Overview

This assignment is to be implemented using procedural programming. These are some general rules about what you should and should not do. 1. Your assignment should be organised into one zip file with name following the format “familyname_studentId_ass1.zip”. The zip file ONLY contains three source-code files and one README: (a) A driver file driver.cpp containing your main() function. Meanwhile, the main() function should make it clear what is going on, and should not be too large. (b) A header file header.h containing the prototypes for the functions you write. (c) An implementation file header.cpp containing the implementations of your functions. (d) In README, describe the role and content of each source-code file, and how to run your code. 2. Your code must be C++17-compliant and work on capa.its.uow.edu.au. 3. We want readable code with a good code layout. 4. Include sensible volumes of commenting. 5. Use appropriate and self-explained variable/function names. Description This program is used to simulate the process of a crowdsourcing system, and we simplify some steps here. The Tasks.txt and Workers.txt file save the information of individual tasks and workers, respectively. Each task (one line record from in Tasks.txt) represents a task which needs to be assigned to a worker to finish. The crowdsourcing system attempts to assign the task through a list of workers in the same line in Tasks.txt. All workers in the list will try the task in order. Each worker can try five times. Whether this worker is successful depends on the average performance over five times. The next worker can try only when the current worker fails. If the current worker y succeeds, you should output something like “Assignment of Task x to worker y succeeds” where x is the taskID and y is the workerID. Otherwise, output something like “Assignment of Task x to worker y fails”. Now, let us define the inputs in Tasks.txt and Workers.txt, ‘worker performance’ at a time, ‘worker average performance’ and the ‘successful condition’ of a worker. Inputs in Tasks.txt and Workers.txt: 1. Tasks.txt taskId,description,uncertainty,difficulty,workers:a list of worker IDs Example: 123,image labelling,5,10,workers:0,1 2. Workers.txt workerId,name,variability,ability Example: 0,Michael,-2,50 Worker Performance and her/his average performance: The performance score is a sample drawn from a normal distribution. In this normal distribution, “mean = worker ability – task difficulty” and “standard deviation = task uncertainty +worker variability”. E.g, given the task and the worker in the example above. Mean=50-10, and standard deviation=5+(-2). The average performance is the average score of five independent draws from this distribution. Successful condition of a worker We say the worker is successful if and only if the average performance score is greater than 50. Otherwise (i.e., the score <= 50), it fails. Output: The tasks from the “Tasks.txt” file are to be processed in the order they are given, and each task is independent. You should output the information of each task (i.e., all attribute information in the input file) being processed and the evaluation results for the workers in the list (i.e., Assignment of Task x to worker y succeeds or not). You should output something (like below) into the “Output.txt” file. Note: 1. Do not change Tasks.txt and Workers.txt. Report results for tasks in order. 2. Use structs to store information for tasks and workers. 3. Name your executable file as “run”. It should run like: $ ./run Tasks.txt Workers.txt Output.txt 4.