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找到约 10,000 项符合「Testing」的源代码

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m contents.m

% Higher-Order Spectral Analysis Toolbox - Demo suite % Version 2.0.3 (R12 compliant) 27 Dec 2000 % % hosademo : main demo file % all other .m files in this directory are invoked by hosademo
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txt 测试 英文简历.txt

熟悉C、C++、 DELPHI程序设计语言; Proficient in program language, such as C, C++, and Delphi. 熟悉MS SQL 、了解Oracle数据库; Be familiar with MS SQL and Oracle. 精通测试理论和测试技术,熟悉测试流程 ; Proficient in software qu
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txt readme.txt

This directory contains the (fledgling) test suite for Expat. The tests provide general unit testing and regression coverage. The tests are not expected to be useful examples of Expat usage; see t
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bas module.bas

Attribute VB_Name = "Module1" ' This sample application and corresponding sample code is provided ' for example purposes only. It has not undergone rigorous testing ' and as such should not be shi
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m contents.m

% Higher-Order Spectral Analysis Toolbox - Demo suite % Version 2.0.3 (R12 compliant) 27 Dec 2000 % % hosademo : main demo file % all other .m files in this directory are invoked by hosademo
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pcf chicago.pcf

; This file is used to configure the ; ; ******************************************************************* ; KEYWORK DISCRIPTION: ; ********************************************************
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pcf klm.pcf

; This file is used to configure the ; ; ******************************************************************* ; KEYWORK DISCRIPTION: ; ********************************************************
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c svmclass2.c

/* -------------------------------------------------------------------- [pred_labels, dec_fun] = svmclass2( tst_data, trn_data, trn_labels, alpha, bias, ker, arg ) Evaluate SVM decision functio
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c~ svmclass2.c~

/* -------------------------------------------------------------------- [pred_labels, dec_fun] = svmclass2( tst_data, trn_data, trn_labels, alpha, bias, ker, arg ) Evaluate SVM decision function.
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c svmclass2.c

/* -------------------------------------------------------------------- [pred_labels, dec_fun] = svmclass2( tst_data, trn_data, trn_labels, alpha, bias, ker, arg ) Evaluate SVM decision functio