Domain Testing: Divide and Conquer - Testing Education

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There have been several discussions in the literature about the relative merits of partition testing and pure random testing. Pure random testing is not random selection of test cases from subdomains, but is just random selection of test cases from the entire input domain without forming any partitions. Random and partition testing have been found to be better than each other under certain conditions, and the two are almost equivalent under certain other conditions. Proportional partition testing has mostly been discussed as a method that evolved in order to improve partition testing and to make its effectiveness at finding failures greater than that of random testing. Weyuker and Jeng (1991) noted that when the original partition testing method is refined so that we form all subdomains of equal size and then select an equal number of test cases from each subdomain, pure random testing can never beat partition testing in terms of effectively finding failures. This is assuming that either the number of subdomains formed is very large or the number of test cases chosen from each subdomain is very large compared to the size of the subdomain itself. Chan et al. (1998) cited a modified version of the proportional partition testing method that somewhat blends the refined version of partition testing described by Weyuker and Jeng (1991) with the traditional proportional partition testing method. Chan et al. (1998) called their method the Optimally Refined Proportional Sampling (ORPS) strategy. This method involves partitioning the input domain into equally sized partitions as described by Weyuker and Jeng (1991), and then selecting one test case at random from each equally sized subdomain. Chan et al. (1998) noted that the results of trying out their ORPS strategy on several programs seemed positive enough to recommend this method as a subdomain testing strategy. Ntafos (1998) has illustrated an experiment in which he compared random testing with proportional partition testing. When doing proportional partition testing, he considered 50 subdomains. He applied the two strategies to 50 test cases to start with, and then increased to 2,000 total test cases in increments of 50 cases. 26
He referred to the number of test cases as n, the probability of detecting at least one failure in subdomain i as Pi and the number of subdomains as k. Ntafos (1998) found the following: The experiment was repeated 1,000 times using random values for the probabilities and the failure rates (but keeping the overall failure rate about the same). Test case allocation for proportional partition testing was done by starting with an initial allocation of ni = max(l, floor(n Pi )) and allocating each of the remaining test cases so as to minimize the percentage difference between the current and the true proportional allocation. With 50 test cases we have that proportional partition testing was outperformed by random testing in 154 out of 1,000 cases but the probability of detecting at least one error is 22.5% higher for proportional partition testing than random testing (averaged over the 1,000 cases). (pp. 43-44) With 2,000 test cases, proportional partition testing is outperformed in only 35 cases but the two strategies perform equally well in 581 cases. The probability of detecting at least one error is now only 0.06% higher for proportional partition testing. The variation of the various values with n is mostly the expected one; note that the number of cases in which random testing outperforms proportional partition testing tends to decrease but the decrease is not monotonic. It is also somewhat surprising that even with 2,000 test cases random testing still outperforms proportional partition testing in a significant number of cases. (p. 44) Ntafos (1998) repeated his experiment with 100 subdomains. This time, he started with 100 test cases and increased to a total of 4,000 test cases in increments of 100 cases. “The results are similar; even with 4,000 test cases, there is still one case when random outperforms proportional partition testing while the difference in performance is only 0.009%” (p. 44). Ntafos (1998) concluded that if it requires at least one test case selected from each subdomain and thousands of test cases overall to prove that proportional 27
Page 1 and 2: Domain Testing: Divide and Conquer
Page 3 and 4: We the undersigned committee hereby
Page 5 and 6: Table of Contents Chapter 1: Introd
Page 7 and 8: Chapter 3: Instructional Design and
Page 9 and 10: 5.04 Facilities Used for the Experi
Page 11 and 12: List of Tables Table 6.01 Question
Page 13 and 14: Acknowledgements • Dr. Cem Kaner,
Page 15 and 16: 1.01 Problem Description Chapter 1:
Page 17 and 18: There are two general approaches to
Page 19 and 20: effective testing with reduced effo
Page 21 and 22: Other researchers have used the fea
Page 23 and 24: July 22, 2003; Frankl, Hamlet, Litt
Page 25 and 26: Chapter 2: Domain Testing: A Litera
Page 27 and 28: Black-box testers may or may not re
Page 29 and 30: For instance, in the above example,
Page 31 and 32: Myers (1979) suggested associating
Page 33 and 34: In the functional approach to doing
Page 35 and 36: in the correctness of the program.
