Software Engineering and Formal Methods - 17th International Conference, SEFM 2019, Oslo, Norway, September 18-20, 2019, Proceedings
Software Engineering and Formal Methods - 17th International Conference, SEFM 2019, Oslo, Norway, September 18-20, 2019, Proceedings
复制标题
软件工程和形式化方法 - 第 17 届国际会议，SEFM 2019，挪威奥斯陆，2019 年 9 月 18-20 日，论文集
DOI：
10.1007/978-3-030-30446-1_14
复制
发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Foster M
中科院分区：
文献类型：
--
作者：
Foster M
模型是理解软件系统的重要途径。如果它们还不存在，那么我们需要从系统行为中推断它们。大多数当前的方法推断经典FSM模型不考虑数据，因此限制了适用性。EFSMs提供了一种简洁地对具有内部状态的系统建模的方法，但现有的推理技术要么不能推断出允许从输入计算输出的模型，要么严重依赖全面的白盒跟踪来揭示内部程序状态，这通常是不可用的。在本文中，我们提出了一种推断EFSM模型的方法，包括修改内部状态的函数。我们的技术使用黑盒跟踪，其中只包含系统外部观察者可见的信息。我们以原型的形式实现了我们的方法。
Models are an important way of understanding software systems. If they do not already exist, then we need to infer them from system behaviour. Most current approaches infer classical FSM models that do not consider data, thus limiting applicability. EFSMs provide a way to concisely model systems with an internal state but existing inference techniques either do not infer models which allow outputs to be computed from inputs, or rely heavily on comprehensive white-box traces to reveal the internal program state, which are often unavailable.In this paper, we present an approach for inferring EFSM models, including functions that modify the internal state. Our technique uses black-box traces which only contain information visible to an external observer of the system. We implemented our approach as a prototype.