8,015 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

    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

    Boundary Spanner Corruption in Business Relationships

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    Boundary spanner corruption—voluntary collaborative behaviour between individuals representing different organisations that violates their organisations’ norms—is a serious problem in business relationships. Drawing on insights from the literatures on general corruption perspectives, the dark side of business relationships and deviance in sales and service organisations, this dissertation identifies boundary spanner corruption as a potential dark side complication inherent in close business relationships It builds research questions from these literature streams and proposes a research structure based upon commonly used methods in corruption research to address this new concept. In the first study, using an exploratory survey of boundary spanner practitioners, the dissertation finds that the nature of boundary spanner corruption is broad and encompasses severe and non-severe types. The survey also finds that these deviance types are prevalent in a widespread of geographies and industries. This prevalence is particularly noticeable for less-severe corruption types, which may be an under-researched phenomenon in general corruption research. The consequences of boundary spanner corruption can be serious for both individuals and organisations. Indeed, even less-severe types can generate long-term negative consequences. A second interview-based study found that multi-level trust factors could also motivate the emergence of boundary spanner corruption. This was integrated into a theoretical model that illustrates how trust at the interpersonal, intraorganisational, and interorganisational levels enables corrupt behaviours by allowing deviance-inducing factors stemming from the task environment or from the individual boundary spanner to manifest in boundary spanner corruption. Interpersonal trust between representatives of different organisations, interorganisational trust between these organisations, and intraorganisational agency trust of management in their representatives foster the development of a boundary-spanning social cocoon—a mechanism that can inculcate deviant norms leading to corrupt behaviour. This conceptualisation and model of boundary spanner corruption highlights intriguing directions for future research to support practitioners engaged in a difficult problem in business relationships

    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

    Computational Geometry Contributions Applied to Additive Manufacturing

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    This Doctoral Thesis develops novel articulations of Computation Geometry for applications on Additive Manufacturing, as follows: (1) Shape Optimization in Lattice Structures. Implementation and sensitivity analysis of the SIMP (Solid Isotropic Material with Penalization) topology optimization strategy. Implementation of a method to transform density maps, resulting from topology optimization, into surface lattice structures. Procedure to integrate material homogenization and Design of Experiments (DOE) to estimate the stress/strain response of large surface lattice domains. (2) Simulation of Laser Metal Deposition. Finite Element Method implementation of a 2D nonlinear thermal model of the Laser Metal Deposition (LMD) process considering temperaturedependent material properties, phase change and radiation. Finite Element Method implementation of a 2D linear transient thermal model for a metal substrate that is heated by the action of a laser. (3) Process Planning for Laser Metal Deposition. Implementation of a 2.5D path planning method for Laser Metal Deposition. Conceptualization of a workflow for the synthesis of the Reeb Graph for a solid region in ℝ" denoted by its Boundary Representation (B-Rep). Implementation of a voxel-based geometric simulator for LMD process. Conceptualization, implementation, and validation of a tool for the minimization of the material over-deposition at corners in LMD. Implementation of a 3D (non-planar) slicing and path planning method for the LMD-manufacturing of overhanging features in revolute workpieces. The aforementioned contributions have been screened by the international scientific community via Journal and Conference submissions and publications

    Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

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    This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

    Towards a framework for the study of ongoing socio-technical transitions: explored through the UK self-driving car paradigm

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    The UK government set out to see self-driving cars on roads by 2021. The idea of a self-driving car has been around for almost a century, and more recent technological developments have made self-driving cars a real-life possibility. While a fully self-driving automobility system is some distance away, real-life testing is bringing autonomous driving closer to consumers. Some claim this to be the biggest disruption to mobility systems since the invention of the car. Claims about the potential of self-driving mobility range from economic and social benefits to environmental improvements. A significant ambiguity however remains concerning how they will be deployed and how the technological innovation will affect mobility aims and related transport and infrastructure systems. So far, the vast majority of studies on AVs have focused on the technology aspect of this transition lacking contributions that address this from a broader socio-technical perspective. With the accelerated adoption of new technologies, Sustainability Transitions has come to prominence as a research area that seeks to understand and guide socio-technical transitions toward sustainable trajectories. Socio-technical transitions theoretical framework has been used to understand historical transitions in the majority of empirical applications. The ability to apply the same framework to ongoing transitions and to guide these towards sustainable outcomes remains unsubstantiated. To address this gap this thesis examines the foundations of multi-level perspective (MLP) – a socio-technical transitions analytical framework – and develops an analytical framework (SRPM – System Rules Pathways Mechanisms) that is appropriate for the study of ongoing transitions. The refocused framework incorporates critical realism to focus analysis on causation and causal mechanisms. It is used to analyse the ongoing socio-technical transition to self-driving cars in the UK through a four-step analytical process. The study is framed as a case-based process mechanism study. The four steps are: i) contextualisation of the ongoing transition to AVs in the UK as a socio-technical transition based on the MLP theoretical framework; ii) identification of internal and external structural relations within the transition through the notion of rules and the morphogenetic cycle; iii) aligning observed processes with transition pathways to theorise about the trajectories of the transition; iv) identification of causal mechanisms in the observed processes through identification of demi-regularities through data analysis of grey literature and theorisation about mechanisms through the development of mechanism sketches and schemata. The thesis makes two contributions to knowledge: i) methodological and ii) empirical. The methodological contribution is the development of the SRPM analytical framework to study an ongoing socio-technical transition, and the empirical contribution is the application of this framework to the study of the ongoing transition to driverless cars in the UK

    Modeling, Simulation and Prediction of Vehicle Crashworthiness in Full Frontal Impact

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    Vehicle crashworthiness assessment is critical to help reduce road accident fatalities and ensure safer vehicles for road users. Techniques to assess crashworthiness include physical tests and mathematical modeling and simulation of crash events, the latter is preferred as mathematical modeling is generally cheaper to perform in comparison with physical testing. The most common mathematical modeling technique used for crashworthiness assessment is nonlinear Finite Element (FE) modeling. However, a problem with the use of Finite Element Model (FEM) for crashworthiness assessment is inaccessibility to individual researchers, public bodies, small universities and engineering companies due to need for detailed CAD data, software licence costs along with high computational demands. This thesis investigates modeling strategies which are affordable, computationally and labour inexpensive, and could be used by the above-mentioned groups. Use of Lumped Parameter Models (LPM) capable of capturing vehicle parameters contributing to vehicle crashworthiness has been proposed as an alternative to adopting FEM, while the later have been used to validate LPMs developed in this thesis. The main crash scenario analysed is a full frontal impact against a rigid barrier. Front-end deformation which can be used to measure crash energy absorption and pitching which could lead to occupant injuries in a frontal crash event are parameters focused on. The thesis investigates two types of vehicles; vehicle with initial structure intact is defined as baseline vehicle, while a vehicle that underwent unprofessional repairs on its structural members made of Ultra High Strength Steel (UHSS) is defined as a modified vehicle. The proposed novel LPM for a baseline vehicle impact is inspired by pendulum motion and expresses the system using Lagrangian formulation to predict the two phases of impact: front-end deformation and vehicle pitching. Changes in crashworthiness performance of a modified vehicle were investigated with a FEM; tensile tests on UHSS coupons were conducted to generate material inputs for this FEM. Further, a full scale crash test was conducted to validate the FE simulations. An LPM to conduct crashworthiness assessment of a modified vehicle has been proposed, it is based on a double pendulum with a torsional spring representing the vehicle undergoing a full frontal impact.publishedVersio
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