arrow
返回

A dynamic protocol conformance test method

delete2003-07-01
delete4
PRE
AI
M
Myungchul Kim
S
Sang‐Jo Yoo
J
Jinhee Park
S
Sungwon Kang
H
Hyuckjae Lee
DOI:10.1016/s0164-1212(02)00085-7delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
Protocol conformance test is used to promote the interoperability of protocol implementations developed by venders. Non-interoperability between protocol implementations may be caused by ambiguity and/or misinterpretation of protocol specifications by vendors or by different implementations using different options in specifications. The conventional method used for protocol conformance test has been standardized by ISO/IEC JTC1 and ITU-T with the purpose of determining whether a protocol implementation conforms to its specification. However, the conventional method sometimes gives wrong test results because the test is based on static test sequences. This problem is caused by some failed transitions of a protocol's finite state machine included in a test sequence, which have an effect on the test result of transitions to be tested. In this paper, an approach called dynamic conformance test method (DCTM) is proposed to solve this problem. DCTM dynamically selects different test sequences during testing depending on whether alternative paths without failed transitions exist. As a result, the fault coverage of DCTM is better than that of the conventional test method. DCTM has been implemented and applied to the TCP protocol in order to demonstrate its improvement in the fault coverage compared to that of the conventional method. (C) 2002 Elsevier Science Inc. All rights reserved.
AI总结

AI总结

对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。

期刊

Journal of Systems and Software 封面图
Journal of Systems and Software
IF:
4.1
论文数:
5.4K
被引数:
8.4K

机构

暂无机构信息
引用论文

引用论文

High-definition trans cranial direct current stimulation and its effects on cognitive function: a systematic review
err2022-12-17
err0
PREAI
errJaya Shanker Tedla; Devika Rani Sangadala; Ravi Shankar Reddy; Kumar Gular; Snehil Dixit
err分享
err收藏
Online cross‐validation‐based ensemble learning
err2017-05-04
err0
errOAAI
errDavid Benkeser; Cheng Ju; Sam Lendle; Mark van der Laan
err分享
err收藏