A avaliação e melhoria de um processo de software requer um grande esforço por parte de gerentes e desenvolvedores, uma vez que a obtenção de dados para tomada de decisão, acerca da evolução do processo nem sempre é trivial. O desenvolvimento de software, como qualquer disciplina de Engenharia, necessita de mecanismos de mensuração, para que através de uma avaliação de seus resultados o processo possa ser melhorado. Mas a mensuração pode ser uma tarefa bastante trabalhosa sem o auxílio de metodologias ou ferramentas de apoio. Neste sentido, este trabalho apresenta um modelo para mensuração em processos de software, no contexto do projeto APSEE-Prosoft. O objetivo do modelo proposto é prover suporte a realização de mensuração em processos de software, através do desenvolvimento e implantação de programas de mensuração, visando auxiliar aos gerentes na realização de atividades como planejamento, coleta e análise de métricas em um processo de software. Neste trabalho são combinados aspectos relacionados a importantes áreas da Engenharia de Software, como mensuração, processos de software, ambientes de engenharia de software centrados em processos (PSEE), bem como a utilização de métodos formais para a definição e especificação de um modelo de mensuração integrado a um PSEE. / The software process evaluation and improvement requests great effort of managers and developers, especially because obtaining data for decision support (about process evolution) is not a simple task. The software development, as any discipline of Engineering, needs measurement mechanisms, so that through an evaluation of its results, the process can be improved. But measurement can be a difficult task without the aid of methodologies or support tools. In this sense, this paper presents a model for software processes measurement, on the context of APSEE-Prosoft project. The model's objective is to provide support for the measurement in software processes, through the development and implantation of measurement programs, to aid managers in the accomplishment of activities such as planning, collecting and analysis of metrics in a software process. This paper combines aspects related to important areas of Software Engineering, as measurement, software process, process-centered engineering environment (PSEE), besides the use of formal methods for a definition and specification of a measurement model integrated to a PSEE.

A avaliação e melhoria de um processo de software requer um grande esforço por parte de gerentes e desenvolvedores, uma vez que a obtenção de dados para tomada de decisão, acerca da evolução do processo nem sempre é trivial. O desenvolvimento de software, como qualquer disciplina de Engenharia, necessita de mecanismos de mensuração, para que através de uma avaliação de seus resultados o processo possa ser melhorado. Mas a mensuração pode ser uma tarefa bastante trabalhosa sem o auxílio de metodologias ou ferramentas de apoio. Neste sentido, este trabalho apresenta um modelo para mensuração em processos de software, no contexto do projeto APSEE-Prosoft. O objetivo do modelo proposto é prover suporte a realização de mensuração em processos de software, através do desenvolvimento e implantação de programas de mensuração, visando auxiliar aos gerentes na realização de atividades como planejamento, coleta e análise de métricas em um processo de software. Neste trabalho são combinados aspectos relacionados a importantes áreas da Engenharia de Software, como mensuração, processos de software, ambientes de engenharia de software centrados em processos (PSEE), bem como a utilização de métodos formais para a definição e especificação de um modelo de mensuração integrado a um PSEE. / The software process evaluation and improvement requests great effort of managers and developers, especially because obtaining data for decision support (about process evolution) is not a simple task. The software development, as any discipline of Engineering, needs measurement mechanisms, so that through an evaluation of its results, the process can be improved. But measurement can be a difficult task without the aid of methodologies or support tools. In this sense, this paper presents a model for software processes measurement, on the context of APSEE-Prosoft project. The model's objective is to provide support for the measurement in software processes, through the development and implantation of measurement programs, to aid managers in the accomplishment of activities such as planning, collecting and analysis of metrics in a software process. This paper combines aspects related to important areas of Software Engineering, as measurement, software process, process-centered engineering environment (PSEE), besides the use of formal methods for a definition and specification of a measurement model integrated to a PSEE.

