Tests are important artifacts in the software development process. Testing activities such as test automation, test maintenance, and test suite optimization mainly rely on an in-depth understanding of test specifications. The manual process of writing testspecifications in natural language can create many different quality issues such as ambiguous, incomplete, redundant, or inconsistent test cases. Nowadays, the concept of test smells is proposed by several researchers to be used as indicators of low-qualityattributes in test specifications. Quality assurance processes for test specifications often rely on manual reviews to detect these smells. The manual process of detecting these smells is considered time consuming and costly. However, there is currently no work that implements a comprehensive quality model that classifies and identifies these smells by using a systematic strategy. As a result, there is a need for machine-supported analytical measures that decrease the time and effort needed to detect these smells manually, especially when it comes to reviewing and validating large test specifications.This study aims to investigate which natural language smell metrics implemented in NALABS can be found in test specifications and to measure the sufficiency of those smellmetrics. It also aims to extend these smell metrics by exploring, proposing, or combining with new bad smell metrics to cover more aspects of natural language test quality. The results of the study show that the smell metrics exists in real-world test specifications and can uncover many potential quality issues by assisting test designers in identifying certain types of quality issues pertaining to for example the understandability and complexity of test specifications. Moreover, the results show thatthe list of smell metrics implemented in NALABS is incomplete and can be extended to cover more aspects of test quality.

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Submitted by Diogo Barreiros (diogo.barreiros@ufba.br) on 2017-06-08T11:28:18Z No. of bitstreams: 1 Dissertação Mydiã_Freitas.pdf: 3038925 bytes, checksum: 799df53dc64e5b455ed52bb760695ae2 (MD5) / Approved for entry into archive by Vanessa Reis (vanessa.jamile@ufba.br) on 2017-06-12T15:16:18Z (GMT) No. of bitstreams: 1 Dissertação Mydiã_Freitas.pdf: 3038925 bytes, checksum: 799df53dc64e5b455ed52bb760695ae2 (MD5) / Made available in DSpace on 2017-06-12T15:16:18Z (GMT). No. of bitstreams: 1 Dissertação Mydiã_Freitas.pdf: 3038925 bytes, checksum: 799df53dc64e5b455ed52bb760695ae2 (MD5) / Code smell é definido como um potencial problema de design localizado em determinada parte do código fonte de um sistema de software e pode indicar deficiências no design que podem influenciar a facilidade de manutenção, facilidade de teste e confiabilidade do software. Um bom exemplo de code smell que vai de encontro aos princípios do bom design definido na programação orientada a objetos é o Shotgun Surgery, que corresponde a classes cuja modificação implica em muitas pequenas alterações em muitas outras classes. Quando as modificações estão espalhadas, elas são difíceis de serem encontradas. Como resultado, é fácil perder uma mudança importante, causando assim, problemas na manutenção do sistema. A atividade de identificação de code smells é analisada e confirmada pelo próprio programador ou um revisor independente, contudo, a detecção manual de code smells por meio de inspeções de código consume muito tempo e é pouco escalável. Ferramentas que auxiliam a identificação de code smells têm sido bastante utilizadas em diversos estudos. Neste contexto, esta dissertação propõe investigar se a detecção automática de code smells por meio de ferramentas é considerada útil pelos desenvolvedores como forma de avaliar a qualidade do design de sistemas de software, principalmente em termos de facilidade de manutenção. Realizamos três estudos: sendo um estudo preliminar e dois estudos experimentais similares. O objetivo do estudo preliminar era nos auxiliar a perceber e corrigir problemas que pudessem surgir no decorrer do desenvolvimento dos estudos experimentais. O objetivo desses estudos era investigar a qualidade do design de sistemas de softwares e code smells através do uso de ferramentas de detecção. Os resultados desses estudos indicam que existe relação entre os code smells God Class, Data Class, Shotgun Surgery, Refused Bequest e Feature Envy com problemas de design associados a dificuldades no processo de manutenção de sistemas de softwares.

This study provides a critical analysis of refactoring by surveying the refactoring tools in IDEA and Eclipse. Ways are discussed to locate targets for refactorings, via detection of code smells from static code analysis in IDEA and during the compilation process in Eclipse. New code smells are defined as well as the refactorings needed to remove the code smells. The impacts the code smells have on design are well documented. Considerable effort is made to describe how these code smells and their refactorings can be used to improve design. Practical methods are provided to detect code smells in large projects such as Sun’s JDK. The methodology includes a classification scheme to categorise code smells by their value and complexity to handle large projects more efficiently. Additionally a detailed analysis is performed on the evolution of the JDK from a maintainability point of view. Code smells are used to measure maintainability in this instance. / Dissertation (MSc (Computer Science))--University of Pretoria, 2008. / Computer Science / unrestricted

