Measuring productivity in globally distributed projects is crucial to improve team performance. These measures often display information on whether a given project is moving forward or starts to demonstrate undesired behaviors. In this paper we are interested in showing how analytical models could deliver insights for the behavior of specific distributed software collaboration projects. We present a model for distributed projects using stochastic automata networks (SAN) formalism to estimate, for instance, the required level of coordination for specific project configurations. We focus our attention on the level of interaction among project participants and its close relation with team’s productivity. The models are parameterized for different scenarios and solved using numerical methods to obtain exact solutions. We vary the team’s expertise and support levels to measure the impact on the overall project performance. As results, we present our derived productivity index for all scenarios and we state implications found in order to analyze popular preconceptions in GSD area, confirming some, and refusing others. Finally, we foresee ways to extend the models to represent more intricate behaviors and communication patterns that are usually present in globally distributed software projects.

The emergence of wireless networks has contributed to a growing number of studies and protocols regarding its performance and reliability requirements, among others. Several issues have to be considered when deploying such devices under harsh environmental conditions. These issues often force the designer to adopt decisions that are usually difficult to verify in real world settings. In order to mitigate such problems, an alternative resides in the use of simulation models for both homogeneous and heterogeneous devices. This paper describes an event-based Wireless Network Simulator (WiNeS) for devices operating in several topologies and configurations of networks. WiNeS is a Java-based framework specially built to support customized network options that offers hybrid simulation for virtual and physical nodes in the same environment. Some of WiNeS' features include the computation of maximum communication distances among devices in 2D and 3D spatial node distributions as well as pairing rules to evaluate the nodes connectivity.

Global software engineering is an area of increasing research challenges, in which teams are dispersed in multiple sites collaborating across borders and time zones. In spite of its potential competitive advantages, globally distributed projects must deal with difficulties when distributing resources such as teams with cultural diversities, different skills and experience levels. Both industry and academia demonstrate a special interest in the modeling and prediction, mainly representing systems in order to extract interesting indices, for example, evaluating whether or not a project will succeed. This paper demonstrates the usefulness of analytical modeling techniques in order to predict the outcome of geographically-distributed projects. We focus our attention to the participants interaction and its interplay when it affects team productivity. The models are parametrized considering single-site and multi-site scenarios, varying resources availability, teams expertise and support levels. Performance indices from both scenarios are presented and conclusion indicates possible model extensions.

The solution of state-based stochastic models is usually a demanding application, then it is a natural subject to high performance techniques. We are particularly interested in the speedup of Bootstrap Simulation of structured Markovian models. This approach is a quite recent development in the performance evaluation area, and it brings a considerable improvement in the results accuracy, despite the intrinsic effect of randomness in simulation experiments. Unfortunately, Bootstrap Simulation has higher computational cost than other alternatives. We present experiments with different options to optimize the parallel solution of Bootstrap Simulation applied to three practical examples described in Stochastic Automata Networks (SAN) formalism. This paper contribution resides in the discussion of theoretical implementation issues, the obtained speedup and the actual processing and communication times for all experiments. Additionally, we also suggest future works to improve even more the proposed solution and we discuss some interesting insights for parallelization of similar applications.

New guidelines and methods for teams and organizational structures are crucial to improve efficiency and scalability for globally distributed software development. Our work introduces a simplified process to be used by local teams working globally. The process is derived from the Agile Unified Process proposal and is highly centered in team motivation using game principles