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功能點分析(Function Point Analysis)為一種考量資訊系統商業實務貢獻的功能複雜度指標，過去數十年來，許多學者對此指標的應用有過廣泛研究，但是，應用於某些領域的系統仍未有深入探討。例如本研究使用的個案，是一個點對點訊息傳遞資訊系統，其特性是採用同儕計算架構(Peer－to－Peer, P2P)，並使用後設資料模型(Meta-data Model)進行資料塑模，使用功能點分析模型進行研究，透過實際的估算步驟，期望能夠提出功能點分析的適用性問題，以求進一步應用於業界及後續學術研究。

The quality of information systems in any organization helps to determine theefficiency of the organization. Many organizations maintain a custom software portfolio, whose quality is important to the organization. Management would like to optimize the portfolio’s quality. Decisions about software replacement or enhancement are made based on organizational needs and priorities. The development resources allocated help in determining the quality of new software, and should be put to optimal use. Enhancing existing software might sound cheap and easy but it is not always efficient. This thesis proposes a simulation model - iKriya - for this problem. It explores the consequences of various development and maintenance policies which might be applied.These depend on the state of existing software portfolio, the queue and properties of proposed projects, and the resources available. Optimal decisions are made by the simulator by taking the above mentioned factors into consideration.

As a part of the quality management, product defectiveness prediction is vital for small software organizations as for instutional ones. Although for defect prediction there have been conducted a lot of studies, process enactment data cannot be used because of the difficulty of collection. Additionally, there is no proposed approach known in general for the analysis of process enactment data in software engineering. In this study, we developed a method to show the applicability of process enactment data for defect prediction and answered &ldquo / Is process enactment data beneficial for defect prediction?&rdquo / , &ldquo / How can we use process enactment data?&rdquo / and &ldquo / Which approaches and analysis methods can our method support?&rdquo / questions. We used multiple case study design and conducted case studies including with and without process enactment data in a small software development company. We preferred machine learning approaches rather than statistical ones, in order to cluster the data which includes process enactment informationsince we believed that they are convenient with the pattern oriented nature of the data. By the case studies performed, we obtained promising results. We evaluated performance values of prediction models to demonstrate the advantage of using process enactment data for the prediction of defect open duration value. When we have enough data points to apply machine learning methods and the data can be clusteredhomogeneously, we observed approximately 3% (ranging from -10% to %17) more accurate results from analyses including with process enactment data than the without ones. Keywords:

Training is a powerful and required method to equip human resources with tools to keep their organizations competitive in the markets. Typically at the end of class, trainees are asked to give their feelings about or satisfaction with the training. Although there are various reasons for conducting training evaluations, the common theme is the need to continuously improve a training program in the future. Among training evaluation methods, post-training surveys or questionnaires are the most commonly used way to get trainees’ reaction about the training program and “the forms will tell you to what extent you’ve been successful.” (Kirkpatrick 2006) A higher satisfaction score means more trainees were satisfied with the training. A total of 40 prediction models grouped into 10-GIQs prediction models and 6-GIQs prediction models were built in this work to predict the total training satisfaction based on trainees’ general information which included a trainee’s desire to take training, a trainee’s attitude in training class and other information related to the trainee’s work environment and other characteristics. The best models selected from 10-GIQs and 6-GIQs prediction models performed the prediction work with the prediction quality of PRED (0.15) >= 99% and PRED (0.15) >= 98%, separately. An interesting observation discovered in this work is that the training satisfaction could be predicted based on trainees information that was not related to any training experience at all. The dominant factors on training satisfaction were the trainee’s attitude in training class and the trainee’s desire to take the training which was found in 10-GIQs prediction models and 6-GIQs prediction models, separately. / text