Submitted by Irene Nascimento (irene.kessia@ufpe.br) on 2017-03-08T19:19:52Z No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_FelipeOliveiraBarbalho.pdf: 1338681 bytes, checksum: 59450531ef14c232cbd53efcacba8b7e (MD5) / Made available in DSpace on 2017-03-08T19:19:52Z (GMT). No. of bitstreams: 2 license_rdf: 1232 bytes, checksum: 66e71c371cc565284e70f40736c94386 (MD5) Dissertação_FelipeOliveiraBarbalho.pdf: 1338681 bytes, checksum: 59450531ef14c232cbd53efcacba8b7e (MD5) Previous issue date: 2014-04-28 / Há uma tendência das organizações que atuam no desenvolvimento e manutenção de software em utilizarem Pontos de Função como medida padrão em seus processos de medição. Atualmente a análise de pontos de função é a técnica mais utilizada entre as organizações brasileiras. Por outro lado, o COSMIC é uma técnica de medição considerada como a segunda geração em método de medição funcional de projetos de desenvolvimento e manutenção de software, sendo precisa e abrangente para medir software e estimar esforço de desenvolvimento, despertando o interesse do mercado de desenvolvimento de software por essa métrica. Quando considerada a migração das bases históricas de medição de software das organizações para uma nova unidade de medida, há como consequência um alto custo para se medir os projetos legados. Nesse sentido, o objetivo desse trabalho é propor uma alternativa para migração de bases históricas de Pontos de Função para o COSMIC. A abordagem propõe uma fórmula de conversão, o qual foi encontrada a partir da medição de quatro projetos de desenvolvimento de software analisados nessas duas técnicas, para atualizar seus dados sem o custo de refazer toda sua base histórica. / There is a tendency in software development and maintenance organizations in using Function Points as a standard measure in their measurement processes. Currently the analysis of function points is the most used technique among Brazilian organizations. On the other hand, COSMIC is a measurement technique considered as the secondgeneration method of functional measurement for software development and maintenance projects, with an accurate and comprehensive approach to measure and estimate software development effort, arousing interest of software development market for this metric. When organizations are considering the migration of their historical measure basis for a new measurement unit, there is a consequent high cost to measure the legacy projects. In this sense, the purpose of this work is to propose an alternative to migrate historical bases of Function Points to COSMIC. The approach proposes a conversion factor, which was found from the measurement of four software development projects analyzed in these two techniques to update its data without the cost of redoing the entire historical basis.

Context: Early prediction of software cost and quality is important for better software planning and controlling. In early development phases, design complexity metrics are considered as useful indicators of software testing effort and some quality attributes. Although many studies investigate the relationship between design complexity and cost and quality, it is unclear what we have learned from these studies, because no systematic synthesis exists to date. Aim: The research presented in this thesis is intended to contribute for the body of knowledge about cost and quality prediction. A major part of this thesis presents the systematic review that provides detail discussion about state of the art of research on relationship between software design metric and cost and software quality. Method: This thesis starts with a literature review to identify the important complexity dimensions and potential predictors for predicting external software quality attributes are identified. Second, we aggregated Spearman correlation coefficients and estimated odds ratios from univariate logistic regression models from 59 different data sets from 57 primary studies by a tailored meta-analysis approach. At last, it is an attempt to evaluate and explain for disagreement among selected studies. Result: There are not enough studies for quantitatively summarizing relationship between design complexity and development cost. Fault proneness and maintainability is the main focused characteristics that consume 75% total number of studies. Within fault proneness and maintainability studies, coupling and scale are two complexity dimensions that are most frequently used. Vote counting shows evidence about positive impact of some design metrics on these two quality attributes. Meta analysis shows the aggregated effect size of Line of code (LOC) is stronger than those of WMC, RFC and CBO. The aggregated effect sizes of LCOM, DIT and NOC are at trivial to small level. In subgroup analysis, defect collections phase explains more than 50% of observed variation in five out of seven investigated metrics. Conclusions: Coupling and scale metrics are stronger correlated to fault proneness than cohesion and inheritance metrics. No design metrics are stronger single predictors than LOC. We found that there is a strong disagreement between the individual studies, and that defect collection phase is able to partially explain the differences between studies.

