The Experts below are selected from a list of 443340 Experts worldwide ranked by ideXlab platform
Ioannamaria Attarian - One of the best experts on this subject based on the ideXlab platform.
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a goal driven framework for Software Project data analytics
Conference on Advanced Information Systems Engineering, 2013Co-Authors: George Chatzikonstantinou, Kostas Kontogiannis, Ioannamaria AttarianAbstract:The life cycle activities of industrial Software systems are often complex, and encompass a variety of tasks. Such tasks are supported by integrated environments (IDEs) that allow for Project data to be collected and analyzed. To date, most such analytics techniques are based on quantitative models to assess Project features such as effort, cost and quality. In this paper, we propose a Project data analytics framework where first, analytics objectives are represented as goal models with conditional contributions; second, goal models are transformed to rules that yield a Markov Logic Network (MLN) and third, goal models are assessed by an MLN probabilistic reasoner. This approach has been applied with promising results to a sizeable collection of Software Project data obtained by ISBSG repository, and can yield results even with incomplete or partial data.
Suzanne Rivard - One of the best experts on this subject based on the ideXlab platform.
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Software Project Risk Drivers as Project Manager Stressors and Coping Resources
2011 44th Hawaii International Conference on System Sciences, 2011Co-Authors: Suzanne Rivard, Yannik St-james, Ann-frances CameronAbstract:Although the stressful nature of high risk exposure Software Projects and the adverse repercussions of stress on Project participants and performance have long been recognized, there is still little research on the subject. This paper builds upon two foundations - the cognitive-transactional theory of stress and the concept of Software Project risk exposure - to propose a model of Software Project risk drivers as Software Project manager stressors and coping resources. The model posits that some Software Project risk drivers - core Project characteristics and Project objectives - play the role of stressors and that other risk drivers - Project environment characteristics - play the role of coping resources. The model further suggests that Software Project managers are faced with both chronic stress and acute stress, which have different antecedents. This paper broadens current understanding of the role of Software Project risk drivers; it also contributes to knowledge on Software Project management by focusing on the emotional components this activity.
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specifying the Software Project risk construct
Americas Conference on Information Systems, 2010Co-Authors: Mazen Elmasri, Suzanne RivardAbstract:This paper conceptualizes Software Project risk in terms of risk exposure and defines it as an aggregate multidimensional construct comprised of four interrelated dimensions: risk sources, risk events, risk management mechanisms, and expected outcomes. The paper also theorizes about relationships between the four dimensions. Furthermore, it argues that the risk factors identified in the literature could be systematically categorized using the proposed construct. The specification is derived from a review of 20 years of Software Project risk literature – from 1989 to 2009 and on a semantic decompositional analysis of Software Project risk definitions. The proposed construct conceptualization helps demarcate between the often intertwined behavioural factors and Project attributes recognized risk factors in the literature pertaining to Software Project risk. By identifying the dimensions of risk and their interrelationships, the suggested specification should help improve the construct’s explanatory and predictive power.
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an integrative contingency model of Software Project risk management
Journal of Management Information Systems, 2001Co-Authors: Henri Barki, Suzanne Rivard, Jean TalbotAbstract:Drawing both from the IS literature on Software Project risk management and the contingency research in Organization Theory literature, the present study develops an integrative contingency model of Software Project risk management. Adopting a profile deviation perspective of fit, the outcome of a Software development Project (Performance) is hypothesized to be influenced by the fit between the Project's risk (Risk Exposure) and how Project risk is managed (Risk Management Profile). The research model was tested with longitudinal data obtained from Project leaders and key users of 75 Software Projects. The results support the contingency model proposed and suggest that in order to increase Project performance a Project's risk management profile needs to vary according to the Project's risk exposure. Specifically, high-risk Projects were found to call for high information processing capacity approaches in their management. However, the most appropriate management approach was found to depend on the performance criterion used. When meeting Project budgets was the performance criterion, successful high-risk Projects had high levels of internal integration, as well as high levels of formal planning. When system quality was the performance criterion, successful high-risk Projects had high levels of user participation.
Guilherme Horta Travassos - One of the best experts on this subject based on the ideXlab platform.
