Maintaining large code bases can be a challenging endeavour. As new libraries, APIs and standards are introduced, old code is migrated to use them. To provide as clean and succinct an interface as possible for developers, old APIs are ideally removed as new ones are introduced. In practice, this becomes difficult as automatically finding and transforming code in a semantically correct way can be challenging, particularly as the size of a code base increases. In this paper, we present a real-world implementation of a system to refactor large C++ code bases efficiently. A combination of the Clang compiler framework and the MapReduce parallel processor, ClangMR enables code maintainers to easily and correctly transform large collections of code. We describe the motivation behind such a tool, its implementation and then present our experiences using it in a recent API update with Google's C++ code base.

Carbon nanotubes (CNTs) are one of the most promising materials for nanoelectronic applications. Before bringing CNTs into large-scale production, a reliable nanorobotic system for automated handling and characterization as well as prototyping of CNT-based components is essential. This paper presents the NanoLab setup, a nanorobotic system that combines specially developed key components such as electrothermal microgrippers and mobile microrobots inside a scanning electron microscope. The working principle and fabrication of mobile microrobots and electrothermal microgripper as well as their interaction and integration is described. Furthermore, the NanoLab is used to explore novel key strategies such as automated locating of CNTs for pick-and-place handling and methods for electrical characterization of CNTs. The results have been achieved within the framework of a European research project where the scientific knowledge will be transfered into an industrial system that will be commercially available for potential customers.

This paper describes a new position tracking system that uses the scanning electron microscope as a fast, high-resolution sensor system. The position tracking system works similar to an optical encoder using a specially structured pattern as scale. Thus, with low computational overhead, an accuracy below 10 nm is achieved in a tungsten cathode-based microscope. The tracking system is virtually immune to changes in contrast, brightness, magnification and, to a certain extend, to defocusing. With a customized, external scan generator and scanning algorithm, the bottleneck of image acquisition can be bypassed and the position tracking system can reach update rates of more than 1 kHz. Furthermore, measurements can be conducted over long working ranges of up to 200 mum without losing precision.

This paper presents the detailed design of a nanohandling robot cell that can work inside an SEM's vacuum chamber and incorporates miniature video microscopes in order to enable fully automated nanohandling and -assembly. The geometrical and mechanical requirements are defined and addressed in a modular implementation. Image processing techniques can be used to recognize and track objects and three dimensional information can be obtained by stereo vision as well as the microscope's focus. To control this highly heterogeneous system, different low-level controllers are used, challenges for cooperatively controlling the multi-robot system are outlined, and high-level automation is discussed.