The allocation of tasks can be seen as a success-critical management activity in distributed development projects. However, such task allocation is still one of the major challenges in global software development due to an insufficient understanding of the criteria that influence task allocation decisions. This article presents a qualitative study aimed at identifying and understanding such criteria that are used in practice. Based on interviews with managers from selected software development organizations, criteria currently applied in industry are identified. One important result is, for instance, that the sourcing strategy and the type of software to be developed have a significant effect on the applied criteria. The article presents the goals, design, and results of the study as well as an overview of related and future work.
The allocation of development tasks to sites is one of the most important activities in the management of global software development projects. Its various influences on the risks and benefits of distributed projects require careful consideration of multiple allocation criteria in a systematic way. In practice, however, work is often allocated based on only one single criterion such as cost, and defined processes or algorithms for task allocation are typically not used.Existing research approaches mainly focus on selected aspects such as the minimization of crosssite communication and are difficult to adapt to specific environments. This article presents a customizable multi-criteria model for task allocation in global software development projects.Based on an analysis of the state of the practice, a set of requirements was derived and used for evaluating existing task allocation models from different domains. The Bokhari algorithm was identified as a suitable starting point and modified with respect to the fulfillment of the requirements. The modification includes the development of mechanisms for customization, the incorporation of cause-effect relationships, and the use of probabilistic modeling of uncertainty with Bayesian networks. The application of the model is demonstrated in different scenarios that represent typical hypothetical and real distribution decision problems in industrial contexts.Experience from applying the model to such problems has shown, for instance, that depending on the weight of different criteria, very different task distributions will result. This demonstrates, in consequence, the need for systematic multi-criteria task allocation support in global software development.
Distributing development tasks in the context of global software development bears both many risks and many opportunities. Nowadays, distributed development is often driven by only a few factors or even just a single factor such as workforce costs. Risks and other relevant factors such as workforce capabilities, the innovation potential of different regions, or cultural factors are often not recognized sufficiently. This could be improved by using empirically-based multi-criteria distribution models. Currently, there is a lack of such decision models for distributing software development work. This article focuses on mechanisms for such decision support. First, requirements for a distribution model are formulated based on needs identified from practice. Then, distribution models from different domains are surveyed, compared, and analyzed in terms of suitability. Finally, research questions and directions for future work are given.
Today, software-intensive systems are increasingly being developed in a globally distributed way. However, besides its benefit, global development also bears a set of risks and problems. One critical factor for successful project management of distributed software development is the allocation of tasks to sites, as this is assumed to have a major influence on the benefits and risks. We introduce a model that aims at improving management processes in globally distributed projects by giving decision support for task allocation that systematically regards multiple criteria. The criteria and causal relationships were identified in a literature study and refined in a qualitative interview study. The model uses existing approaches from distributed systems and statistical modeling. The article gives an overview of the problem and related work, introduces the empirical and theoretical foundations of the model, and shows the use of the model in an example scenario.
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