Background: A key idea of feature orientation is to decompose a software product line along the features it provides. Feature decomposition is orthogonal to object-oriented decomposition it crosscuts the underlying package and class structure. It has been argued often that feature decomposition improves system structure (reduced coupling, increased cohesion). However, recent empirical findings suggest that this is not necessarily the case, which is the motivation for our empirical investigation. Aim: In fact, there is little empirical evidence on how the alternative decompositions of feature orientation and object orientation compare to each other in terms of their association with observable properties of system structure (coupling, cohesion). This motivated us to empirically investigate and compare the properties of three decompositions (object-oriented, feature-oriented, and their intersection) of 28 feature-oriented software product lines. Method: In an exploratory, observational study, we quantify internal attributes, such as import coupling and cohesion, to describe and analyze the different decompositions of a feature-oriented product line in a systematic, reproducible, and comparable manner. For this purpose, we use three established software measures (CBU, IUD, EUD) as well as standard distribution statistics (e.g., Gini coefficient). Results: First, feature decomposition is associated with higher levels of structural coupling in a product line than a decomposition into classes. Second, although coupling is concentrated in feature decompositions, there are not necessarily hot-spot features. Third, the cohesion of feature modules is not necessarily higher than class cohesion, whereas feature modules serve more dependencies internally than classes. Fourth, coupling and cohesion measurement show potential for sampling optimization in complex static and dynamic product-line analyses (product-line type checking, feature-interaction detection). Conclusions: Our empirical study raises critical questions about alleged advantages of feature decomposition. At the same time, we demonstrate how the measurement of structural attributes can facilitate static and dynamic analyses of software product lines. (authors' abstract) / Series: Technical Reports / Institute for Information Systems and New Media

Background: A key idea of feature orientation is to decompose a software product line along the features it provides. Feature decomposition is orthogonal to object-oriented decomposition it crosscuts the underlying package and class structure. It has been argued often that feature decomposition improves system structure (reduced coupling, increased cohesion). However, recent empirical findings suggest that this is not necessarily the case, which is the motivation for our empirical investigation. Aim: In fact, there is little empirical evidence on how the alternative decompositions of feature orientation and object orientation compare to each other in terms of their association with observable properties of system structure (coupling, cohesion). This motivated us to empirically investigate and compare the properties of three decompositions (object-oriented, feature-oriented, and their intersection) of 28 feature-oriented software product lines. Method: In an exploratory, observational study, we quantify internal attributes, such as import coupling and cohesion, to describe and analyze the different decompositions of a feature-oriented product line in a systematic, reproducible, and comparable manner. For this purpose, we use three established software measures (CBU, IUD, EUD) as well as standard distribution statistics (e.g., Gini coefficient). Results: First, feature decomposition is associated with higher levels of structural coupling in a product line than a decomposition into classes. Second, although coupling is concentrated in feature decompositions, there are not necessarily hot-spot features. Third, the cohesion of feature modules is not necessarily higher than class cohesion, whereas feature modules serve more dependencies internally than classes. Fourth, coupling and cohesion measurement show potential for sampling optimization in complex static and dynamic product-line analyses (product-line type checking, feature-interaction detection). Conclusions: Our empirical study raises critical questions about alleged advantages of feature decomposition. At the same time, we demonstrate how the measurement of structural attributes can facilitate static and dynamic analyses of software product lines. (authors' abstract) / Series: Technical Reports / Institute for Information Systems and New Media

