FLASH: Fitness Landscape Analysis to improve Search Heuristics - A Systematic Exploration for different Software Engineering Problems

许多软件工程任务可以表述为优化问题，并且可以使用不同的搜索启发式/算法自动解决。典型的软件工程问题的例子，可以使用优化方法，包括需求优先级划分、发布计划、架构和设计优化、自动程序修复、测试套件生成和扩展，以及测试用例选择和优先级划分。然而，对于这些问题中的大多数，通常不知道搜索空间和适应度的特征，这导致算法选择基于跟踪和错误。此外，搜索空间可以是多种多样的，并且可能因问题实例而异。更好地理解不同的搜索问题将导致更好的算法选择和参数调优。因此，FLASH项目旨在进行系统的描述性研究，对健身景观进行分类。这些知识将用于改进针对不同软件工程问题的启发式搜索。将进行实验验证，以经验证明在设计时和运行时对不同搜索空间的深入理解将有助于改进现有的最先进算法。研究的核心挑战将是：(1)有效地提取软件工程中不同复杂问题的适应度景观信息；(2)有效地、自动地改进应用搜索算法以解决特定问题。

Many software engineering tasks can be formulated as optimisation problems and can be automatically solved with different search heuristics/algorithms. Examples for typical software engineering problems, where optimisation methods can be used, are requirements prioritisation, release planning, architecture and design optimisation, automatic program repair, test suite generation and augmentation, and test case selection and prioritisation. However, for most of these problems the characteristics of the search space and fitness landscape are usually not known, which leads to algorithm selection on a trail-and-error basis. Furthermore, search spaces can be diverse and may also vary from problem instance to problem instance. A better understanding of the different search problems will lead to better algorithm selection and parameter tuning. Consequently, the FLASH project aims to perform a systematic descriptive study to classify fitness landscapes. This knowledge will be used to improve search heuristics for different software engineering problems. An experimental validation will be performed to empirically demonstrate that a deep understanding of the different search spaces at design-time and at runtime will help to improve existing state-of-the-art algorithms.The central research challenges will be (1) to efficiently extract information about the fitness landscapes for different complex problems in software engineering, and (2) to effectively and automatically improve the applied search algorithms to solve specific problems.