derivation methods. Next, the innovation step was accomplished by creating a framework for the derivation of a software reference architecture model considering an organization’s business values. The resulting framework is composed of three core modules: Business Value Modeling, Agile Reference Architecture Modeling, and Goal-Driven SOA Architecture Modeling. While the Business value modeling module focuses on building a stakeholder-centric business specification, the Agile Reference Architecture Modeling and the Goal-Driven SOA Architecture Modeling modules concentrate on generating a software reference architecture aligned with the business value specification. Finally, the validation part of our framework is achieved through proof-of-concept prototypes for three new domain specific languages, case studies, and quasi-experiments, including a family of controlled experiments. The findings from our research show that the complexity and lack of rigor in the existing approaches to represent business values can be addressed by an early requirements specification method that represents the value exchanges of a business. Also, by using sophisticated model-driven engineering techniques (e.g., metamodels, model transformations, and model transformation languages), it was possible to obtain source generators to derive a software architecture model based on early requirements value models, while assuring traceability throughout the architectural derivation process. In conclusion, despite using sophisticated techniques, the derivation process of a software reference architecture is helped by simple to use methods supported by black box transformations and guidelines that facilitate the activities for the less experienced software architects. The experimental validation process used confirmed that our framework is feasible and perceived as easy to use and useful, also indicating that the participants of the experiments intend to use it in the future

30 Years of Software Refactoring Research:A Systematic Literature Review

Due to the growing complexity of software systems, there has been a dramatic increase and industry demand for tools and techniques on software refactoring in the last ten years, defined traditionally as a set of program transformations intended to improve the system design while preserving the behavior. Refactoring studies are expanded beyond code-level restructuring to be applied at different levels (architecture, model, requirements, etc.), adopted in many domains beyond the object-oriented paradigm (cloud computing, mobile, web, etc.), used in industrial settings and considered objectives beyond improving the design to include other non-functional requirements (e.g., improve performance, security, etc.). Thus, challenges to be addressed by refactoring work are, nowadays, beyond code transformation to include, but not limited to, scheduling the opportune time to carry refactoring, recommendations of specific refactoring activities, detection of refactoring opportunities, and testing the correctness of applied refactorings. Therefore, the refactoring research efforts are fragmented over several research communities, various domains, and objectives. To structure the field and existing research results, this paper provides a systematic literature review and analyzes the results of 3183 research papers on refactoring covering the last three decades to offer the most scalable and comprehensive literature review of existing refactoring research studies. Based on this survey, we created a taxonomy to classify the existing research, identified research trends, and highlighted gaps in the literature and avenues for further research.Comment: 23 page

30 Years of Software Refactoring Research: A Systematic Literature Review

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/155872/4/30YRefactoring.pd

Component-based software engineering: a quantitative approach

Dissertação apresentada para a obtenção do Grau de Doutor em Informática pela Universidade Nova de Lisboa, Faculdade de Ciências e TecnologiaBackground: Often, claims in Component-Based Development (CBD) are only supported by qualitative expert opinion, rather than by quantitative data. This contrasts with the normal practice in other sciences, where a sound experimental validation of claims is standard practice. Experimental Software Engineering (ESE) aims to bridge this gap. Unfortunately, it is common to find experimental validation efforts that are hard to replicate and compare, to build up the body of knowledge in CBD. Objectives: In this dissertation our goals are (i) to contribute to evolution of ESE, in what concerns the replicability and comparability of experimental work, and (ii) to apply our proposals to CBD, thus contributing to its deeper and sounder understanding. Techniques: We propose a process model for ESE, aligned with current experimental best practices, and combine this model with a measurement technique called Ontology-Driven Measurement (ODM). ODM is aimed at improving the state of practice in metrics definition and collection, by making metrics definitions formal and executable,without sacrificing their usability. ODM uses standard technologies that can be well adapted to current integrated development environments. Results: Our contributions include the definition and preliminary validation of a process model for ESE and the proposal of ODM for supporting metrics definition and collection in the context of CBD. We use both the process model and ODM to perform a series experimental works in CBD, including the cross-validation of a component metrics set for JavaBeans, a case study on the influence of practitioners expertise in a sub-process of component development (component code inspections), and an observational study on reusability patterns of pluggable components (Eclipse plug-ins). These experimental works implied proposing, adapting, or selecting adequate ontologies, as well as the formal definition of metrics upon each of those ontologies. Limitations: Although our experimental work covers a variety of component models and, orthogonally, both process and product, the plethora of opportunities for using our quantitative approach to CBD is far from exhausted. Conclusions: The main contribution of this dissertation is the illustration, through practical examples, of how we can combine our experimental process model with ODM to support the experimental validation of claims in the context of CBD, in a repeatable and comparable way. In addition, the techniques proposed in this dissertation are generic and can be applied to other software development paradigms.Departamento de Informática of the Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa (FCT/UNL); Centro de Informática e Tecnologias da Informação of the FCT/UNL; Fundação para a Ciência e Tecnologia through the STACOS project(POSI/CHS/48875/2002); The Experimental Software Engineering Network (ESERNET);Association Internationale pour les Technologies Objets (AITO); Association forComputing Machinery (ACM