3,533 research outputs found

    SoK: Analysis of Software Supply Chain Security by Establishing Secure Design Properties

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    This paper systematizes knowledge about secure software supply chain patterns. It identifies four stages of a software supply chain attack and proposes three security properties crucial for a secured supply chain: transparency, validity, and separation. The paper describes current security approaches and maps them to the proposed security properties, including research ideas and case studies of supply chains in practice. It discusses the strengths and weaknesses of current approaches relative to known attacks and details the various security frameworks put out to ensure the security of the software supply chain. Finally, the paper highlights potential gaps in actor and operation-centered supply chain security techniques

    Modeling Crowd Feedback in the Mobile App Market

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    Mobile application (app) stores, such as Google Play and the Apple App Store, have recently emerged as a new model of online distribution platform. These stores have expanded in size in the past five years to host millions of apps, offering end-users of mobile software virtually unlimited options to choose from. In such a competitive market, no app is too big to fail. In fact, recent evidence has shown that most apps lose their users within the first 90 days after initial release. Therefore, app developers have to remain up-to-date with their end-users’ needs in order to survive. Staying close to the user not only minimizes the risk of failure, but also serves as a key factor in achieving market competitiveness as well as managing and sustaining innovation. However, establishing effective communication channels with app users can be a very challenging and demanding process. Specifically, users\u27 needs are often tacit, embedded in the complex interplay between the user, system, and market components of the mobile app ecosystem. Furthermore, such needs are scattered over multiple channels of feedback, such as app store reviews and social media platforms. To address these challenges, in this dissertation, we incorporate methods of requirements modeling, data mining, domain engineering, and market analysis to develop a novel set of algorithms and tools for automatically classifying, synthesizing, and modeling the crowd\u27s feedback in the mobile app market. Our analysis includes a set of empirical investigations and case studies, utilizing multiple large-scale datasets of mobile user data, in order to devise, calibrate, and validate our algorithms and tools. The main objective is to introduce a new form of crowd-driven software models that can be used by app developers to effectively identify and prioritize their end-users\u27 concerns, develop apps to meet these concerns, and uncover optimized pathways of survival in the mobile app ecosystem

    GitHub: Factors Influencing Project Activity Levels

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    Open source software projects typically extend the capabilities of their software by incorporating code contributions from a diverse cross-section of developers. This GitHub structural path modelling study captures the current top 100 JavaScript projects in operation for at least one year or more. It draws on three theories (information integration, planned behavior, and social translucence) to help frame its comparative path approach, and to show ways to speed the collaborative development of GitHub OSS projects. It shows a project’s activity level increases with: (1) greater responder-group collaborative efforts, (2) increased numbers of major critical project version releases, and (3) the generation of further commits. However, the generation of additional forks negatively impacts overall project activity levels

    Enterprise 2.0: Collaboration and Knowledge Emergence as a Business Web Strategy Enabler

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    The Web is becoming in many respects a powerful tool for supporting business strategy as companies are quickly becoming more and more reliant on new Web-based technologies to capitalize on new business opportunities. However, this introduces additional managerial problems and risks that have to be taken into consideration, if they are not to be left behind. In this chapter we explore the Web’s present and future potential in relation to information sharing, knowledge management, innovation management, and the automation of cross-organizational business transactions. The suggested approach will provide entrepreneurs, managers, and IT leaders with guidance on how to adopt the latest Web 2.0-based technologies in their everyday work with a view to setting up a business Web strategy. Specifically, Enterprise 2.0 is presented as a key enabler for businesses to expand their ecosystems and partnerships. Enterprise 2.0 also acts as a catalyst for improving innovation processes and knowledge work

