9,296 research outputs found

    A systematic literature review on source code similarity measurement and clone detection: techniques, applications, and challenges

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    Measuring and evaluating source code similarity is a fundamental software engineering activity that embraces a broad range of applications, including but not limited to code recommendation, duplicate code, plagiarism, malware, and smell detection. This paper proposes a systematic literature review and meta-analysis on code similarity measurement and evaluation techniques to shed light on the existing approaches and their characteristics in different applications. We initially found over 10000 articles by querying four digital libraries and ended up with 136 primary studies in the field. The studies were classified according to their methodology, programming languages, datasets, tools, and applications. A deep investigation reveals 80 software tools, working with eight different techniques on five application domains. Nearly 49% of the tools work on Java programs and 37% support C and C++, while there is no support for many programming languages. A noteworthy point was the existence of 12 datasets related to source code similarity measurement and duplicate codes, of which only eight datasets were publicly accessible. The lack of reliable datasets, empirical evaluations, hybrid methods, and focuses on multi-paradigm languages are the main challenges in the field. Emerging applications of code similarity measurement concentrate on the development phase in addition to the maintenance.Comment: 49 pages, 10 figures, 6 table

    Japanese Expert Teachers' Understanding of the Application of Rhythm in Judo: a New Pedagogy

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    Aim The aim of this research is to understand the application of rhythm in judo through the experience of expert Japanese coaches. Background Scientists and experienced coaches agree rhythm is an important skill in people’s everyday life. There is currently no research that investigates the importance of rhythm in judo. People with a highly developed sense of rhythm, move properly, breathe properly, or begin and finish work at the right time. Where sport is concerned, motion and dance can play an important role not only in the improvement of performance, but also in the reduction, or even prevention of, injuries. Those who are naturally musically inclined (have a musical ear) may find they can improve their technique faster than others, and this is something that, by investigating the way expert coaches understand the application of rhythm in judo, this research seeks to understand. As Lange, (1970) stated, factors of movement are ‘weight, space, time, and flow on the background of the general flux of movement in proportional arrangements’ (Bradley, 2008; Selioni, 2013; Youngerman, 1976), therefore, this research will investigate the interaction of body and mind. Dance training as well as judo are somatic experiences that have as their ultimate goal the attainment of a skilled body. With quality training an athlete gains an increased awareness of their body which leads to better control of movement and is very important for judo athletes. This training is found in Japanese kabuki dance (Hahn, 2007), the Greek syrtaki dance (Zografou & Pateraki, 2007), and in walking techniques used in the traditional and Olympic sports of Japanese judo and Greek wrestling. Methods Interpretative phenomenological analysis (IPA) was the most suitable data analysis approach for this study for a number of reasons, mainly because it was considered to most closely reflect the author's realist epistemological view. The idiographic approach and framework, particularly on IPA, was regarded as a useful framework in which the current topic could meaningfully be explored. As this study is one of the first to explore this new thematic area, IPA was the preferred approach to address the goal of providing a detailed account of the expert’s experience. Therefore, semi-structured interviews were used as a data source. This is the most conventional form of data collection using IPA and most closely reflects the researcher-participant relationship. Semi-structured interviews provide considerable flexibility by allowing the researcher to be guided by the phenomena of interest to the participant. In this study, purposive sampling was achieved using inclusion criteria pertaining to the research question. Using the ranking system criteria based on the belt in combination with age employed by the International Judo Federation (IJF) and Kodokan Judo Institute, six expert coaches of forty years old and over with a minimum belt rank of 6th dan were selected as a sample. Results Both interviews and the codification process contributed to new findings regarding the application of rhythm to judo, and judo itself as a pedagogical tool. The diagrammatic model can be considered a 'guideline' to the phenomena deemed most significant. The personal significance of rhythm in judo was evidenced by the frequency with which the interviewees naturally referred to it during the interviews. A number of interviewees said that it was important for rhythm to be second nature. Rhythm was also described as an integrated and representative element in the context of training. This framework was seen as essential in providing the reader with a contextualised understanding of the phenomena considered most important for the current research. Interviewees reported various motives for employing training in rhythm such as faster technical development, better attack/defence, fitness, speed, skills acquisition, personal and spiritual growth, competition results. Conclusions This study offers first-hand accounts from professional coaches of a previously unknown phenomena, namely the use of rhythm in judo, and sheds insight on how judo experts understand rhythm in terms of training, competition, and personal growth. These findings suggest that outside of training, coaches play an important role in teaching, mentoring, and leading students. In conclusion, the research revealed four important points which form the basis of a new method of teaching judo: pedagogy, skills, rhythm and movement