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supporting requirements definition and quality assurance in ubiquitous Software Project
Leveraging Applications of Formal Methods, 2008Co-Authors: Rodrigo O Spinola, Felipe C R Pinto, Guilherme Horta TravassosAbstract:The development of ubiquitous Software Project demands the use of specific Software technologies to deal with the inherent complexity of this type of Project. Despite the advances in the Software engineering field, the building of ubiquitous Software still represents a grand challenge. For instance, secondary and primary studies indicated the existence of 13 ubiquity characteristics that can influence ubiquitous Software Projects. Therefore, in this paper we describe these ubiquity characteristics organized into a body of knowledge regarding ubiquitous computing and used to characterize ubiquitous Software Projects. Besides, an ongoing research concerned with supporting ubiquity requirements definition and verification (checklist based inspection) activities is also introduced.
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evaluating Software Project portfolio risks
Journal of Systems and Software, 2007Co-Authors: Helio R Costa, Marcio De Oliveira Barros, Guilherme Horta TravassosAbstract:As in any other business, Software development organizations try to maximize their profits and minimize their risks. The risks represent uncertain events and conditions that may prevent enterprises from attaining their goals, turning risk management into a major concern, not only for Project managers but also for executive officers involved with strategic objectives. In this sense, economical concepts can greatly support Software Engineers in the effort to better quantify the uncertainties of either a single Project or even a Project portfolio. In this paper, we present a technique for evaluating risk levels in Software Projects through analogies with economic concepts. This technique allows a manager to estimate the probability distribution of earnings and losses incurred by an organization in relation to its Software Project portfolio. This approach has been calibrated by data collected in an empirical study, which has been planned and accomplished to provide information about the relative importance of risk factors in Software Projects. A usage example of such an approach is presented. Finally, we introduce a case tool specially built to support the application of the proposed techniques.
Arie Van Deursen - One of the best experts on this subject based on the ideXlab platform.
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how to build a good practice Software Project portfolio
International Conference on Software Engineering, 2014Co-Authors: Hennie Huijgens, Rini Van Solingen, Arie Van DeursenAbstract:What can we learn from historic data that is collected in three Software companies that on a daily basis had to cope with highly complex Project portfolios? In this paper we analyze a large dataset, containing 352 finalized Software engineering Projects, with the goal to discover what factors affect Software Project performance, and what actions can be taken to increase Project performance when building a Software Project portfolio. The Software Projects were classified in four quadrants of a Cost/Duration matrix: analysis was performed on factors that were strongly related to two of those quadrants, Good Practices and Bad Practices. A ranking was performed on the factors based on statistical significance. The paper results in an inventory of ‘what factors should be embraced when building a Project portfolio?’ (Success Factors), and ‘what factors should be avoided when doing so?’ (Failure Factors). The major contribution of this paper is that it analyzes characteristics of best performers and worst performers in the dataset of Software Projects, resulting in 7 Success Factors (a.o. steady heartbeat, a fixed, experienced team, agile (Scrum), and release-based), and 9 Failure Factors (a.o. once-only Project, dependencies with other systems, technology driven, and rules- and regulations driven).
Stefan Biffl - One of the best experts on this subject based on the ideXlab platform.
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Software Project portfolio optimization with advanced multiobjective evolutionary algorithms
Applied Soft Computing, 2011Co-Authors: Thomas Kremmel, Jiří Kubalík, Stefan BifflAbstract:Large Software companies have to plan their Project portfolio to maximize potential portfolio return and strategic alignment, while balancing various preferences, and considering limited resources. Project portfolio managers need methods and tools to find a good solution for complex Project portfolios and multiobjective target criteria efficiently. However, Software Project portfolios are challenging to describe for optimization in a practical way that allows efficient optimization. In this paper we propose an approach to describe Software Project portfolios with a set of multiobjective criteria for portfolio managers using the COCOMO II model and introduce a multiobjective evolutionary approach, mPOEMS, to find the Pareto-optimal front efficiently. We evaluate the new approach with portfolios choosing from a set of 50 Projects that follow the validated COCOMO II model criteria and compare the performance of the mPOEMS approach with state-of-the-art multiobjective optimization evolutionary approaches. Major results are as follows: the portfolio management approach was found usable and useful; the mPOEMS approach outperformed the other approaches.
