949 resultados para software project


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Requirements Engineering (RE) has received much attention in research and practice due to its importance to software project success. Its inter-disciplinary nature, the dependency to the customer, and its inherent uncertainty still render the discipline diffcult to investigate. This results in a lack of empirical data. These are necessary, however, to demonstrate which practically relevant RE problems exist and to what extent they matter. Motivated by this situation, we initiated the Naming the Pain in Requirements Engineering (NaPiRE) initiative which constitutes a globally distributed, bi-yearly replicated family of surveys on the status quo and problems in practical RE.

In this article, we report on the analysis of data obtained from 228 companies in 10 countries. We apply Grounded Theory to the data obtained from NaPiRE and reveal which contemporary problems practitioners encounter. To this end, we analyse 21 problems derived from the literature with respect to their relevance and criticality in dependency to their context, and we complement this picture with a cause-effect analysis showing the causes and effects surrounding the most critical problems.

Our results give us a better understanding of which problems exist and how they manifest themselves in practical environments. Thus, we provide a rst step to ground contributions to RE on empirical observations which, by now, were dominated by conventional wisdom only.

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Requirement engineering is a key issue in the development of a software project. Like any other development activity it is not without risks. This work is about the empirical study of risks of requirements by applying machine learning techniques, specifically Bayesian networks classifiers. We have defined several models to predict the risk level for a given requirement using three dataset that collect metrics taken from the requirement specifications of different projects. The classification accuracy of the Bayesian models obtained is evaluated and compared using several classification performance measures. The results of the experiments show that the Bayesians networks allow obtaining valid predictors. Specifically, a tree augmented network structure shows a competitive experimental performance in all datasets. Besides, the relations established between the variables collected to determine the level of risk in a requirement, match with those set by requirement engineers. We show that Bayesian networks are valid tools for the automation of risks assessment in requirement engineering.

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Doutoramento em Gestão

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BACKGROUND: Computer simulations are of increasing importance in modeling biological phenomena. Their purpose is to predict behavior and guide future experiments. The aim of this project is to model the early immune response to vaccination by an agent based immune response simulation that incorporates realistic biophysics and intracellular dynamics, and which is sufficiently flexible to accurately model the multi-scale nature and complexity of the immune system, while maintaining the high performance critical to scientific computing. RESULTS: The Multiscale Systems Immunology (MSI) simulation framework is an object-oriented, modular simulation framework written in C++ and Python. The software implements a modular design that allows for flexible configuration of components and initialization of parameters, thus allowing simulations to be run that model processes occurring over different temporal and spatial scales. CONCLUSION: MSI addresses the need for a flexible and high-performing agent based model of the immune system.

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This research was undertaken with an objective of studying software development project risk, risk management, project outcomes and their inter-relationship in the Indian context. Validated instruments were used to measure risk, risk management and project outcome in software development projects undertaken in India. A second order factor model was developed for risk with five first order factors. Risk management was also identified as a second order construct with four first order factors. These structures were validated using confirmatory factor analysis. Variation in risk across categories of select organization / project characteristics was studied through a series of one way ANOVA tests. Regression model was developed for each of the risk factors by linking it to risk management factors and project /organization characteristics. Similarly regression models were developed for the project outcome measures linking them to risk factors. Integrated models linking risk factors, risk management factors and project outcome measures were tested through structural equation modeling. Quality of the software developed was seen to have a positive relationship with risk management and negative relationship with risk. The other outcome variables, namely time overrun and cost over run, had strong positive relationship with risk. Risk management did not have direct effect on overrun variables. Risk was seen to be acting as an intervening variable between risk management and overrun variables.

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Software Engineering Team project introductory lecture and project start up for 2014-2015. it covers team working, infrastructure tools, and an outline of the agile methods, practices and principles that will be used.

