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Release planning is part of iterative software development and strongly impacts the success of a product by providing a roadmap for future releases. As such, it is of key importance for lean and agile organizations. Often features are highly dependent on each other and the value of a release is influenced by a set of bundled features constituting a theme.This paper addresses the topic of theme-based release planning. Themes might be defined, manually, upfront or as the result of computer-based analysis. In this paper, we propose an analytical approach to detect themes from a given set of feature dependencies. On top of an existing release planning methodology called EVOLVE II, our approach applies clustering performed on a feature dependency graph. The release plans generated from such an approach are a balance between two goals: (i) considering the values of individual features, (ii) detecting and utilizing synergy effects between semantically related features.As a proof-of-concept, we present a case study addressing the theme-based release planning for 50 features of a text processing system. The preliminary evaluation results show improved release plans with regards to accommodating themes.

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Given the strategic importance of energy and air pollution in the today world and due to the fact that the maritime transport system is one of the main sources of energy consumption and emissions in the environment, particularly contamination of water, so in recent years, fuel consumption and emissions reduction in the maritime transport industry has received considerable attention. Thus, in this paper, a new method is provided for typical boat hybridization, so by adding an electric motor and battery to boat power transmission system, dynamic performance will improve fuel consumption and emissions reduces. For this purpose, power transmission system elements are modelled and boat function is evaluated in real terms of movement by defining energy management strategy between power sources. The simulation results show that boat hybridization considerably reduces fuel consumption and emissions.