A systematic literature review on the code smells datasets and validation mechanisms

The accuracy reported for code smell-detecting tools varies depending on the dataset used to evaluate the tools. Our survey of 45 existing datasets reveals that the adequacy of a dataset for detecting smells highly depends on relevant properties such as the size, severity level, project types, number of each type of smell, number of smells, and the ratio of smelly to non-smelly samples in the dataset. Most existing datasets support God Class, Long Method, and Feature Envy while six smells in Fowler and Beck's catalog are not supported by any datasets. We conclude that existing datasets suffer from imbalanced samples, lack of supporting severity level, and restriction to Java language.Comment: 34 pages, 10 figures, 12 tables, Accepte

Software product quality metrics : a systematic mapping study

In the current competitive world, producing quality products has become a prominent factor to succeed in business. In this respect, defining and following the software product quality metrics (SPQM) to detect the current quality situation and continuous improvement of systems have gained tremendous importance. Therefore, it is necessary to review the present studies in this area to allow for the analysis of the situation at hand, as well as to enable us to make predictions regarding the future research areas. The present research aims to analyze the active research areas and trends on this topic appearing in the literature during the last decade. A Systematic Mapping (SM) study was carried out on 70 articles and conference papers published between 2009 and 2019 on SPQM as indicated in their titles and abstract. The result is presented through graphics, explanations, and the mind mapping method. The outputs include the trend map between the years 2009 and 2019, knowledge about this area and measurement tools, issues determined to be open to development in this area, and conformity between conference papers, articles and internationally valid quality models. This study may serve as a foundation for future studies that aim to contribute to the development in this crucial field. Future SM studies might focus on this subject for measuring the quality of network performance and new technologies such as Artificial Intelligence (AI), Internet of things (IoT), Cloud of Things (CoT), Machine Learning, and Robotics.publishedVersio

30 Years of Software Refactoring Research: A Systematic Literature Review

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

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

Explainable, Security-Aware and Dependency-Aware Framework for Intelligent Software Refactoring

As software systems continue to grow in size and complexity, their maintenance continues to become more challenging and costly. Even for the most technologically sophisticated and competent organizations, building and maintaining high-performing software applications with high-quality-code is an extremely challenging and expensive endeavor. Software Refactoring is widely recognized as the key component for maintaining high-quality software by restructuring existing code and reducing technical debt. However, refactoring is difficult to achieve and often neglected due to several limitations in the existing refactoring techniques that reduce their effectiveness. These limitation include, but not limited to, detecting refactoring opportunities, recommending specific refactoring activities, and explaining the recommended changes. Existing techniques are mainly focused on the use of quality metrics such as coupling, cohesion, and the Quality Metrics for Object Oriented Design (QMOOD). However, there are many other factors identified in this work to assist and facilitate different maintenance activities for developers: 1. To structure the refactoring field and existing research results, this dissertation provides the most scalable and comprehensive systematic literature review analyzing the results of 3183 research papers on refactoring covering the last three decades. Based on this survey, we created a taxonomy to classify the existing research, identified research trends and highlighted gaps in the literature for further research. 2. To draw attention to what should be the current refactoring research focus from the developers’ perspective, we carried out the first large scale refactoring study on the most popular online Q&A forum for developers, Stack Overflow. We collected and analyzed posts to identify what developers ask about refactoring, the challenges that practitioners face when refactoring software systems, and what should be the current refactoring research focus from the developers’ perspective. 3. To improve the detection of refactoring opportunities in terms of quality and security in the context of mobile apps, we designed a framework that recommends the files to be refactored based on user reviews. We also considered the detection of refactoring opportunities in the context of web services. We proposed a machine learning-based approach that helps service providers and subscribers predict the quality of service with the least costs. Furthermore, to help developers make an accurate assessment of the quality of their software systems and decide if the code should be refactored, we propose a clustering-based approach to automatically identify the preferred benchmark to use for the quality assessment of a project. 4. Regarding the refactoring generation process, we proposed different techniques to enhance the change operators and seeding mechanism by using the history of applied refactorings and incorporating refactoring dependencies in order to improve the quality of the refactoring solutions. We also introduced the security aspect when generating refactoring recommendations, by investigating the possible impact of improving different quality attributes on a set of security metrics and finding the best trade-off between them. In another approach, we recommend refactorings to prioritize fixing quality issues in security-critical files, improve quality attributes and remove code smells. All the above contributions were validated at the large scale on thousands of open source and industry projects in collaboration with industry partners and the open source community. The contributions of this dissertation are integrated in a cloud-based refactoring framework which is currently used by practitioners.Ph.D.College of Engineering & Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/171082/1/Chaima Abid Final Dissertation.pdfDescription of Chaima Abid Final Dissertation.pdf : Dissertatio

