Problem Solving with C++ (10th Edition)
Problem Solving with C++ (10th Edition)
10th Edition
ISBN: 9780134448282
Author: Walter Savitch, Kenrick Mock
Publisher: PEARSON
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Chapter 5.4, Problem 21STE
Program Plan Intro

Testing:

  • It denotes an activity to check whether actual results match expected results.
  • It guarantees that software system is defect free.
  • It involves execution of a software component for evaluating one or more interest properties.
  • It identifies errors, gaps or requirements that are omitted related to actual requirements.
  • It could be performed manually or using automated tools.
  • It can be classified as white or black box testing.
  • The manual testing would include testing of software short of any tool.
    • The tester behaves as an end-user.
    • It tests software for identifying any behavior that is unexpected.
    • The different stages include unit, integration, system as well as user acceptance testing.
  • The automation testing uses software to test product.
    • It includes automation for a manual process.
    • The test scenarios are been re-run that are been performed manually.
    • It is used for testing application from performance, load in addition to stress view point.

Driver program:

  • The driver program contains program’s main function.
  • It is responsible for launching program operations.
  • It is responsible for converting user program into physical execution unit termed as task.
  • Each function must be designed, tested and coded as a discrete unit from rest of program.
  • It denotes a testing program for functions or statement that is been written in code.
  • It tests the functionality usually for debugging as well as code verification.

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Here are two diagrams. Make them very explicit, similar to Example Diagram 3 (the Architecture of MSCTNN). graph LR subgraph Teacher_Model_B [Teacher Model (Pretrained)] Input_Teacher_B[Input C (Complete Data)] --> Teacher_Encoder_B[Transformer Encoder T] Teacher_Encoder_B --> Teacher_Prediction_B[Teacher Prediction y_T] Teacher_Encoder_B --> Teacher_Features_B[Internal Features F_T] end subgraph Student_B_Model [Student Model B (Handles Missing Labels)] Input_Student_B[Input C (Complete Data)] --> Student_B_Encoder[Transformer Encoder E_B] Student_B_Encoder --> Student_B_Prediction[Student B Prediction y_B] end subgraph Knowledge_Distillation_B [Knowledge Distillation (Student B)] Teacher_Prediction_B -- Logits Distillation Loss (L_logits_B) --> Total_Loss_B Teacher_Features_B -- Feature Alignment Loss (L_feature_B) --> Total_Loss_B Partial_Labels_B[Partial Labels y_p] -- Prediction Loss (L_pred_B) --> Total_Loss_B Total_Loss_B -- Backpropagation -->…
Please provide me with the output  image of both of them . below are the diagrams code I have two diagram : first diagram code  graph LR subgraph Teacher Model (Pretrained) Input_Teacher[Input C (Complete Data)] --> Teacher_Encoder[Transformer Encoder T] Teacher_Encoder --> Teacher_Prediction[Teacher Prediction y_T] Teacher_Encoder --> Teacher_Features[Internal Features F_T] end subgraph Student_A_Model[Student Model A (Handles Missing Values)] Input_Student_A[Input M (Data with Missing Values)] --> Student_A_Encoder[Transformer Encoder E_A] Student_A_Encoder --> Student_A_Prediction[Student A Prediction y_A] Student_A_Encoder --> Student_A_Features[Student A Features F_A] end subgraph Knowledge_Distillation_A [Knowledge Distillation (Student A)] Teacher_Prediction -- Logits Distillation Loss (L_logits_A) --> Total_Loss_A Teacher_Features -- Feature Alignment Loss (L_feature_A) --> Total_Loss_A Ground_Truth_A[Ground Truth y_gt] -- Prediction Loss (L_pred_A)…

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Problem Solving with C++ (10th Edition)

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