863 research outputs found

    Dependency-Aware Software Requirements Selection using Fuzzy Graphs and Integer Programming

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    Software requirements selection aims to find an optimal subset of the requirements with the highest value while respecting the project constraints. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Such Value Dependencies, however, are imprecise and hard to capture. In this paper, we propose a method based on integer programming and fuzzy graphs to account for value dependencies and their imprecision in software requirements selection. The proposed method, referred to as Dependency-Aware Software Requirements Selection (DARS), is comprised of three components: (i) an automated technique for the identification of value dependencies from user preferences, (ii) a modeling technique based on fuzzy graphs that allows for capturing the imprecision of value dependencies, and (iii) an Integer Linear Programming (ILP) model that takes into account user preferences and value dependencies identified from those preferences to reduce the risk of value loss in software projects. Our work is verified by studying a real-world software project. The results show that our proposed method reduces the value loss in software projects and is scalable to large requirement sets.Comment: arXiv admin note: text overlap with arXiv:2003.0480

    Replan: Release planning for agile development

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    Release Planning methodologies have made possible that project managers and users in general can plan project’s releases. These methods try to automatize the human-based planning processes. Currently they are a few web-based and stand-alone tools about release planning, but not all of them offer the same functionalities, like the update of an already planned release or a detailed plan expressed in a timeline. Moreover, these systems are oriented to stakeholders criteria, without taking enough consideration to the available resources. This becomes a limitation, because in many occasions it is vital to have a temporal planning of a release. It also affects key aspects like the planning efficiency or the speed at which it is executed. In this project a web-based release planning tool has been developed. In this tool, users can create a release with different entities in an easy and simple way. The tool is based in a mathematical model that generates an scheduled plan as tight as possible to the available time and resources. On the other hand, the tool also guarantees the priority fulfillment of features, by respecting the temporal criteria that the user could establish. The system is also modular, as it can be integrated with other possible different visualizations. Its development in a cloud server also provides public access and scalability. The tests performed to the system show that the presented mathematical model guarantees the scheduled and efficient planning of a project’s release

    How to Place Your Apps in the Fog -- State of the Art and Open Challenges

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    Fog computing aims at extending the Cloud towards the IoT so to achieve improved QoS and to empower latency-sensitive and bandwidth-hungry applications. The Fog calls for novel models and algorithms to distribute multi-service applications in such a way that data processing occurs wherever it is best-placed, based on both functional and non-functional requirements. This survey reviews the existing methodologies to solve the application placement problem in the Fog, while pursuing three main objectives. First, it offers a comprehensive overview on the currently employed algorithms, on the availability of open-source prototypes, and on the size of test use cases. Second, it classifies the literature based on the application and Fog infrastructure characteristics that are captured by available models, with a focus on the considered constraints and the optimised metrics. Finally, it identifies some open challenges in application placement in the Fog

    Optimizing the Prioritization of Natural Disaster Recovery Projects

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    Prioritizing reconstruction projects to recover a base from a natural disaster is a complicated and arduous process that involves all levels of leadership. The project prioritization phase of base recovery has a direct affect on the allocation of funding, the utilization of human resources, the obligation of projects, and the overall speed and efficiency of the recovery process. The focus of this research is the development of an objective and repeatable process for optimizing the project prioritization phase of the recovery effort. This work will focus on promoting objectivity in the project prioritizing process, improving the communication of the overall base recovery requirement, increasing efficiency in utilizing human and monetary resources, and the creation of a usable and repeatable decision-making tool based on Value-Focused Thinking and integer programming methods
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