1,201 research outputs found

    JWalk: a tool for lazy, systematic testing of java classes by design introspection and user interaction

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    Popular software testing tools, such as JUnit, allow frequent retesting of modified code; yet the manually created test scripts are often seriously incomplete. A unit-testing tool called JWalk has therefore been developed to address the need for systematic unit testing within the context of agile methods. The tool operates directly on the compiled code for Java classes and uses a new lazy method for inducing the changing design of a class on the fly. This is achieved partly through introspection, using Java’s reflection capability, and partly through interaction with the user, constructing and saving test oracles on the fly. Predictive rules reduce the number of oracle values that must be confirmed by the tester. Without human intervention, JWalk performs bounded exhaustive exploration of the class’s method protocols and may be directed to explore the space of algebraic constructions, or the intended design state-space of the tested class. With some human interaction, JWalk performs up to the equivalent of fully automated state-based testing, from a specification that was acquired incrementally

    Técnicas de anålise de imagens para detecção de retinopatia diabética

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    Orientadores: Anderson de Rezende Rocha. Jacques WainerTese (doutorado) - Universidade Estadual de Campinas, Instituto de ComputaçãoResumo: Retinopatia DiabĂ©tica (RD) Ă© uma complicação a longo prazo do diabetes e a principal causa de cegueira da população ativa. Consultas regulares sĂŁo necessĂĄrias para diagnosticar a retinopatia em um estĂĄgio inicial, permitindo um tratamento com o melhor prognĂłstico capaz de retardar ou atĂ© mesmo impedir a cegueira. Alavancados pela evolução da prevalĂȘncia do diabetes e pelo maior risco que os diabĂ©ticos tĂȘm de desenvolver doenças nos olhos, diversos trabalhos com abordagens bem estabelecidas e promissoras vĂȘm sendo desenvolvidos para triagem automĂĄtica de retinopatia. Entretanto, a maior parte dos trabalhos estĂĄ focada na detecção de lesĂ”es utilizando caracterĂ­sticas visuais particulares de cada tipo de lesĂŁo. AlĂ©m do mais, soluçÔes artesanais para avaliação de necessidade de consulta e de identificação de estĂĄgios da retinopatia ainda dependem bastante das lesĂ”es, cujo repetitivo procedimento de detecção Ă© complexo e inconveniente, mesmo se um esquema unificado for adotado. O estado da arte para avaliação automatizada de necessidade de consulta Ă© composto por abordagens que propĂ”em uma representação altamente abstrata obtida inteiramente por meio dos dados. Usualmente, estas abordagens recebem uma imagem e produzem uma resposta Âż que pode ser resultante de um Ășnico modelo ou de uma combinação Âż e nĂŁo sĂŁo facilmente explicĂĄveis. Este trabalho objetivou melhorar a detecção de lesĂ”es e reforçar decisĂ”es relacionadas Ă  necessidade de consulta, fazendo uso de avançadas representaçÔes de imagens em duas etapas. NĂłs tambĂ©m almejamos compor um modelo sofisticado e direcionado pelos dados para triagem de retinopatia, bem como incorporar aprendizado supervisionado de caracterĂ­sticas com representação orientada por mapa de calor, resultando em uma abordagem robusta e ainda responsĂĄvel para triagem automatizada. Finalmente, tivemos como objetivo a integração das soluçÔes em dispositivos portĂĄteis de captura de imagens de retina. Para detecção de lesĂ”es, propusemos abordagens de caracterização de imagens que possibilitem uma detecção eficaz de diferentes tipos de lesĂ”es. Nossos principais avanços estĂŁo centrados na modelagem de uma nova tĂ©cnica de codificação para imagens de retina, bem como na preservação de informaçÔes no processo de pooling ou agregação das caracterĂ­sticas obtidas. Decidir automaticamente pela necessidade de encaminhamento do paciente a um especialista Ă© uma investigação ainda mais difĂ­cil e muito debatida. NĂłs criamos um mĂ©todo mais simples e robusto para decisĂ”es de necessidade de consulta, e que nĂŁo depende da detecção de lesĂ”es. TambĂ©m propusemos um modelo direcionado pelos dados que melhora significativamente o desempenho na tarefa de triagem da RD. O modelo produz uma resposta confiĂĄvel com base em respostas (locais e globais), bem como um mapa de ativação que permite uma compreensĂŁo de importĂąncia de cada pixel para a decisĂŁo. Exploramos a metodologia de explicabilidade para criar um descritor local codificado em uma rica representação em nĂ­vel mĂ©dio. Os modelos direcionados pelos dados sĂŁo o estado da arte para triagem de retinopatia diabĂ©tica. Entretanto, mapas de ativação sĂŁo essenciais para interpretar o aprendizado em termos de importĂąncia de cada pixel e para reforçar pequenas caracterĂ­sticas discriminativas que tĂȘm potencial de melhorar o diagnĂłsticoAbstract: Diabetic Retinopathy (DR) is a long-term complication of diabetes and the leading cause of blindness among working-age adults. A regular eye examination is necessary to diagnose DR at an early stage, when it can be treated with the best prognosis and the visual loss delayed or deferred. Leveraged by the continuous expansion of diabetics and by the increased risk that those people have to develop eye diseases, several works with well-established and promising approaches have been proposed for automatic screening. Therefore, most existing art focuses on lesion detection using visual characteristics specific to each type of lesion. Additionally, handcrafted solutions for referable diabetic retinopathy detection and DR stages identification still depend too much on the lesions, whose repetitive detection is complex and cumbersome to implement, even when adopting a unified detection scheme. Current art for automated referral assessment resides on highly abstract data-driven approaches. Usually, those approaches receive an image and spit the response out Âż that might be resulting from only one model or ensembles Âż and are not easily explainable. Hence, this work aims at enhancing lesion detection and reinforcing referral decisions with advanced handcrafted two-tiered image representations. We also intended to compose sophisticated data-driven models for referable DR detection and incorporate supervised learning of features with saliency-oriented mid-level image representations to come up with a robust yet accountable automated screening approach. Ultimately, we aimed at integrating our software solutions with simple retinal imaging devices. In the lesion detection task, we proposed advanced handcrafted image characterization approaches to detecting effectively different lesions. Our leading advances are centered on designing a novel coding technique for retinal images and preserving information in the pooling process. Automatically deciding on whether or not the patient should be referred to the ophthalmic specialist is a more difficult, and still hotly debated research aim. We designed a simple and robust method for referral decisions that does not rely upon lesion detection stages. We also proposed a novel and effective data-driven model that significantly improves the performance for DR screening. Our accountable data-driven model produces a reliable (local- and global-) response along with a heatmap/saliency map that enables pixel-based importance comprehension. We explored this methodology to create a local descriptor that is encoded into a rich mid-level representation. Data-driven methods are the state of the art for diabetic retinopathy screening. However, saliency maps are essential not only to interpret the learning in terms of pixel importance but also to reinforce small discriminative characteristics that have the potential to enhance the diagnosticDoutoradoCiĂȘncia da ComputaçãoDoutor em CiĂȘncia da ComputaçãoCAPE