Complex modern software is often built using existing application frameworks and middleware frameworks. These frameworks provide useful common services, while simultaneously imposing architectural rules and constraints. Existing software architecture evaluation methods do not explicitly consider the implications of these frameworks for software architecture. This research extends scenario-based architecture evaluation methods by incorporating framework-related information into different evaluation activities. I propose four techniques which target four different activities within a scenario-based architecture evaluation method. 1) Scenario development: A new technique was designed aiming to extract general scenarios and tactics from framework-related architectural patterns. The technique is intended to complement the current scenario development process. The feasibility of the technique was validated through a case study. Significant improvements of scenario quality were observed in a controlled experiment conducted by another colleague. 2) Architecture representation: A new metrics-driven technique was created to reconstruct software architecture in a just-in-time fashion. This technique was validated in a case study. This approach has significantly improved the efficiency of architecture representation in a complex environment. 3) Attribute specific analysis (performance only): A model-driven approach to performance measurement was applied by decoupling framework-specific information from performance testing requirements. This technique was validated on two platforms (J2EE and Web Services) through a number of case studies. This technique leads to the benchmark producing more representative measures of the eventual application. It reduces the complexity behind the load testing suite and framework-specific performance data collecting utilities. 4) Trade-off and sensitivity analysis: A new technique was designed seeking to improve the Analytical Hierarchical Process (AHP) for trade-off and sensitivity analysis during a framework selection process. This approach was validated in a case study using data from a commercial project. The approach can identify 1) trade-offs implied by an architecture alternative, along with the magnitude of these trade-offs. 2) the most critical decisions in the overall decision process 3) the sensitivity of the final decision and its capability for handling quality attribute priority changes.

Statische Codemetriken sind wichtige Indikatoren für die Qualität eines Softwaresystems. Sie beleuchten dabei unterschiedliche Aspekte eines Softwaresystems. Deshalb ist es notwendig, mehrere Codemetriken zu nutzen, um die Qualität eines Softwaresystems in seiner Gesamtheit bewerten zu können. Wünschenswert wäre zudem eine Darstellung, die die Struktur des Gesamtsystems und die Bewertung einzelner Elemente eines Softwaresystems in einer Darstellung kombiniert. Die Arbeit untersucht deshalb, welche Metaphern geeignet sind, um eine solche Darstellung zu ermöglichen. Ein zweites Ziel der Arbeit war es, eine solche Visualisierung automatisch erzeugen zu können. Dafür wurde ein Generator entwickelt, der diese Anforderung erfüllt. Zur Konzeption dieses Generators kamen Techniken aus der generativen Softwareentwicklung zum Einsatz. Bei der Umsetzung des Generators wurde auf Techniken aus der modellgetriebenen Softwareentwicklung zurückgegriffen, vor allem auf Techniken aus dem openArchitectureWare-Framework. Der Generator kann in Eclipse eingebunden werden und ist in der Lage, aus einem Java-Projekt die Struktur und die Metrikwerte automatisch zu extrahieren. Diese Werte werden daraufhin in ein dreidimensionales Modell überführt, das auf dem offenen Extensible 3D Standard basiert. Der Generator ermöglichte zudem die Evaluierung zweier unterschiedlicher Metaphern, die im Rahmen der Arbeit durchgeführt wurde.

Software quality ensures that applications that are developed are failure free. Some modern systems are intricate, due to the complexity of their information processes. Software fault prediction is an important quality assurance activity, since it is a mechanism that correctly predicts the defect proneness of modules and classifies modules that saves resources, time and developers’ efforts. In this study, a model that selects relevant features that can be used in defect prediction was proposed. The literature was reviewed and it revealed that process metrics are better predictors of defects in version systems and are based on historic source code over time. These metrics are extracted from the source-code module and include, for example, the number of additions and deletions from the source code, the number of distinct committers and the number of modified lines. In this research, defect prediction was conducted using open source software (OSS) of software product line(s) (SPL), hence process metrics were chosen. Data sets that are used in defect prediction may contain non-significant and redundant attributes that may affect the accuracy of machine-learning algorithms. In order to improve the prediction accuracy of classification models, features that are significant in the defect prediction process are utilised. In machine learning, feature selection techniques are applied in the identification of the relevant data. Feature selection is a pre-processing step that helps to reduce the dimensionality of data in machine learning. Feature selection techniques include information theoretic methods that are based on the entropy concept. This study experimented the efficiency of the feature selection techniques. It was realised that software defect prediction using significant attributes improves the prediction accuracy. A novel MICFastCR model, which is based on the Maximal Information Coefficient (MIC) was developed to select significant attributes and Fast Correlation Based Filter (FCBF) to eliminate redundant attributes. Machine learning algorithms were then run to predict software defects. The MICFastCR achieved the highest prediction accuracy as reported by various performance measures. / School of Computing / Ph. D. (Computer Science)