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Managing software maintenance is rarely a precise task due to uncertainties concerned with resources and services descriptions. Even when a well-established maintenance process is followed, the risk of delaying tasks remains if the new services are not precisely described or when resources change during process execution. Also, the delay of a task at an early process stage may represent a different delay at the end of the process, depending on complexity or services reliability requirements. This paper presents a knowledge-based representation (Bayesian Networks) for maintenance project delays based on specialists experience and a corresponding tool to help in managing software maintenance projects. (c) 2006 Elsevier Ltd. All rights reserved.

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BACKGROUND : Project Based Learning (PBL) allows students to learn by doing hands on work and thus also again practical skills. Therefore going to software simulation may seem like a backwards step. However, the opportunity presented itself to create a unit on Artificial intelligence (AI). This lends itself it a software approach. An added benefit was the opportunity to create a PBL AI unit for both Engineering and IT students.

PURPOSE : Can Project Based Learning be improved with dedicated, specifically written, software design?

DESIGN/METHOD : After introducing a dedicated software package the student marks and student feedback for the AI unit for a few years before the package introduction until the most recent year was analysed. In the student surveys, 2 key questions where examined: unit material quality and feedback to students. Student comments were also studied.

RESULTS : Student surveys gave a consistently high mark for unit’s material and student marks seems consistent as well but favourable comments increased. The most significant result was that the students’ thoughts about the project feedback had increased significantly, probably due to the inbuilt feedback system in the dedicated software package.

CONCLUSIONS : With an appropriate subject matter a dedicated software package can help students in PBL. Student enjoyment increased which, in turn, increased their motivation.

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This article presents software architecture for a web-based system to aid project managing, conceptually founded on guidelines of the Project Management Body of Knowledge (PMBoK) and on ISO/IEC 9126, as well as on the result of an empiric study done in Brazil. Based on these guidelines, this study focused on two different points of view about project management: the view of those who develop software systems to aid management and the view of those who use these systems. The designed software architecture is capable of guiding an incremental development of a quality system that will satisfy today's marketing necessities, principally those of small and medium size enterprises.

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[EN]One of the main issues of the current education system is the lack of student motivation. This aspect together with the permanent change that the Information and Communications Technologies involve represents a major challenge for the teacher: to continuously update contents and to keep awake the student’s interest. A tremendously useful tool in classrooms consists on the integration of projects with participative and collaborative dynamics, where the teacher acts mainly as a guidance to the student activity instead of being a mere knowledge and evaluation transmitter. As a specific example of project based learning, the EDUROVs project consists on building an economic underwater robot using low cost materials, but allowing the integration and programming of many accessories and sensors with minimum budget using opensource hardware and software.

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Software evolution research has focused mostly on analyzing the evolution of single software systems. However, it is rarely the case that a project exists as standalone, independent of others. Rather, projects exist in parallel within larger contexts in companies, research groups or even the open-source communities. We call these contexts software ecosystems, and on this paper we present The Small Project Observatory, a prototype tool which aims to support the analysis of project ecosystems through interactive visualization and exploration. We present a case-study of exploring an ecosystem using our tool, we describe about the architecture of the tool, and we distill the lessons learned during the tool-building experience.

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When project managers determine schedules for resource-constrained projects, they commonly use commercial project management software packages. Which resource-allocation methods are implemented in these packages is proprietary information. The resource-allocation problem is in general computationally difficult to solve to optimality. Hence, the question arises if and how various project management software packages differ in quality with respect to their resource-allocation capabilities. None of the few existing papers on this subject uses a sizeable data set and recent versions of common software packages. We experimentally analyze the resource-allocation capabilities of Acos Plus.1, AdeptTracker Professional, CS Project Professional, Microsoft Office Project 2007, Primavera P6, Sciforma PS8, and Turbo Project Professional. Our analysis is based on 1560 instances of the precedence- and resource-constrained project scheduling problem RCPSP. The experiment shows that using the resource-allocation feature of these packages may lead to a project duration increase of almost 115% above the best known feasible schedule. The increase gets larger with increasing resource scarcity and with increasing number of activities. We investigate the impact of different complexity scenarios and priority rules on the project duration obtained by the software packages. We provide a decision table to support managers in selecting a software package and a priority rule.