Code anomalies, also known as code smells, are any characteristics in software code that indicate amore severe problem exists deep in the code. These anomalies do not always prevent a system fromfunctioning, but they can restrict development and increase the difficulty of maintaining the software.The idea of code anomalies in conventional software is the subject of many research papers. However,very few explicitly examine web application anomalies and offer solutions to web applicationanomalies. Additionally, there aren't enough studies looking at whether anomalies found inconventional software systems can also be found in web applications. Web application code anomaliesmay potentially differ from traditional software systems in a few ways. For instance, web applicationshave a client-server architecture that can create unique challenges for communication between theclient and server. This may result in code anomalies that relate to network delays or resource-intensiveoperations. Additionally, web applications often rely on third-party libraries and frameworks, whichcan introduce additional code anomalies. This study aims to fill the gaps mentioned above byinvestigating code anomalies in web applications using a systemic mapping study. This study usessystematic mapping to collect and analyze literature through predefined criteria and procedures.Furthermore, this study provides an overview of approaches and tools that can identify and detectanomalies, determine where code anomalies occur, and whether refactoring has been considered. Theresults of this study show that there’s a wide array of techniques to detect anomalies, code anomaliesoccur everywhere. Refactoring is a technique to solve code anomalies and while there are alreadymany refactoring techniques cataloged for traditional software, there is a lack of refactoringsspecifically cataloged for web applications.

An approach using dot plots as an aid to visualizing smells within Java source files is presented. Dot plots are a visual tool that allows for viewing duplication in a document or text string. Our approach uses a plug-in for the Eclipse Java IDE to convert Java source files into dot plots. The goal here is to find problem areas in the code, known as "Code Smells", that could indicate that the source file needs to be modified or refactored. In the dot plot these problem areas appear as sections that contain interesting dot formations. Color is also used to enhance places of the dot plot that could be important. Duplication is a common problem in source code and also an important Code Smell. We will show that through finding the Duplicate Code smell we will also be able to find other code smells creating a plug-in that a programmer can use during the coding process to help improve code design.

Submitted by Mayara Nascimento (mayara.nascimento@ufba.br) on 2016-05-31T14:36:19Z No. of bitstreams: 1 DissertaçãoMestrado - Luciana Lins versão completa (1) 22.12.15.pdf: 3112045 bytes, checksum: 6d585e19435cc700b532cd4aed755f85 (MD5) / Approved for entry into archive by Alda Lima da Silva (sivalda@ufba.br) on 2016-06-03T23:25:31Z (GMT) No. of bitstreams: 1 DissertaçãoMestrado - Luciana Lins versão completa (1) 22.12.15.pdf: 3112045 bytes, checksum: 6d585e19435cc700b532cd4aed755f85 (MD5) / Made available in DSpace on 2016-06-03T23:25:31Z (GMT). No. of bitstreams: 1 DissertaçãoMestrado - Luciana Lins versão completa (1) 22.12.15.pdf: 3112045 bytes, checksum: 6d585e19435cc700b532cd4aed755f85 (MD5) / A revisão sistemática é um recurso importante para a engenharia de software baseada em evidências, que consiste em uma forma de síntese dos resultados de pesquisas primárias relacionados com um problema específico. O presente trabalho tem como objetivo apresentar um método refinado de síntese temática em Engenharia de Software com base na proposta de Cruzes e Dyba [20]. O método foi testado na análise qualitativa de um conjunto de estudos primários provenientes de uma revisão sistemática sobre o tema Code Smells. Os principais resultados são a apresentação passos que compõem o método adotado, lições aprendidas, principais dificuldades durante o processo, bem como as descobertas relacionadas aos resultados obtidos para o tema analisado.

abstract: Research has shown that the ability to smell is the most direct sense an individual can experience. With every breath a person takes, the brain recognizes thousands of molecules and makes connections with our memories to determine their composition. With the amount of research looking into how and why we smell, researchers still have little understanding of how the nose and brain process an aroma, and how emotional and physical behavior is impacted. This research focused on the affects smell has on a caregiver in a simulated Emergency Department setting located in the SimET of Banner Good Samaritan Medical Center in Phoenix, Arizona. The study asked each participant to care for a programmed mannequin, or "patient", while performing simple computer-based tasks, including memory and recall, multi-tasking, and mood-mapping to gauge physical and mental performance. Three different aromatic environments were then introduced through diffusion and indirect inhalation near the participants' task space: 1) a control (no smell), 2) an odor (simulated dirty feet), and 3) an aroma (one of four true essential oils plus a current odor-eliminating compound used in many U.S. Emergency Departments). This study was meant to produce a stressful environment by leading the caregiver to stay in constant movement throughout the study through timed tasks, uncooperative equipment, and a needy "patient". The goal of this research was to determine if smells, and of what form of pleasantness and repulsiveness, can have an effect on the physical and mental performance of emergency caregivers. Findings from this study indicated that the "odor eliminating" method currently used in typical Emergency Departments, coffee grounds, is more problematic than helpful, and the introduction of true essential oils may not only reduce stress, but increase efficiency and, in turn, job satisfaction. / Dissertation/Thesis / M.S.D. Design 2013

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