Quantifying the psychological properties of words

This thesis explores the psychological properties of words – the idea that words carry links to additional information beyond their dictionary meaning. It does so by presenting three distinct publications and an applied project, the Macroscope. The published research respectively covers: the modelling of language networks to explain lexical growth; the use of high dimensional vector representations of words to discuss language learning; and the collection of a normative dataset of single word humour ratings. The first publication outlines the use of network science in psycholinguistics. The methodology is discussed, providing clear guidelines on the application of networks when answering psychologically motivated questions. A selection of psychological studies is presented as a demonstration of use cases for networks in cognitive psychology. The second publication uses referent feature norms to represent words in a high dimensional vector space. A correlative link between referent distinctiveness and age of acquisition is proposed. The shape bias literature (the idea that children only pay attention to the shape of objects early on) is evaluated in relation to the findings. The third publication collects and shares a normative dataset of single word humour ratings. Descriptive properties of the dataset are outlined and the potential future use in the field of humour is discussed. Finally, the thesis presents the Macroscope, a collaborative project put together with Li Ying. The Macroscope is an online platform, allowing for easy analysis of the psychological properties of target words. The platform is showcased, and its full functionality is presented, including visualisation examples. Overall, the thesis aims to give researchers all that’s necessary to start working with psychological properties of words – the understanding of network science in psycholinguistics, high dimensional vector spaces, normative datasets and the applied use of all the above through the Macroscope

Consumer brand relationships: the determinants of brand loyalty in the context of football clubs

The present research resides within the field of consumer brand relationships and is grounded in the Service dominant logic (S-D logic) marketing stance as framework. Following the realisation of a lack of works in this novel marketing approach addressing the area of emotions with service brands, the present research aims to fill this gap by achieving a more comprehensive knowledge of the underlying components responsible for the occurrence of brand loyalty with emotion-laden brands, and for the emotional consequences and attitudes the supporters of the brand are faced with. This was addressed by following an exploratory approach on a single industry (i.e. football) in the European context. Where, the primary unit of analysis of this research is the individual as a resource integrator/beneficiary as part of a wider social network engaged with the brand. Integrating the emerging view on consumer brand relationship theory where brands are dynamic and actively co-created entities that evolve with consumers and cultures in kind (Allen et al., 2008) and in line with theoretical framework of this research, S-D logic. Therefore, a bibliometric study was initially carried out on the S-D logic literature, followed by a critical review of the research areas that underpinned this research, which collectively defined the implementation of the subsequent research stages. Resulting in a mix methods approach, comprising of a qualitative study with 46 interviews on three Portuguese football clubs and a quantitative study with 842 respondents across six European countries. A service brand model is proposed where brand loyalty is built from the interaction of the five constructs identified (brand associations, involvement, satisfaction, emotional attachment, and trust), with emotional attachment representing a crucial construct. Providing brand managers, the knowledge on how to improve the level of relationship between the organisation and its consumers. Moreover, this research brings to the forefront of S-D logic research the consumer brand relationship realm, more specifically the concept of emotions with service brands.O presente estudo integra-se na teoria dos relacionamentos do consumidor com a marca, tendo a lógica dominante de serviço (lógica D-S) como enquadramento. Dado que existe uma escassez de estudos relativamente às emoções para com as marcas de serviço nesta singular abordagem do marketing, o presente estudo pretende reduzir esta lacuna através da aquisição de um conhecimento mais abrangente dos componentes responsáveis pelo surgimento da lealdade para com marcas de cariz emocional, e que contribuem para níveis emocionais mais elevados em termos das atitudes e consequências dai resultantes para os apoiantes da marca. Estes aspetos foram considerados seguindo uma abordagem exploratória numa única industria, a do futebol num contexto europeu. Onde a principal unidade de analise desta pesquisa é o individuo como integrador/beneficiário envolvido com a marca, fazendo parte de uma network social mais abrangente. Incorporando a perspetiva emergente na teoria de relacionamento do consumidor com a marca onde as marcas são dinâmicas e são entidades cocriadas que evolvem com os consumidores e suas culturas (Allen et al., 2008) em linha com o enquadramento teórico desta pesquisa, lógica D-S. Consequentemente, um estudo bibliométrico da literatura referente à lógica dominante de serviço foi conduzido numa primeira fase, seguido de uma revisão critica das áreas de pesquisas que integram esta pesquisa, definindo a implementação das etapas de pesquisa subsequentes. Resultando numa abordagem de métodos mistos, correspondente a um estudo qualitativo com 46 entrevistas referentes a três clubes Portugueses de futebol e um estudo quantitativo com 842 inquiridos em seis países Europeus. Um modelo de marca de serviço é proposto onde a lealdade à marca é construída com base na interação de cinco construtos identificados (associações à marca, envolvimento, satisfação, ligação emocional, e confiança), de onde a ligação emocional se evidencia como um construto crucial. Permitindo aos gestores de marcas o conhecimento de como incrementar o nível de relacionamento entre a organização e os seus consumidores. Acresce o facto de que esta pesquisa salienta a relevância empírica da área de relacionamento do consumidor com a marca, em particular o conceito das emoções com marcas de serviço, na literatura referente à logica dominante de serviço

