loadrunner工具的使用,最关键的在于3个地方:

A:脚本的编写

B:场景设计

C:性能测试结果分析

其 中难度比较大的第一步是:编写脚本,有很多人对于loadrunner里面的各种函数使用的并不熟练,理解也不透彻,导致各种翻阅资料也找不到正解,耽误 了学习的时间。所以最近这段时间,华华会把loadrunner里面的一系列函数都会写出来,给大家答疑解惑:今天我们的主角 是:web_reg_save_param

函数名:web_reg_save_param()

1:首先我们通过函数助手:F1键,可以帮我们召唤出函数助手。我们输入web_reg_save_param(),查看这个函数的注释:

aaarticlea/png;base64,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" alt="" />

函数的作用是从响应结果里面获取指定的内容。

用法:

   web_reg_save_param("outFlightVal",
    "LB=", "RB=", LAST );

1:LB表示左边界,RB表示右边界

2:这个是预注册函数,顾名思义。如果你要查找指定的字符内容,那么请放在你的请求之前。因为他是从http请求的响应结果里面去查找内容。

3:请自行补充什么是HTTP请求 以及HTTP响应,有助于自己理解第2点内容。

4:什么是左右边界,我们通过如下代码来进行演示:

  <meta content="nnMfhFk2-jzizMjXGdiGWSZu8j2sDj5TmDSw" name="csrf-token">

比如说我们要获取‘nnMfhFk2-jzizMjXGdiGWSZu8j2sDj5TmDSw’这段内容,

左边界是:meta content="

右边界是:“name=

5:左右边界一定要是唯一的,这样才能帮我们唯一的找到这个值,否则返回的就是数组类型哦!

实战:

1:地址:http://127.0.0.1:1080/webtours/

2:操作:打开网页,获取登录所需的session

3:因为登录的时候,需要Usersession的内容,我们通过抓包或者是查看源码,可以得到Usersession所在的位置:

<input type=hidden name=userSession value=124084.062616444zDicfHDpQHAiDDDDDicQfpttDicf>

红色的字体部分就是我们所想要的内容。

左边界是:name=userSession value=

右边界是:>

4:脚本如下:

Action()
{
    web_reg_save_param("session",
        "LB=name=userSession value=",
        "RB=>",
        LAST);     web_url("web_url",
        "URL=http://127.0.0.1:1080/webtours/nav.pl?in=home",
        "TargetFrame=",
        "Resource=0",
        "Referer=",
        LAST);     //打印获取到的session值
    lr_output_message(lr_eval_string("{session}"));
    return 0;
}

5:运行脚本,结果如下所示:

aaarticlea/png;base64,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" alt="" />

下一节,我们来介绍下预注册函数 web_reg_save_param()函数获取的关联值跟登录结合的用法。

loadrunner函数解密之web_reg_save_param的更多相关文章

  1. loadrunner函数解密之web_reg_find

    loadrunner工具的使用,最关键的在于3个地方: A:脚本的编写 B:场景设计 C:性能测试结果分析 其中难度比较大的第一步是:编写脚本,有很多人对于loadrunner里面的各种函数使用的并不 ...

  2. LoadRunner 函数大全之中文解释

    LoadRunner 函数大全之中文解释 // sapgui_table_set_column_selected 模拟用户 // 单击表中的列标题. int sapgui_table_set_colu ...

  3. LoadRunner函数示例:lr_paramarr_random()

    lr_paramarr_random()函数的作用为:从一个参数数组中随机抽取一个值并以字符串形式返回.其使用方式及返回方式如下: char * lr_paramarr_random( const c ...

  4. LoadRunner函数的介绍

    LoadRunner函数的介绍 LoadRunner函数 一:通用函数 LoadRunner的通用函数以lr为前缀,可以在任何协议中使用.可以如下分类: 信息相关的函数: lr_error_messa ...

  5. LoadRunner函数百科叒叒叒更新了!

    首先要沉痛通知每周四固定栏目[学霸君]由于小编外派公干,本周暂停. 那么这周就由云层君来顶替了,当然要要说下自己做的内容啦,DuangDuang! <LoadRunner函数百科>更新通知 ...

  6. JS的eval函数解密反混淆

    https://www.hhtjim.com/js-decryption-de-obfuscate-eval-function.html JS的eval函数解密反混淆

  7. myeclipse调用loadrunner函数开发测试脚本

    myeclipse调用loadrunner函数开发测试脚本 一.使用myeclipse开发性能测试脚本 1.使用Eclipse新建一个Java工程,将目录%LoadRunner_Home%\class ...

  8. LoadRunner函数大全之中文解释

    LoadRunner函数大全之中文解释

  9. 软件测试中LoadRunner函数中的几个陷阱

    软件测试 中 LoadRunner 函数中的几个陷阱 1.atof 在 loadrunner 中如果直接用 float f; f=atof("123.00"); lr _outpu ...

随机推荐

  1. caffe配置NCCL

    设置Makefile.config 打开开关: USE_NCCL := 1, 并添加nccl库路径 USE_NCCL := 1 INCLUDE_DIRS += /path/nccl/build/inc ...

  2. map()实现zip()功能

    c = (map(lambda x,y:(x,y),[1,2,3],["abd","def","ghi"]))print(list(c)) ...

  3. if --else的注意点

  4. tomcat 查看和修改内存

    为了解决tomcat在大进行大并发请求时,出现内存溢出的问题,请修改tomcat的内存大小,其中分为以下两种方式: 一.使用 catalina.bat 等命令行方式运行的 tomcat 查看系统最大支 ...

  5. Redis无法保存ef复杂对象

    最近项目需要使用redis. 然后我就满怀激情开始处理数据层了.在原来查询数据的基础上,有封装了一个redis缓存层. 结果在redis保存ef对象的时候,发现了一个非常尴尬的问题. model: p ...

  6. hihocoder #1236 Scores (15北京赛区网络赛J) (五维偏序,强制在线,bitset+分块)

    链接:http://hihocoder.com/problemset/problem/1236 思路; 有n个五维的向量,给出q个询问,每个询问是一个五维向量,问有多少个向量没有一维比这个向量大.并且 ...

  7. adb is down 的解决方法

    今天装完android Eclipse 之后 ,运行时报出这么个错误 : The connection to adb is down, and a severe error has occured.  ...

  8. 洛谷 P4100 [HEOI2013]钙铁锌硒维生素 解题报告

    P4100 [HEOI2013]钙铁锌硒维生素 题目描述 银河队选手名单出来了!小林,作为特聘的营养师,将负责银河队选手参加 宇宙比赛的饮食. 众所周知,前往宇宙的某个星球,通常要花费好长好长的时间, ...

  9. 【洛谷P2261】余数求和

    题目大意:给定 n, k,求\(\sum\limits_{i=1}^n k\%n\) 的值. 题解:除法分块思想的应用. \(x\%y=x-y\lfloor {x\over y}\rfloor\),因 ...

  10. poj 2763(RMQ+BIT\树链剖分)

    传送门:Problem 2763 https://www.cnblogs.com/violet-acmer/p/9686774.html 题意: 一对夫妇居住在xx村庄,小屋之间有双向可达的道路,不会 ...