Code pattern analysis of object-oriented programming languages

Code patterns, including programming patterns and design patterns, are good references for programming language feature improvement and software re-engineering. However, to our knowledge, no existing research has attempted to detect code patterns based on code clone detection technology. In this study, we build upon the previous work and propose to detect and analyze code patterns from a collection of open source projects using NiPAT technology. Because design patterns are most closely associated with object-oriented languages, we choose Java and Python projects to conduct our study. The tool we use for detecting patterns is NiPAT, a pattern detecting tool originally developed for the TXL programming language based on the NiCad clone detector. We extend NiPAT for the Java and Python programming languages. Then, we try to identify all the patterns from the pattern report and classify them into several different categories. In the end of the study, we analyze all the patterns and compare the differences between Java and Python patterns.

Licenshantering inom webbprojekt : Hur medvetna är företag om tredjepartslicenser?

Teknikutvecklingen går snabbt framåt, och idag finns det ett stort behov av att använda andra utvecklares kod för att hänga med i det höga tempot. De kallas samlat för ramverk eller bibliotek, och hjälper utvecklaren att på ett effektivare sätt ta sig från start till mål utan att behöva skriva all programmeringskod själv. Dessa tredjepartslösningar är nästintill alltid bundna till ett licensavtal, vars restriktioner och tillåtelser utvecklaren måste följa vid nyttjandet. I denna studie har vi undersökt hur medvetenheten ser ut kring de licenser som är bundna till dessa tredjepartslösningar. Då det framkom i vår förstudie att vårt fall hade en relativt låg medvetenhet har vi även valt att titta på hur medvetenheten kan ökas. För att genomföra detta har vi valt att intervjua utvecklare och projektledare på ett konsultföretag. Vi undersökte även vilka faktorer som är viktiga för att höja medvetenheten samt vilka konsekvenser som kunde uppkomma vid bristfällande licenshantering. Vi upptäckte att det var en bristfällig kunskap om tredjepartslicenser på det studerade företaget, och hur de följde de licensrestriktioner som fanns för respektive licens. För att höja medvetenheten föreslår vi hjälpmedel i form av en automatiserad centraliserad lösning, lathundar för en enklare överblick av licensavtalen och hur användning av redan färdiga programvaror kan hjälpa till att öka medvetenheten och hanteringen av licenser.

Introduction to EdShare

Presentation slides used in my online webinar session at ALTC 2016 Online Winter Conference. Providing an introduction to EdShare, the open source OER sharing platform from the University of Southampton. Discussion around its core features as well as the future development roadmap. Link to webinar recording will be added shortly.

Análisis de los sistemas de información en la productividad de la empresa Belta Ltda.

Los sistemas y la tecnología de información han sido una pieza clave en las organizaciones, estos buscan lograr un equilibrio junto con las estrategias empresariales, ya que de esta manera las empresas estarían en mejores condiciones para enfrentar los desafíos del mercado. (Morantes Leal y Miraidy Elena, 2007)1. Para abordar este tema, hemos decidido realizar un análisis de un sistema de información aplicado en la empresa Belta Ltda. para determinar la relación que existe entre la productividad y el uso de los sistemas empresariales. La información de este análisis está compuesta por 6 capítulos divididos de la siguiente manera: En el primer capítulo se muestra una introducción de los sistemas de información empresarial, la importancia del uso de las tecnologías, además se describe los objetivos de esta investigación, el alcance y vinculación de este proyecto con la línea de investigación de la escuela de administración de la universidad del Rosario. En el segundo capítulo se presenta el marco teórico; la descripción de los tipos de sistemas de información, y las metodologías utilizadas para la evaluación del uso de las tecnologías. Enseguida se describe la metodología utilizada para llevar a cabo esta investigación y las herramientas utilizadas para este caso de estudio en el capítulo tres. En el cuarto capítulo se muestra una descripción de la empresa, el organigrama, el entorno general del negocio, y se desarrolla la aplicación del documento guía; el modelo integral 5d`s, que consiste en realizar diferentes diagnósticos para determinar cómo se encuentra la empresa a nivel interno y externo. Finalmente, según el análisis y resultados obtenidos con esta investigación, se dan unas conclusiones finales y se proponen unas recomendaciones para la empresa en los últimos capítulos.