    Quantitative imaging analysis:challenges and potentials

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    Fairness Testing: A Comprehensive Survey and Analysis of Trends

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    Unfair behaviors of Machine Learning (ML) software have garnered increasing attention and concern among software engineers. To tackle this issue, extensive research has been dedicated to conducting fairness testing of ML software, and this paper offers a comprehensive survey of existing studies in this field. We collect 100 papers and organize them based on the testing workflow (i.e., how to test) and testing components (i.e., what to test). Furthermore, we analyze the research focus, trends, and promising directions in the realm of fairness testing. We also identify widely-adopted datasets and open-source tools for fairness testing

    Investigations into the model driven design of distribution patterns for web service compositions

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    Increasingly, distributed systems are being used to provide enterprise level solutions with high scalability and fault tolerance These solutins are often built using Web servces that are composed to perform useful business functions Acceptance of these composed systems is often constrained by a number of non-functional properties of the system such as availability, scalability and performance There are a number of drstribution patterns that each exhibit different non-functional charactmstics These patterns are re-occuring distribution schemes that express how a system is to be assembled and subsequently deployed. Traditional approaches to development of Web service compositions exhibit a number of Issues Firstly, Web service composition development is often ad-hoc and requires considerable low level coding effort for realisatlon Such systems often exhibit fixed architectures, making maintenance difficult and error prone Additionally, a number of the non-funchonal reqwements cannot be easily assessed by exammng low level code. In this thesis we explicitly model the compositional aspects of Web service compositions usmg UML Activity diagrams Ths approach uses a modehng and transformation framework, based on Model Dnven Software Development (MDSD), going from high level models to an executable system The framework is guided by a methodological framework whose primary artifact is a distribution pattern model, chosen from the supplied catalog. Our modelling and transfomation framework improves the development process of Web service compositions, with respect to a number of criteria, when compared to the traditional handcrafted approach Specifically, we negate the coding effort traditionally associated with Web service composition development Maintenance overheads of the solution are also slgnificantly reduced, while improved mutability 1s achieved through a flexible architecture when compared with existing tools We also improve the product output from the development process by exposing the non-functional runtime properties of Web service compositlons using distribution patterns