O desenvolvimento de sistemas com eficácia, eficiência e satisfação dos usuários tem feito com que a usabilidade se torne uma característica importante na avaliação de qualidade de um produto de software. A análise da interação do usuário com o sistema é uma das formas de mensurar essa característica. Novas tecnologias permitem a criação de sistemas com foco na qualidade de interação do usuário, com grande parte do processamento ocorrendo no lado cliente, como as Aplicações Internet Ricas ou simplesmente RIAs, de Rich Internet Applications. No entanto, os dados de interação do usuário armazenados no servidor web são insuficientes para extrair conhecimento útil sobre a qualidade da interação. Este trabalho apresenta uma abordagem para avaliação automática de usabilidade através da aplicação de clustering e métricas na análise de log de RIAs. A abordagem proposta utiliza a Web Application Usage Tracking Tool, WAUTT, para capturar a interação do usuário e o algoritmo X-Means para realizar o agrupamento dos dados. O resultado da avaliação automática emprega métricas que fornecem informação quantitativa a respeito da usabilidade de sistemas web e que poderão ser utilizadas pelo avaliador para auxiliar na tomada de decisão. As informações obtidas com as métricas foram comparadas a um método de avaliação tradicional, a avaliação heurística, para corroborar os resultados obtidos pela abordagem proposta. O clustering foi uma técnica útil para reduzir o volume de dados e permitira ao avaliador concentrar os seus esforços em determinados grupos de usuários com comportamentos semelhantes. A aplicação de métricas aos clusters permitiu realizar uma avaliação de usabilidade quantitativa para auxiliar a tomada de decisão em relação a algumas das subcaracterísticas de usabilidade. A avaliação automática de usabilidade realizada tem potencial para auxiliar no desenvolvimento de sistemas web. / The development of systems with effectiveness, efficiency and user satisfaction has made that usability become an important feature in quality assessment of software products. The analysis of user interaction data with the system is one way to measure this feature. New technologies allow the creation of systems with focus on quality of user interaction and a large part of the processing occurs on the client side, as Rich Internet Applications, from RIAs for short. However, user interaction data stored on the webserver are insufficient to extract useful knowledge about the quality of interaction. This dissertation presents an approach for automatic usability evaluation by applying clustering and metrics in log analysis of RIAs. The proposed approach uses the Web Application Usage Tracking Tool, WAUTT, to capture user interaction and the X-means algorithm to perform clustering. The result of the automatic evaluation applies metrics that provide quantitative information about the usability of web systems and may be used to assist evaluators in making decisions. Information obtained from metrics were compared to a traditional evaluation method, heuristic evaluation, to corroborate the results obtained by the proposed approach. Clustering was a useful technique to reduce the volume of data and allowed the evaluator focus their efforts on certain groups of users with similar behaviors. The application of metrics enabled perform a quantitative usability evaluation to assist the decision making process about some usability subcharacteristics. The automatic usability evaluation conducted as the proposed approach has the potential to assist in developing web systems.

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.

[pt] Diversas tecnologias de implementação de software são discutidas na literatura. Duas dessas tecnologias são a orientação a objetos, que se encontra consolidada, e a orientação a agentes, que vem sendo objeto de muitos estudos e experimentos. Esses estudos indicam a orientação a agentes como muito promissora e como uma evolução da orientação a objetos. No entanto, há poucos trabalhos comparando essas duas técnicas e os poucos trabalhos se baseiam em comparações ideológicas e qualitativas. Essa dissertação tem por objetivo desenvolver e avaliar modos sistemáticos de avaliação de duas arquiteturas de implementação de sistemas. As duas tecnologias apresentadas foram comparadas e foi determinado se a utilização de uma tecnologia trouxe benefícios, desvantagens ou foi indiferente face à outra. A comparação foi realizada tomando por base um problema real, ou seja, foram criadas duas implementações que solucionam o problema de modo similar cada uma usando uma tecnologia. Para o desenvolvimento desse trabalho foi criado um plano de medição com base na técnica Goal Question Metric. O plano de medição foi aplicado às duas implementações e resultados obtidos foram avaliados definindo os benefícios de cada técnica. Por fim, foi feita uma crítica da utilização do modelo GQM em um projeto real. / [en] There are several software development technologies currently in the literature. Two such technologies are object orientation, which is consolidated, and agent orientation, which has been the subject of many studies and experiments. These studies indicate the agent orientation as very promising and an evolution of object orientation. However, there is only a few studies comparing these two techniques and these studies have been based on ideological and qualitative comparisons. This dissertation aims to develop and evaluate methods of systematic evaluation of two architectures for implementing systems. The two technologies presented were compared and determined whether the use of technology has brought benefits, disadvantages or was indifferent to the other. The comparison was performed based on taking a real problem; in other words, two implementations have been created that address the problem similarly each using a technology. To develop this work, it was created a measurement plan based on the technique Goal Question Metric. The measurement plan was applied to both implementations and results were evaluated by defining the benefits of each technique. Finally was done a discussion about the use of the GQM model in a real project.