Ultra-Low Temperature Partial Oxidation: Detailed Kinetics, Safety, and Environmental Issues

The innovation in several industrial sectors has been recently characterized by the need for reducing the operative temperature either for economic or environmental related aspects. Promising technological solutions require the acquisition of fundamental-based knowledge to produce safe and robust systems. In this sense, reactive systems often represent the bottleneck. For these reasons, this work was focused on the integration of chemical (i.e., detailed kinetic mechanism) and physical (i.e., computational fluid dynamics) models. A theoretical-based kinetic mechanism mimicking the behaviour of oxygenated fuels and their intermediates under oxidative conditions in a wide range of temperature and pressure was developed. Its validity was tested against experimental data collected in this work by using the heat flux burner, as well as measurements retrieved from the current literature. Besides, estimations deriving from existing models considered as the benchmark in the combustion field were compared with the newly generated mechanism. The latter was found to be the most accurate for the investigated conditions and fuels. Most influential species and reactions on the combustion of butyl acetate were identified. The corresponding thermodynamic parameter and rate coefficients were quantified through ab initio calculations. A reduced detailed kinetic mechanism was produced and implemented in an open-source computational fluid dynamics model to characterize pool fires caused by the accidental release of aviation fuel and liquefied natural gas, at first. Eventually, partial oxidation processes involving light alkenes were optimized following the quick, fair, and smoot (QFS) paradigm. The proposed procedure represents a comprehensive and multidisciplinary approach for the construction and validation of accurate models, allowing for the characterization of developing industrial sectors and techniques.

CFD Applications for Wave Energy Conversion Devices (MoonWEC) and Turbulent Fountains for Environmental Fluid Mechanics

This thesis is based on two studies that are related to floating wave energy conversion (WEC) devices and turbulent fountains. The ability of the open-source CFD software OpenFOAM® has been studied to simulate these phenomena. The CFD model has been compared with the physical experimental results. The first study presents a model of a WEC device, called MoonWEC, which is patented by the University of Bologna. The CFD model of the MoonWEC under the action of waves has been simulated using OpenFOAM and the results are promising. The reliability of the CFD model is confirmed by the laboratory experiments, conducted at the University of Bologna, for which a small-scale prototype of the MoonWEC was made from wood and brass. The second part of the thesis is related to the turbulent fountains which are formed when a heavier source fluid is injected upward into a lighter ambient fluid, or else a lighter source fluid is injected downward into a heavier ambient fluid. For this study, the first case is considered for laboratory experiments and the corresponding CFD model. The vertical releases of the source fluids into a quiescent, uniform ambient fluid, from a circular source, were studied with different densities in the laboratory experiments, conducted at the University of Parma. The CFD model has been set up for these experiments. Favourable results have been observed from the OpenFOAM simulations for the turbulent fountains as well, indicating that it can be a reliable tool for the simulation of such phenomena.

Impact of retransmissions in IEEE 802.11bd

The main goal of this thesis is to study the impact of retransmissions in the upcoming IEEE 802.11bd standard and to determine an algorithm which can, on a vehicle to vehicle basis, activate them or not depending on the channel state, using the channel busy rate (CBR) as the leading metric. The study was based on simulations performed with the WiLabV2Xsim, which is an open source discrete event simulator that can be used to simulate communication between vehicles under the rules of different protocols.

Hybrid Artificial Intelligence to Extract Patterns and Rules from Argumentative and Legal Texts

This Thesis is composed of a collection of works written in the period 2019-2022, whose aim is to find methodologies of Artificial Intelligence (AI) and Machine Learning to detect and classify patterns and rules in argumentative and legal texts. We define our approach “hybrid”, since we aimed at designing hybrid combinations of symbolic and sub-symbolic AI, involving both “top-down” structured knowledge and “bottom-up” data-driven knowledge. A first group of works is dedicated to the classification of argumentative patterns. Following the Waltonian model of argument and the related theory of Argumentation Schemes, these works focused on the detection of argumentative support and opposition, showing that argumentative evidences can be classified at fine-grained levels without resorting to highly engineered features. To show this, our methods involved not only traditional approaches such as TFIDF, but also some novel methods based on Tree Kernel algorithms. After the encouraging results of this first phase, we explored the use of a some emerging methodologies promoted by actors like Google, which have deeply changed NLP since 2018-19 — i.e., Transfer Learning and language models. These new methodologies markedly improved our previous results, providing us with best-performing NLP tools. Using Transfer Learning, we also performed a Sequence Labelling task to recognize the exact span of argumentative components (i.e., claims and premises), thus connecting portions of natural language to portions of arguments (i.e., to the logical-inferential dimension). The last part of our work was finally dedicated to the employment of Transfer Learning methods for the detection of rules and deontic modalities. In this case, we explored a hybrid approach which combines structured knowledge coming from two LegalXML formats (i.e., Akoma Ntoso and LegalRuleML) with sub-symbolic knowledge coming from pre-trained (and then fine-tuned) neural architectures.