Page 37 and 38: Whittaker and Jorgensen (2002) desc
Page 39: listed above. o Worst Case Testing
Page 43 and 44: Hutcheson (2003) described boundary
Page 45 and 46: 2.02.03.02 Special Value Testing Jo
Page 47 and 48: change has caused something that us
Page 49 and 50: Hence, a row in an orthogonal array
Page 51 and 52: combinations of valid equivalence c
Page 53 and 54: Chapter 3: Instructional Design and
Page 55 and 56: Carey, 1985; Dick et al., 2001; Dri
Page 57 and 58: and how they apply the knowledge. T
Page 59 and 60: Keeping the questionnaires anonymou
Page 61 and 62: objectives of the instruction. Bein
Page 63 and 64: software testing courses before, si
Page 65 and 66: accomplished learning. This also he
Page 67 and 68: available and integrate them with t
Page 69 and 70: substance of the materials to make
Page 71 and 72: 4. Expertise-oriented approaches, w
Page 73 and 74: specifically said, “A pretest is
Page 75 and 76: instructional design itself. Accord
Page 77 and 78: • Appendix G: Day 2 Lecture • A
Page 79 and 80: • Reference materials • Linking
Page 81 and 82: Every exercise question and every q
Page 83 and 84: Chapter 5: Experiment Design 5.01 O
Page 85 and 86: This first version of the advertise
Page 87 and 88: o Numeric variables � Integer �
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Standard Deviation: “A measure de
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Question 2 (10 points): • Test A:
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Table 6.10: Final Scores - Pretest
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Chart 6.01: Paper-Based Pretest and
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6.02 Performance Test Results Appen
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11 12 0 0 9. How would you rate you
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commented that they liked the fact
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11. What was the least useful part
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appreciated the fact that a lot of
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Most of them commented that they be
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48% Q4: How would you rate your ove
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Chapter 7: Conclusion 7.01 Domain T
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7.01.02 Minuses Kaner (2003) also c
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work is strong evidence that the st
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Boland, P. J., Singh, H., & Cukic,
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Clarke, L. A., Hassell, J., & Richa
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Hajnal, À., & Forgács, I. (1998).
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Jeng, B., & Weyuker, E. J. (1994, J
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Mayrhauser, A. V., Walls, J., & Mra
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Schroeder, P. J., & Korel, B. (2000
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Zhu, H., Hall, P. A. V., & May, J.
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Appendix A: Reference Material# 1 f
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What is an input variable? An input
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Step 6: Determine whether the varia
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Domain Testing Equivalence Class an
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Partition the input domain into dif
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domain specific special condition b
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Appendix C: Reference Material# 3 f
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What is All-Pairs Combination Testi
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If ‘n’ is the total number of v
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Step 3: Step 4: Step 5: Test case#
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Test case# a(3) b(2) c(2) d(2) e(2)
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Step 9: • The only two pairs miss
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Appendix D: Equivalence Class Analy
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Appendix A: Equivalence Class Analy
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Appendix E: Guidelines for All-Pair
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Appendix B: Guidelines for filling
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Appendix F: Day 1 Lecture (Introduc
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Why do we need to test software? To
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Analysis To assert that the output
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Analysis The total possible combina
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What is Domain Testing? Domain test
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Domain testing-Terminology Boundary
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Summary Our goal is to not only do
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Session 2: Domain Testing Sowmya Pa
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Testing Integer fields � Example
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Testing Integer fields Example 1
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Variable(s) Equivalence Class(es)
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Testing Integer fields Example 2 St
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© Sowmya Padmanabhan, 2003 19
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Word Problems � Example 3: SunTru
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Word Problems Example 3 � Credit
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Word Problems Example 3 � ‘cred
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Word Problems Example 3 � $400
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Word Problems Example 3 � The inp
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Word Problems Example 3 � Failure
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Variable(s) Equivalence Class(es)
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Word Problems Example 4 � Step 1:
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Word Problems Example 4 Step 6: Par
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Word Problems � Example 5: The pa
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Word Problems Example 5 � User, P
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Word Problems Example 5 � ‘widt
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Word Problems Example 5 � 1
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Word Problems Example 5 � The inp
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Word Problems Example 5 � Failure
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Variable (s) ‘width’ Equivalenc
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Testing multiple ranges � The pro
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Testing multiple ranges Example 6
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Word Problems Example 6 Step 6: Par
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Analyzing non-numbers � Let us fi
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Standard ASCII The first 32 charact
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52 4 53 5 54 6 55 7 56 8 57 9 58 :
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108 l 109 m 110 n 111 o 112 p 113 q
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ASCII characters � ASCII files:
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Why bother about ASCII characters i
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Analyzing non-numbers Example 6 �
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Analyzing non-numbers Example 6 Par
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Variable Equivalence classes tax-in
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Testing String fields � We encoun
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Testing String fields Example 7 �
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Testing String fields Example 7 Ste
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25 EM End of medium 26 SUB Substitu