    Towards A Practical High-Assurance Systems Programming Language

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    Writing correct and performant low-level systems code is a notoriously demanding job, even for experienced developers. To make the matter worse, formally reasoning about their correctness properties introduces yet another level of complexity to the task. It requires considerable expertise in both systems programming and formal verification. The development can be extremely costly due to the sheer complexity of the systems and the nuances in them, if not assisted with appropriate tools that provide abstraction and automation. Cogent is designed to alleviate the burden on developers when writing and verifying systems code. It is a high-level functional language with a certifying compiler, which automatically proves the correctness of the compiled code and also provides a purely functional abstraction of the low-level program to the developer. Equational reasoning techniques can then be used to prove functional correctness properties of the program on top of this abstract semantics, which is notably less laborious than directly verifying the C code. To make Cogent a more approachable and effective tool for developing real-world systems, we further strengthen the framework by extending the core language and its ecosystem. Specifically, we enrich the language to allow users to control the memory representation of algebraic data types, while retaining the automatic proof with a data layout refinement calculus. We repurpose existing tools in a novel way and develop an intuitive foreign function interface, which provides users a seamless experience when using Cogent in conjunction with native C. We augment the Cogent ecosystem with a property-based testing framework, which helps developers better understand the impact formal verification has on their programs and enables a progressive approach to producing high-assurance systems. Finally we explore refinement type systems, which we plan to incorporate into Cogent for more expressiveness and better integration of systems programmers with the verification process

    Designing a Direct Feedback Loop between Humans and Convolutional Neural Networks through Local Explanations

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    The local explanation provides heatmaps on images to explain how Convolutional Neural Networks (CNNs) derive their output. Due to its visual straightforwardness, the method has been one of the most popular explainable AI (XAI) methods for diagnosing CNNs. Through our formative study (S1), however, we captured ML engineers' ambivalent perspective about the local explanation as a valuable and indispensable envision in building CNNs versus the process that exhausts them due to the heuristic nature of detecting vulnerability. Moreover, steering the CNNs based on the vulnerability learned from the diagnosis seemed highly challenging. To mitigate the gap, we designed DeepFuse, the first interactive design that realizes the direct feedback loop between a user and CNNs in diagnosing and revising CNN's vulnerability using local explanations. DeepFuse helps CNN engineers to systemically search "unreasonable" local explanations and annotate the new boundaries for those identified as unreasonable in a labor-efficient manner. Next, it steers the model based on the given annotation such that the model doesn't introduce similar mistakes. We conducted a two-day study (S2) with 12 experienced CNN engineers. Using DeepFuse, participants made a more accurate and "reasonable" model than the current state-of-the-art. Also, participants found the way DeepFuse guides case-based reasoning can practically improve their current practice. We provide implications for design that explain how future HCI-driven design can move our practice forward to make XAI-driven insights more actionable.Comment: 32 pages, 6 figures, 5 tables. Accepted for publication in the Proceedings of the ACM on Human-Computer Interaction (PACM HCI), CSCW 202

    Classification system for nanotechnology-enabled health products with both scientific and regulatory application

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    The lack of specific regulatory guidelines for nanotechnology-enabled health products (NHPs) is hampering development and patient access to these innovative technologies. Namely, there is an urgent need for harmonized regulatory definitions and classification systems that allow establishing a standardized framework for NHPs regulatory assessment. In this work, a novel classification system for NHPs is proposed. This classification can be applied for sorting nano-based innovations and regulatory guidelines according to the type of NHPs they address. Said methodology combines scientific and regulatory principles and it is based on the following criteria: principal mode of action, chemical composition, medical purpose and nanomanufacturing approach. This classification system could serve as a useful tool to sensor the state of the art of NHPs which is particularly useful for regulators to support strategy development of regulatory guidelines. Additionally, this tool would also allow manufacturers of NHPs to align their development plans with their applicable guidelines and standards and thus fulfill regulators expectations

    Endogenous measures for contextualising large-scale social phenomena: a corpus-based method for mediated public discourse

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    This work presents an interdisciplinary methodology for developing endogenous measures of group membership through analysis of pervasive linguistic patterns in public discourse. Focusing on political discourse, this work critiques the conventional approach to the study of political participation, which is premised on decontextualised, exogenous measures to characterise groups. Considering the theoretical and empirical weaknesses of decontextualised approaches to large-scale social phenomena, this work suggests that contextualisation using endogenous measures might provide a complementary perspective to mitigate such weaknesses. This work develops a sociomaterial perspective on political participation in mediated discourse as affiliatory action performed through language. While the affiliatory function of language is often performed consciously (such as statements of identity), this work is concerned with unconscious features (such as patterns in lexis and grammar). This work argues that pervasive patterns in such features that emerge through socialisation are resistant to change and manipulation, and thus might serve as endogenous measures of sociopolitical contexts, and thus of groups. In terms of method, the work takes a corpus-based approach to the analysis of data from the Twitter messaging service whereby patterns in users’ speech are examined statistically in order to trace potential community membership. The method is applied in the US state of Michigan during the second half of 2018—6 November having been the date of midterm (i.e. non-Presidential) elections in the United States. The corpus is assembled from the original posts of 5,889 users, who are nominally geolocalised to 417 municipalities. These users are clustered according to pervasive language features. Comparing the linguistic clusters according to the municipalities they represent finds that there are regular sociodemographic differentials across clusters. This is understood as an indication of social structure, suggesting that endogenous measures derived from pervasive patterns in language may indeed offer a complementary, contextualised perspective on large-scale social phenomena