Made available in DSpace on 2015-03-03T15:47:44Z (GMT). No. of bitstreams: 1 TassiaAVF.pdf: 1514001 bytes, checksum: a6dbf5832432db823e99d729ccf7fa2b (MD5) Previous issue date: 2009-02-20 / Nowadays, there are many aspect-oriented middleware implementations that take advantage of the modularity provided by the aspect oriented paradigm. Although the works always present an assessment of the middleware according to some quality attribute, there is not a specific set of metrics to assess them in a comprehensive way, following various quality attributes. This work aims to propose a suite of metrics for the assessment of aspect-oriented middleware systems at different development stages: design, refactoring, implementation and runtime. The work presents the metrics and how they are applied at each development stage. The suite is composed of metrics associated to static properties (modularity, maintainability, reusability, exibility, complexity, stability, and size) and dynamic properties (performance and memory consumption). Such metrics are based on existing assessment approaches of object-oriented and aspect-oriented systems. The proposed metrics are used in the context of OiL (Orb in Lua), a middleware based on CORBA and implemented in Lua, and AO-OiL, the refactoring of OIL that follows a reference architecture for aspect-oriented middleware systems. The case study performed in OiL and AO-OiL is a system for monitoring of oil wells. This work also presents the CoMeTA-Lua tool to automate the collection of coupling and size metrics in Lua source code / Atualmente, ha diversas implementa??es de sistemas de middleware orientado a aspectos que aproveitam o suporte a modulariza??o do paradigma de orienta??o a aspectos. Apesar desses trabalhos sempre apresentarem uma avalia??o do middleware de acordo com algum atributo de qualidade, n?o ha ainda um conjunto de metricas especificamente de nidas para avali?-los de forma abrangente, seguindo v?rios atributos de qualidade. Este trabalho tem como objetivo propor um conjunto de metricas para avalia??o de sistemas de middleware orientado a aspectos em diferentes fases de desenvolvimento: design, refatora??o, implementa??o e execu??o. O trabalho apresenta as metricas e como elas s?o aplicadas em cada uma das fases de desenvolvimento. O conjunto e composto por metricas associadas a propriedades estaticas (modularidade, manutenibilidade, reusabilidade, exibilidade, complexidade, estabilidade e tamanho) e din?micas (desempenho e consumo de mem oria). Tais metricas s?o baseadas em abordagens existentes de avalia??o de sistemas orientados a aspectos e a objetos. As metricas propostas s?o utilizadas no contexto do OiL (Orb in Lua), um middleware baseado em CORBA e implementado em Lua, e AO-OiL, uma refatora??o do OIL que segue uma arquitetura de refer?ncia para sistemas de middleware orientados a aspectos. O estudo de caso executado no OiL e no AO-OiL e um sistema de monitoramento de po?os de petroleo. Esse trabalho apresenta ainda a ferramenta CoMeTA-Lua para automatizar a coleta das metricas de tamanho e acoplamento em codigo-fonte Lua