    SANTO: Social Aerial NavigaTion in Outdoors

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    In recent years, the advances in remote connectivity, miniaturization of electronic components and computing power has led to the integration of these technologies in daily devices like cars or aerial vehicles. From these, a consumer-grade option that has gained popularity are the drones or unmanned aerial vehicles, namely quadrotors. Although until recently they have not been used for commercial applications, their inherent potential for a number of tasks where small and intelligent devices are needed is huge. However, although the integrated hardware has advanced exponentially, the refinement of software used for these applications has not beet yet exploited enough. Recently, this shift is visible in the improvement of common tasks in the field of robotics, such as object tracking or autonomous navigation. Moreover, these challenges can become bigger when taking into account the dynamic nature of the real world, where the insight about the current environment is constantly changing. These settings are considered in the improvement of robot-human interaction, where the potential use of these devices is clear, and algorithms are being developed to improve this situation. By the use of the latest advances in artificial intelligence, the human brain behavior is simulated by the so-called neural networks, in such a way that computing system performs as similar as possible as the human behavior. To this end, the system does learn by error which, in an akin way to the human learning, requires a set of previous experiences quite considerable, in order for the algorithm to retain the manners. Applying these technologies to robot-human interaction do narrow the gap. Even so, from a bird's eye, a noticeable time slot used for the application of these technologies is required for the curation of a high-quality dataset, in order to ensure that the learning process is optimal and no wrong actions are retained. Therefore, it is essential to have a development platform in place to ensure these principles are enforced throughout the whole process of creation and optimization of the algorithm. In this work, multiple already-existing handicaps found in pipelines of this computational gauge are exposed, approaching each of them in a independent and simple manner, in such a way that the solutions proposed can be leveraged by the maximum number of workflows. On one side, this project concentrates on reducing the number of bugs introduced by flawed data, as to help the researchers to focus on developing more sophisticated models. On the other side, the shortage of integrated development systems for this kind of pipelines is envisaged, and with special care those using simulated or controlled environments, with the goal of easing the continuous iteration of these pipelines.Thanks to the increasing popularity of drones, the research and development of autonomous capibilities has become easier. However, due to the challenge of integrating multiple technologies, the available software stack to engage this task is restricted. In this thesis, we accent the divergencies among unmanned-aerial-vehicle simulators and propose a platform to allow faster and in-depth prototyping of machine learning algorithms for this drones

    Taxonomy of Attacks on Open-Source Software Supply Chains

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    The widespread dependency on open-source software makes it a fruitful target for malicious actors, as demonstrated by recurring attacks. The complexity of today's open-source supply chains results in a significant attack surface, giving attackers numerous opportunities to reach the goal of injecting malicious code into open-source artifacts that is then downloaded and executed by victims. This work proposes a general taxonomy for attacks on open-source supply chains, independent of specific programming languages or ecosystems, and covering all supply chain stages from code contributions to package distribution. Taking the form of an attack tree, it covers 107 unique vectors, linked to 94 real-world incidents, and mapped to 33 mitigating safeguards. User surveys conducted with 17 domain experts and 134 software developers positively validated the correctness, comprehensiveness and comprehensibility of the taxonomy, as well as its suitability for various use-cases. Survey participants also assessed the utility and costs of the identified safeguards, and whether they are used

    A Systematic Mapping Study on Requirements Engineering in Software Ecosystems

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    Software ecosystems (SECOs) and open innovation processes have been claimed as a way forward for the software industry. A proper understanding of requirements is as important for these IT-systems as for more traditional ones. This paper presents a mapping study on the issues of requirements engineering and quality aspects in SECOs and analyzes emerging ideas. Our findings indicate that among the various phases or subtasks of requirements engineering, most of the SECO specific research has been accomplished on elicitation, analysis, and modeling. On the other hand, requirements selection, prioritization, verification, and traceability has attracted few published studies. Among the various quality attributes, most of the SECOs research has been performed on security, performance and testability. On the other hand, reliability, safety, maintainability, transparency, usability attracted few published studies. The paper provides a review of the academic literature about SECO-related requirements engineering activities, modeling approaches, and quality attributes, positions the source publications in a taxonomy of issues and identifies gaps where there has been little research.Comment: Journal of Information Technology Research (JITR) 11(1
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