计算机工程 ›› 2018, Vol. 44 ›› Issue (6): 270-278.doi: 10.19678/j.issn.1000-3428.0049612

• 开发研究与工程应用 • 上一篇    下一篇

基于OCL约束建模的嵌入式软件安全性分析

崔红军,黄美锋,吴振宇   

  1. 中国电子科技集团公司第三十二研究所,上海 201808
  • 收稿日期:2017-12-08 出版日期:2018-06-15 发布日期:2018-06-15
  • 作者简介:崔红军(1974—),男,高级工程师,主研方向为软件测评;黄美锋,高级工程师;吴振宇,工程师。
  • 基金项目:
    国家部委基金。

Embedded Software Safety Analysis Based on OCL-constraint Modeling

CUI Hongjun,HUANG Meifeng,WU Zhenyu   

  1. The 32nd Research Institute of China Electronics Technology Group Corporation,Shanghai 201808,China
  • Received:2017-12-08 Online:2018-06-15 Published:2018-06-15

摘要: 目前已有多种模型驱动的软件安全性分析方法用于识别软件失效模式和系统危险,但较少将软件安全性约束与模型相结合,难以保证分析充分性与效率。针对该问题,基于对象约束语言(OCL)设计嵌入式软件安全性分析方法。借助OCL表达式对安全性相关的约束关系进行建模,形成OCL约束模型,并将其融入UML模型。在此基础上,结合嵌入式软件特点,依据约束违背原则进行失效模式识别。在某嵌入式发动机控制软件上的应用结果表明,该方法可自动识别软件失效模式,提高模型驱动安全性分析的充分性与效率,同时降低分析工作量。

关键词: 对象约束语言, 约束建模, 软件安全性分析, 失效模式, 模型驱动

Abstract: At present,many model-driven software safety analysis approaches have been proposed to identify the software failure modes and system hazards of the software products.However,these existing approaches do not integrate the safety constraint into the corresponding models,which can not ensure the analysis effectiveness and sufficiency.To solve the above problems,the safety analysis approach for the embedded software based on the Object Constraint Language(OCL) is proposed in this paper.The constraints related to the safety is described by the OCL representation to obtain the OCL-constraint model for integrating the safety constraint into the UML model.On this basis,considering the characters of embedded software,the failure mode is idenitified.This apporach is applied on the embedded engine control software to illustrate its effectiveness and feasibility.The experimental results show that it can identify the failure modes automatically and improve the effectiveness and sufficiency of the model-driven safety analysis as well as reduce the analysis effort.

Key words: Object Constraint Language(OCL), constraint modeling, software safety analysis, failure mode, model-driven

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