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80 P 81 Q 82 R 83 S 84 T 85 U 86 V
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Extended ASCII Characters Reference
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Session 3: Domain Testing Sowmya Pa
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Testing multidimensional variables
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Testing multidimensional variables
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General analysis of multidimensiona
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Multidimensional numeric fields Exa
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Multidimensional string fields Exam
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Multidimensional string fields �
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Testing Enumerated fields � Range
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Testing Enumerated fields � Examp
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Testing Enumerated fields Example 4
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Identifying variables of a given pr
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Developing test cases for given pro
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Variable Dimension Equivalence clas
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Variable Dimension Equivalence clas
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Look In Variable Equivalence classe
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For ASCII sub-range of allowed grou
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Files of Type Variable Equivalence
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Appendix I: Day 4 Lecture (Day 4 Le
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Testing in combination-Why? � All
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All possible combinations testing
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All-Pairs Combination Testing � M
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All-Pairs Combination Testing � I
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All-Pairs Combination Testing � 7
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All-Pairs Combination Testing Examp
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Application of all-pairs combinatio
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Iteration 3: Test case# Y (4) X (3)
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Iteration 3: Test case# a (4) b (3)
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Iteration 6: Test case# a (4) b (3)
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Look In Variable Equivalence classe
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For ASCII sub-range of allowed grou
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Files of Type Variable Equivalence
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Iteration 2 Test case# LI (6) E(4)
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Appendix J: Day 2 Exercises (Day 2
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d. Partition the input domain into
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f. Partition the input domain into
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d. Next, identify the risks associa
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Non-Numbers Identify the risks asso
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Day 3 Exercises Date: ____________
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g. Partition the input domain into
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e. What is the input domain? f. Nex
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Enumerated fields 3. In the online
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. In Internet Explorer, in the File
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Alignment
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Border
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Protection
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Analyzing given programs/functions
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3. Is the variable multidimensional
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iv. Next, identify the risks associ
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6. For the ‘Insert Table’ funct
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3. Is the variable multidimensional
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iv. Next, identify the risks associ
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Appendix L: Day 4 Exercises (Day 4
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iv. Determine the number of pairs i
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v. Build the all-pairs combination
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4. Develop a series of combination
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Domain Testing-Test A 1 (100 points
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3. A string field/variable ‘s’
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5. The screenshot of the ‘Login
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7. An I-20 VISA 2 program for inter
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9. ZLTech has a web-based student r
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2. A floating-point field/variable
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4. DVD Collections, Inc. has a shop
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6. There are four variables ‘a’
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8. XYZ 3 credit cards offer a ‘ca
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Appendix N: Performance Test (Perfo
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Performance Test (Revised) (100 poi
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Date: _________________ Evaluation
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Appendix P: Instructional Objective
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Appendix Q: Bloom’s Taxonomy of L
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4. Analysis • seeing patterns •
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Day 2 Examples Day 3 Examples Trace
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Day 4 Exercises Example Level HOO I
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Training Schedule Day Instructional
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STUDENT APPLICATION RESEARCH INVOLV
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8. Explain how your proposed study
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CONSENT FORM: DOMAIN TESTING EXPERI
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Appendix V: Call for Participation:
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Appendix W: Call for Participation:
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Appendix X: Performance Tests’ Ev
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• If one student had provided a g
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o You could type more or less quick
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There's no rationale for these test
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page size, perhaps via print or pri
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• Using the variables that this s
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• In the all-pairs analysis, 7 va
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Analysis of Student Performance in
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tester with a couple years experien
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APPENDIX A In this analysis, I used
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esolution: incrementer buttons: .1
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A different orientation may be used
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Slides orientation vs. notes orient
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localized versions of Windows alter
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Report on experiment on teaching sp
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All-pairs analysis The results of t
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