Landslide susceptibility in the Belt and Road Initiative

The Belt and Road Initiative (BRI) is a project launched by the Chinese Government whose main goal is to connect more than 65 countries in Asia, Europe, Africa and Oceania developing infrastructures and facilities. To support the prevention or mitigation of landslide hazards, which may affect the mainland infrastructures of BRI, a landslide susceptibility analysis in the countries involved has been carried out. Due to the large study area, the analysis has been carried out using a multi-scale approach which consists of mapping susceptibility firstly at continental scale, and then at national scale. The study area selected for the continental assessment is the south-Asia, where a pixel-based landslide susceptibility map has been carried out using the Weight of Evidence method and validated by Receiving Operating Characteristic (ROC) curves. Then, we selected the regions of west Tajikistan and north-east India to be investigated at national scale. Data scarcity is a common condition for many countries involved into the Initiative. Therefore in addition to the landslide susceptibility assessment of west Tajikistan, which has been conducted using a Generalized Additive Model and validated by ROC curves, we have examined, in the same study area, the effect of incomplete landslide dataset on the prediction capacity of statistical models. The entire PhD research activity has been conducted using only open data and open-source software. In this context, to support the analysis of the last years an open-source plugin for QGIS has been implemented. The SZ-tool allows the user to make susceptibility assessments from the data preprocessing, susceptibility mapping, to the final classification. All the output data of the analysis conducted are freely available and downloadable. This text describes the research activity of the last three years. Each chapter reports the text of the articles published in international scientific journal during the PhD.

Decentralized systems for the protection and portability of personal data

The General Data Protection Regulation (GDPR) has been designed to help promote a view in favor of the interests of individuals instead of large corporations. However, there is the need of more dedicated technologies that can help companies comply with GDPR while enabling people to exercise their rights. We argue that such a dedicated solution must address two main issues: the need for more transparency towards individuals regarding the management of their personal information and their often hindered ability to access and make interoperable personal data in a way that the exercise of one's rights would result in straightforward. We aim to provide a system that helps to push personal data management towards the individual's control, i.e., a personal information management system (PIMS). By using distributed storage and decentralized computing networks to control online services, users' personal information could be shifted towards those directly concerned, i.e., the data subjects. The use of Distributed Ledger Technologies (DLTs) and Decentralized File Storage (DFS) as an implementation of decentralized systems is of paramount importance in this case. The structure of this dissertation follows an incremental approach to describing a set of decentralized systems and models that revolves around personal data and their subjects. Each chapter of this dissertation builds up the previous one and discusses the technical implementation of a system and its relation with the corresponding regulations. We refer to the EU regulatory framework, including GDPR, eIDAS, and Data Governance Act, to build our final system architecture's functional and non-functional drivers. In our PIMS design, personal data is kept in a Personal Data Space (PDS) consisting of encrypted personal data referring to the subject stored in a DFS. On top of that, a network of authorization servers acts as a data intermediary to provide access to potential data recipients through smart contracts.

First steps in underwater photogrammetry with the support of an unmanned underwater vehicle

The evolution of modern and increasingly sensitive image sensors, the increasingly compact design of the cameras, and the recent emergence of low-cost cameras allowed the Underwater Photogrammetry to become an infallible and irreplaceable technique used to estimate the structure of the seabed with high accuracy. Within this context, the main topic of this work is the Underwater Photogrammetry from a geomatic point of view and all the issues associated with its implementation, in particular with the support of Unmanned Underwater Vehicles. Questions such as: how does the technique work, what is needed to deal with a proper survey, what tools are available to apply this technique, and how to resolve uncertainties in measurement will be the subject of this thesis. The study conducted can be divided into two major parts: one devoted to several ad-hoc surveys and tests, thus a practical part, another supported by the bibliographical research. However the main contributions are related to the experimental section, in which two practical case studies are carried out in order to improve the quality of the underwater survey of some calibration platforms. The results obtained from these two experiments showed that, the refractive effects due to water and underwater housing can be compensated by the distortion coefficients in the camera model, but if the aim is to achieve high accuracy then a model that takes into account the configuration of the underwater housing, based on ray tracing, must also be coupled. The major contributions that this work brought are: an overview of the practical issues when performing surveys exploiting an UUV prototype, a method to reach a reliable accuracy in the 3D reconstructions without the use of an underwater local geodetic network, a guide for who addresses underwater photogrammetry topics for the first time, and the use of open-source environments.

A Distributed Support based on Kubeflow to Ease MLOps of Federated Learning Algorithms

The main objective of my thesis work is to exploit the Google native and open-source platform Kubeflow, specifically using Kubeflow pipelines, to execute a Federated Learning scalable ML process in a 5G-like and simplified test architecture hosting a Kubernetes cluster and apply the largely adopted FedAVG algorithm and FedProx its optimization empowered by the ML platform ‘s abilities to ease the development and production cycle of this specific FL process. FL algorithms are more are and more promising and adopted both in Cloud application development and 5G communication enhancement through data coming from the monitoring of the underlying telco infrastructure and execution of training and data aggregation at edge nodes to optimize the global model of the algorithm ( that could be used for example for resource provisioning to reach an agreed QoS for the underlying network slice) and after a study and a research over the available papers and scientific articles related to FL with the help of the CTTC that suggests me to study and use Kubeflow to bear the algorithm we found out that this approach for the whole FL cycle deployment was not documented and may be interesting to investigate more in depth. This study may lead to prove the efficiency of the Kubeflow platform itself for this need of development of new FL algorithms that will support new Applications and especially test the FedAVG algorithm performances in a simulated client to cloud communication using a MNIST dataset for FL as benchmark.