    Design of decorative 3D models: from geodesic ornaments to tangible assemblies

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    L'obiettivo di questa tesi Ăš sviluppare strumenti utili per creare opere d'arte decorative digitali in 3D. Uno dei processi decorativi piĂč comunemente usati prevede la creazione di pattern decorativi, al fine di abbellire gli oggetti. Questi pattern possono essere dipinti sull'oggetto di base o realizzati con l'applicazione di piccoli elementi decorativi. Tuttavia, la loro realizzazione nei media digitali non Ăš banale. Da un lato, gli utenti esperti possono eseguire manualmente la pittura delle texture o scolpire ogni decorazione, ma questo processo puĂČ richiedere ore per produrre un singolo pezzo e deve essere ripetuto da zero per ogni modello da decorare. D'altra parte, gli approcci automatici allo stato dell'arte si basano sull'approssimazione di questi processi con texturing basato su esempi o texturing procedurale, o con sistemi di riproiezione 3D. Tuttavia, questi approcci possono introdurre importanti limiti nei modelli utilizzabili e nella qualitĂ  dei risultati. Il nostro lavoro sfrutta invece i recenti progressi e miglioramenti delle prestazioni nel campo dell'elaborazione geometrica per creare modelli decorativi direttamente sulle superfici. Presentiamo una pipeline per i pattern 2D e una per quelli 3D, e dimostriamo come ognuna di esse possa ricreare una vasta gamma di risultati con minime modifiche dei parametri. Inoltre, studiamo la possibilitĂ  di creare modelli decorativi tangibili. I pattern 3D generati possono essere stampati in 3D e applicati a oggetti realmente esistenti precedentemente scansionati. Discutiamo anche la creazione di modelli con mattoncini da costruzione, e la possibilitĂ  di mescolare mattoncini standard e mattoncini custom stampati in 3D. CiĂČ consente una rappresentazione precisa indipendentemente da quanto la voxelizzazione sia approssimativa. I principali contributi di questa tesi sono l'implementazione di due diverse pipeline decorative, un approccio euristico alla costruzione con mattoncini e un dataset per testare quest'ultimo.The aim of this thesis is to develop effective tools to create digital decorative 3D artworks. Real-world art often involves the use of decorative patterns to enrich objects. These patterns can be painted on the base or might be realized with the application of small decorative elements. However, their creation in digital media is not trivial. On the one hand, users can manually perform texture paint or sculpt each decoration, in a process that can take hours to produce a single piece and needs to be repeated from the ground up for every model that needs to be decorated. On the other hand, automatic approaches in state of the art rely on approximating these processes with procedural or by-example texturing or with 3D reprojection. However, these approaches can introduce significant limitations in the models that can be used and in the quality of the results. Instead, our work exploits the recent advances and performance improvements in the geometry processing field to create decorative patterns directly on surfaces. We present a pipeline for 2D and one for 3D patterns and demonstrate how each of them can recreate a variety of results with minimal tweaking of the parameters. Furthermore, we investigate the possibility of creating decorative tangible models. The 3D patterns we generate can be 3D printed and applied to previously scanned real-world objects. We also discuss the creation of models with standard building bricks and the possibility of mixing standard and custom 3D-printed bricks. This allows for a precise representation regardless of the coarseness of the voxelization. The main contributions of this thesis are the implementation of two different decorative pipelines, a heuristic approach to brick construction, and a dataset to test the latter

    Next Steps for Human-Centered Generative AI: A Technical Perspective

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    Through iterative, cross-disciplinary discussions, we define and propose next-steps for Human-centered Generative AI (HGAI) from a technical perspective. We contribute a roadmap that lays out future directions of Generative AI spanning three levels: Aligning with human values; Accommodating humans' expression of intents; and Augmenting humans' abilities in a collaborative workflow. This roadmap intends to draw interdisciplinary research teams to a comprehensive list of emergent ideas in HGAI, identifying their interested topics while maintaining a coherent big picture of the future work landscape
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