Trust in Robots

Robots are increasingly becoming prevalent in our daily lives within our living or working spaces. We hope that robots will take up tedious, mundane or dirty chores and make our lives more comfortable, easy and enjoyable by providing companionship and care. However, robots may pose a threat to human privacy, safety and autonomy; therefore, it is necessary to have constant control over the developing technology to ensure the benevolent intentions and safety of autonomous systems. Building trust in (autonomous) robotic systems is thus necessary. The title of this book highlights this challenge: “Trust in robots—Trusting robots”. Herein, various notions and research areas associated with robots are unified. The theme “Trust in robots” addresses the development of technology that is trustworthy for users; “Trusting robots” focuses on building a trusting relationship with robots, furthering previous research. These themes and topics are at the core of the PhD program “Trust Robots” at TU Wien, Austria

Effects of Diversity and Neuropsychological Performance in an NFL Cohort

Objective: The aim of this study was to examine the effect of ethnicity on neuropsychological test performance by comparing scores of white and black former NFL athletes on each subtest of the WMS. Participants and Methods: Data was derived from a de-identified database in South Florida consisting of 63 former NFL white (n=28, 44.4%) and black (n=35, 55.6%) athletes (Mage= 50.38; SD= 11.57). Participants completed the following subtests of the WMS: Logical Memory I and II, Verbal Paired Associates I and II, and Visual Reproduction I and II. Results: A One-Way ANOVA yielded significant effect between ethnicity and performance on several subtests from the WMS-IV. Black athletes had significantly lower scores compared to white athletes on Logical Memory II: F(1,61) = 4.667, p= .035, Verbal Paired Associates I: F(1,61) = 4.536, p = .037, Verbal Paired Associates: II F(1,61) = 4.677, p = .034, and Visual Reproduction I: F(1,61) = 6.562, p = .013. Conclusions: Results suggest significant differences exist between white and black athletes on neuropsychological test performance, necessitating the need for proper normative samples for each ethnic group. It is possible the differences found can be explained by the psychometric properties of the assessment and possibility of a non-representative sample for minorities, or simply individual differences. Previous literature has found white individuals to outperform African-Americans on verbal and non-verbal cognitive tasks after controlling for socioeconomic and other demographic variables (Manly & Jacobs, 2002). This highlights the need for future investigators to identify cultural factors and evaluate how ethnicity specifically plays a role on neuropsychological test performance. Notably, differences between ethnic groups can have significant implications when evaluating a sample of former athletes for cognitive impairment, as these results suggest retired NFL minorities may be more impaired compared to retired NFL white athletes