NLG-Metricverse: An End-to-End Library for Evaluating Natural Language Generation

Driven by recent deep learning breakthroughs, natural language generation (NLG) models have been at the center of steady progress in the last few years. However, since our ability to generate human-indistinguishable artificial text lags behind our capacity to assess it, it is paramount to develop and apply even better automatic evaluation metrics. To facilitate researchers to judge the effectiveness of their models broadly, we suggest NLG-Metricverse—an end-to-end open-source library for NLG evaluation based on Python. This framework provides a living collection of NLG metrics in a unified and easy- to-use environment, supplying tools to efficiently apply, analyze, compare, and visualize them. This includes (i) the extensive support of heterogeneous automatic metrics with n-arity management, (ii) the meta-evaluation upon individual performance, metric-metric and metric-human correlations, (iii) graphical interpretations for helping humans better gain score intuitions, (iv) formal categorization and convenient documentation to accelerate metrics understanding. NLG-Metricverse aims to increase the comparability and replicability of NLG research, hopefully stimulating new contributions in the area.

La diffusione dei cheating bot nei videogiochi e possibili soluzioni di contrasto

Il fine di questo elaborato riguarda lo studio di soluzioni per il contrasto di giocatori baranti controllati da algoritmi presenti nel videogioco online Team Fortress 2. Dopo una breve introduzione alla storia degli sparatutto online, si descriverà il funzionamento di tutti i componenti che sviluppano l'ambiente di gioco, oltre a definire termini e sistemi vitali per la comprensione dell'elaborato ed una breve introduzione a Team Fortress 2. Si procederà alla discussione del cheat e dei software e/o environment sfruttati dagli attacanti in partita, andando a cercare di spiegare il meccanismo e l'origine di questi elementi, nonché introdurre il concetto dei bot baranti implementati usando il programma open source cathook. Una volta spiegata la minaccia si andrà a spiegare la difesa da parte del gioco e degli sviluppatori attraverso il software di anticheat Valve Anti-Cheat (VAC) presente sul gioco, definendo le terminologie e alcune caratteristiche comuni rispetto agli altri, per poi introdurre le nuove tecnologie di contrasto sviluppati per Counter Strike: Global Offensive, ovvero Overwatch, Trust Factor e l'anticheat con deep learning VACNET. Infine, dopo aver definito più approfonditamente il funzionamento degli algoritmi baranti, verranno suggerite delle possibili soluzioni implementabili e del motivo per cui non riescono a risolvere completamente il problema. Concluderemo spiegando cosa stanno facendo i sviluppatori, per poi descrivere come effettivamente il problema possiede come l'unica soluzione di evitare di giocare nei server ufficiali di gioco, mantenendo comunque gli algoritmi liberi nei server ufficiali.

Impact of convective motions on pollutant dispersion in urban canyons: an analysis through RANS simulations

Since the majority of the population of the world lives in cities and that this number is expected to increase in the next years, one of the biggest challenges of the research is the determination of the risk deriving from high temperatures experienced in urban areas, together with improving responses to climate-related disasters, for example by introducing in the urban context vegetation or built infrastructures that can improve the air quality. In this work, we will investigate how different setups of the boundary and initial conditions set on an urban canyon generate different patterns of the dispersion of a pollutant. To do so we will exploit the low computational cost of Reynolds-Averaged Navier-Stokes (RANS) simulations to reproduce the dynamics of an infinite array of two-dimensional square urban canyons. A pollutant is released at the street level to mimic the presence of traffic. RANS simulations are run using the k-ɛ closure model and vertical profiles of significant variables of the urban canyon, namely the velocity, the turbulent kinetic energy, and the concentration, are represented. This is done using the open-source software OpenFOAM and modifying the standard solver simpleFoam to include the concentration equation and the temperature by introducing a buoyancy term in the governing equations. The results of the simulation are validated with experimental results and products of Large-Eddy Simulations (LES) from previous works showing that the simulation is able to reproduce all the quantities under examination with satisfactory accuracy. Moreover, this comparison shows that despite LES are known to be more accurate albeit more expensive, RANS simulations represent a reliable tool if a smaller computational cost is needed. Overall, this work exploits the low computational cost of RANS simulations to produce multiple scenarios useful to evaluate how the dispersion of a pollutant changes by a modification of key variables, such as the temperature.