Le contrôle de version est la pierre angulaire des processus de développement de logiciels modernes. Tout en construisant des logiciels de plus en plus complexes, les développeurs doivent comprendre des sous-systèmes de code source qui leur sont peu familier. Alors que la compréhension de la logique d'un code étranger est relativement simple, la compréhension de sa conception et de sa genèse est plus compliquée. Elle n'est souvent possible que par les descriptions des révisions et de la documentation du projet qui sont dispersées et peu fiables -- quand elles existent. Ainsi, les développeurs ont besoin d'une base de référence fiable et pertinente pour comprendre l'historique des projets logiciels. Dans cette thèse, nous faisons les premiers pas vers la compréhension des motifs de changement dans les historiques de révision. Nous étudions les changements prenant place dans les métriques logicielles durant l'évolution d'un projet. Au travers de multiples études exploratoires, nous réalisons des expériences quantitatives et qualitatives sur plusieurs jeux de données extraits à partir d'un ensemble de 13 projets. Nous extrayons les changements dans les métriques logicielles de chaque commit et construisons un jeu de donnée annoté manuellement comme vérité de base. Nous avons identifié plusieurs catégories en analysant ces changements. Un motif en particulier nommé "compromis", dans lequel certaines métriques peuvent s'améliorer au détriment d'autres, s'est avéré être un indicateur prometteur de changements liés à la conception -- dans certains cas, il laisse également entrevoir une intention de conception consciente de la part des auteurs des changements. Pour démontrer les observations de nos études exploratoires, nous construisons un modèle général pour identifier l'application d'un ensemble bien connu de principes de conception dans de nouveaux projets. Nos résultats suggèrent que les fluctuations de métriques ont le potentiel d'être des indicateurs pertinents pour gagner des aperçus macroscopiques sur l'évolution de la conception dans l'historique de développement d'un projet. / Version control is the backbone of the modern software development workflow. While building more and more complex systems, developers have to understand unfamiliar subsystems of source code. Understanding the logic of unfamiliar code is relatively straightforward. However, understanding its design and its genesis is often only possible through scattered and unreliable commit messages and project documentation -- when they exist. Thus, developers need a reliable and relevant baseline to understand the history of software projects. In this thesis, we take the first steps towards understanding change patterns in commit histories. We study the changes in software metrics through the evolution of projects. Through multiple exploratory studies, we conduct quantitative and qualitative experiments on several datasets extracted from a pool of 13 projects. We mine the changes in software metrics for each commit of the respective projects and manually build oracles to represent ground truth. We identified several categories by analyzing these changes. One pattern, in particular, dubbed "tradeoffs", where some metrics may improve at the expense of others, proved to be a promising indicator of design-related changes -- in some cases, also hinting at a conscious design intent from the authors of the changes. Demonstrating the findings of our exploratory studies, we build a general model to identify the application of a well-known set of design principles in new projects. Our overall results suggest that metric fluctuations have the potential to be relevant indicators for valuable macroscopic insights about the design evolution in a project's development history.

Statische Codemetriken sind wichtige Indikatoren für die Qualität eines Softwaresystems. Sie beleuchten dabei unterschiedliche Aspekte eines Softwaresystems. Deshalb ist es notwendig, mehrere Codemetriken zu nutzen, um die Qualität eines Softwaresystems in seiner Gesamtheit bewerten zu können. Wünschenswert wäre zudem eine Darstellung, die die Struktur des Gesamtsystems und die Bewertung einzelner Elemente eines Softwaresystems in einer Darstellung kombiniert. Die Arbeit untersucht deshalb, welche Metaphern geeignet sind, um eine solche Darstellung zu ermöglichen. Ein zweites Ziel der Arbeit war es, eine solche Visualisierung automatisch erzeugen zu können. Dafür wurde ein Generator entwickelt, der diese Anforderung erfüllt. Zur Konzeption dieses Generators kamen Techniken aus der generativen Softwareentwicklung zum Einsatz. Bei der Umsetzung des Generators wurde auf Techniken aus der modellgetriebenen Softwareentwicklung zurückgegriffen, vor allem auf Techniken aus dem openArchitectureWare-Framework. Der Generator kann in Eclipse eingebunden werden und ist in der Lage, aus einem Java-Projekt die Struktur und die Metrikwerte automatisch zu extrahieren. Diese Werte werden daraufhin in ein dreidimensionales Modell überführt, das auf dem offenen Extensible 3D Standard basiert. Der Generator ermöglichte zudem die Evaluierung zweier unterschiedlicher Metaphern, die im Rahmen der Arbeit durchgeführt wurde.