    The Viability and Potential Consequences of IoT-Based Ransomware

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    With the increased threat of ransomware and the substantial growth of the Internet of Things (IoT) market, there is significant motivation for attackers to carry out IoT-based ransomware campaigns. In this thesis, the viability of such malware is tested. As part of this work, various techniques that could be used by ransomware developers to attack commercial IoT devices were explored. First, methods that attackers could use to communicate with the victim were examined, such that a ransom note was able to be reliably sent to a victim. Next, the viability of using "bricking" as a method of ransom was evaluated, such that devices could be remotely disabled unless the victim makes a payment to the attacker. Research was then performed to ascertain whether it was possible to remotely gain persistence on IoT devices, which would improve the efficacy of existing ransomware methods, and provide opportunities for more advanced ransomware to be created. Finally, after successfully identifying a number of persistence techniques, the viability of privacy-invasion based ransomware was analysed. For each assessed technique, proofs of concept were developed. A range of devices -- with various intended purposes, such as routers, cameras and phones -- were used to test the viability of these proofs of concept. To test communication hijacking, devices' "channels of communication" -- such as web services and embedded screens -- were identified, then hijacked to display custom ransom notes. During the analysis of bricking-based ransomware, a working proof of concept was created, which was then able to remotely brick five IoT devices. After analysing the storage design of an assortment of IoT devices, six different persistence techniques were identified, which were then successfully tested on four devices, such that malicious filesystem modifications would be retained after the device was rebooted. When researching privacy-invasion based ransomware, several methods were created to extract information from data sources that can be commonly found on IoT devices, such as nearby WiFi signals, images from cameras, or audio from microphones. These were successfully implemented in a test environment such that ransomable data could be extracted, processed, and stored for later use to blackmail the victim. Overall, IoT-based ransomware has not only been shown to be viable but also highly damaging to both IoT devices and their users. While the use of IoT-ransomware is still very uncommon "in the wild", the techniques demonstrated within this work highlight an urgent need to improve the security of IoT devices to avoid the risk of IoT-based ransomware causing havoc in our society. Finally, during the development of these proofs of concept, a number of potential countermeasures were identified, which can be used to limit the effectiveness of the attacking techniques discovered in this PhD research

    A Design Science Research Approach to Smart and Collaborative Urban Supply Networks

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    Urban supply networks are facing increasing demands and challenges and thus constitute a relevant field for research and practical development. Supply chain management holds enormous potential and relevance for society and everyday life as the flow of goods and information are important economic functions. Being a heterogeneous field, the literature base of supply chain management research is difficult to manage and navigate. Disruptive digital technologies and the implementation of cross-network information analysis and sharing drive the need for new organisational and technological approaches. Practical issues are manifold and include mega trends such as digital transformation, urbanisation, and environmental awareness. A promising approach to solving these problems is the realisation of smart and collaborative supply networks. The growth of artificial intelligence applications in recent years has led to a wide range of applications in a variety of domains. However, the potential of artificial intelligence utilisation in supply chain management has not yet been fully exploited. Similarly, value creation increasingly takes place in networked value creation cycles that have become continuously more collaborative, complex, and dynamic as interactions in business processes involving information technologies have become more intense. Following a design science research approach this cumulative thesis comprises the development and discussion of four artefacts for the analysis and advancement of smart and collaborative urban supply networks. This thesis aims to highlight the potential of artificial intelligence-based supply networks, to advance data-driven inter-organisational collaboration, and to improve last mile supply network sustainability. Based on thorough machine learning and systematic literature reviews, reference and system dynamics modelling, simulation, and qualitative empirical research, the artefacts provide a valuable contribution to research and practice

    Lift EVERY Voice and Sing: An Intersectional Qualitative Study Examining the Experiences of Lesbian, Gay, Bisexual, and Queer Faculty and Administrators at Historically Black Colleges and Universities

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    While there is minimal literature that address the experiences of lesbian, gay, bisexual, and trans* identified students at Historically Black Colleges and Universities (HBCUs), the experiences of Black, queer faculty and administrators at HBCUs has not been studied. This intersectional qualitative research study focused on the experiences of lesbian, gay, bisexual, and queer identified faculty and administrators who work at HBCUs. By investigating the intersections of religion, race, gender, and sexuality within a predominantly Black institution, this study aims to enhance diversity, equity, and inclusion efforts at HBCUs by sharing the experiences of the LGBQ faculty and administrators that previously or currently work at an HBCU as a full-time employee. The research questions that guided this study were 1) How have LGBQ faculty and staff negotiated/navigated their careers at HBCUs? and 2) How do LGBQ faculty and staff at HBCUs influence cultural (relating to LGBQ inclusion) change at the organizational level? The main theoretical framework used was intersectionality and it shaped the chosen methodology and methods. The Politics of Respectability was the second theoretical framework used to describe the intra-racial tensions within the Black/African American community. The study included 60-120 minute interviews with 12 participants. Using intersectionality as a guide, the data were coded and utilized for thematic analysis. Then, an ethnodramatic performance engages readers. The goals of this study were to encourage policy changes, promote inclusivity for LGBQ employees at HBCUs, and provide an expansion to the body of literature in the field pertaining to the experiences of LGBQ faculty and administrators in higher education
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