A framework for monitored dynamic slicing of reaction systems

IF 1.7 4区 计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Linda Brodo, Roberto Bruni, Moreno Falaschi
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引用次数: 0

Abstract

Reaction systems (RSs) are a computational framework inspired by biochemical mechanisms. A RS defines a finite set of reactions over a finite set of entities. Typically each reaction has a local scope, because it is concerned with a small set of entities, but complex models can involve a large number of reactions and entities, and their computation can manifest unforeseen emerging behaviours. When a deviation is detected, like the unexpected production of some entities, it is often difficult to establish its causes, e.g., which entities were directly responsible or if some reaction was misconceived. Slicing is a well-known technique for debugging, which can point out the program lines containing the faulty code. In this paper, we define the first dynamic slicer for RSs and show that it can help to detect the causes of erroneous behaviour and highlight the involved reactions for a closer inspection. To fully automate the debugging process, we propose to distil monitors for starting the slicing whenever a violation from a safety specification is detected. We have integrated our slicer in BioResolve, written in Prolog which provides many useful features for the formal analysis of RSs. We define the slicing algorithm for basic RSs and then enhance it for dealing with quantitative extensions of RSs, where timed processes and linear processes can be represented. Our framework is shown at work on suitable biologically inspired RS models.

Abstract Image

反应系统监测动态切片框架
反应系统(RS)是一种受生化机制启发的计算框架。一个 RS 定义了一组有限实体上的有限反应。通常情况下,每个反应的范围都是局部的,因为它只涉及一小部分实体,但复杂的模型可能涉及大量的反应和实体,它们的计算可能表现出不可预见的新行为。当发现偏差时,如某些实体的意外产生,通常很难确定其原因,如哪些实体应直接负责,或某些反应是否被误解。切片是一种著名的调试技术,可以指出包含错误代码的程序行。在本文中,我们定义了第一个 RSs 动态切片器,并证明它有助于检测错误行为的原因,并突出显示相关反应,以便进行更仔细的检查。为了使调试过程完全自动化,我们建议在检测到违反安全规范的情况时,提炼出启动切片的监控器。我们已将切片器集成到用 Prolog 编写的 BioResolve 中,它为 RS 的形式分析提供了许多有用的功能。我们为基本 RS 定义了切片算法,然后对其进行了改进,以处理 RS 的定量扩展,其中可以表示定时过程和线性过程。我们的框架已在合适的生物灵感 RS 模型中得到应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Natural Computing
Natural Computing Computer Science-Computer Science Applications
CiteScore
4.40
自引率
4.80%
发文量
49
审稿时长
3 months
期刊介绍: The journal is soliciting papers on all aspects of natural computing. Because of the interdisciplinary character of the journal a special effort will be made to solicit survey, review, and tutorial papers which would make research trends in a given subarea more accessible to the broad audience of the journal.
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