Improvements for concurrent call-by-need functional programming languages.

该项目的最高目标是在并发按需调用函数式编程语言w.r.t.中验证转换的K-改进属性。不同的成本函数（例如时间和空间）。 为了实现这一目标，我们必须开发理论和实践工具来识别K-改进并验证相应的属性。 一个特殊的挑战是并发性，因为在非常早期的阶段，呼叫按需计算的基础和工具的发展。 一个特殊的功能是内在的按需调用共享，它自动允许冗余免费评估，但同时对正确性和优化证明提出了很高的要求该项目的机会是：1.基于直觉和经验的K-优化实际上可以表示为各种代价函数的K-优化。2. 在确定性场景中的K-优化可以被证明在并发情况下也是优化的。3.新的和理论上成立的优化变体，也w.r.t. 时间和空间以及可能的其他成本的组合对于最优地利用计算资源可能有很大帮助，并且也可以被标记为保证。

The top goal of the project are validations of K-improvement properties of transformations in concurrent call-by-need functional programming languages w.r.t. different cost functions (for example time and space). To reach this goal, we have to develop theoretical and practical tools to recognize K-improvements and to verify the corresponding properties. A special challenge is concurrency, since the development of the foundation and tools for call-by-need calculiis in a very early stage. A special feature is the inherent sharing in call-by-need, which automatically permits redundancy free evaluations, but at the same time makes high demands on correctness and optimization-proofsThe chances of the project are: 1. intuition- and experience-based K-optimizations can be really shown as K-optimizations for various cost functions. 2. K-optimizations in the deterministic scenario could be proved to be optimizing also under concurrency. 3. Novel and theoretically founded optimization variants, also w.r.t. combinations of time and space and perhaps other costs can be of great help to optimally utilize the computing resource and could also be labeled with a guarantee.