Operating Systems Concepts & Design
Make sure to return to the AWS Learner Lab page (link in Pilot if you forgot to bookmark it) and hit “Start Lab” to turn on your sandbox / AWS instance.
Go to the folder that contains your repository (likely named ceg2350f25-yourgithubusername).
Create a new directory, Lab04
Create a file named README.md in the Lab04 folder. The Lab 04 Template can be copied from this link:
https://raw.githubusercontent.com/pattonsgirl/CEG2350/refs/heads/main/docs/Labs/Lab04/LabTemplate.mdYou may refer to additional resources outside of the recommended resources provided.
Any resource that you use that contributes to your understanding of exercises in this lab should be cited in the Citations section of your lab answers. To add citations, provide the site and a summary of what it assisted you with. If generative AI was used, include which generative AI system was used and what prompt(s) you fed it.
Generative AI may not write your script for you, only assist with component and how-to type questions.
If you make mistakes with commands in the lab, note them! Writing down what went wrong and what the correction was will significantly help your learning journey. If you cannot find a correction, it will help the TAs or myself understand what point you reached and determine some potential solutions.
Use your AWS instance for this part.
The overall goal is to create a personal finance tracking script using bash. Your script will allow you to add records and remove them and will store the records in a file named .finances in the user’s HOME directory.
BEFORE YOU BEGIN
add or remove or view must call a function that performs the actions required. It is your choice on which action is implemented as a function. The user-guide function is required per the assignment tasks.FINANCE TRACKER IMPLEMENTATION
Create a script named ft for finance tracker.
Your script must take one OR two arguments from the command line. The first argument will always be the finance tracker action - add or remove or view. The second argument (if given) is a string, enclosed in quotes, that is the record description (ex. "Chipotle -12.50").
Your script must use a case statement to evaluate if the first argument contained add or remove or view or clear or help and do actions based on each. If no valid action was given, output Invalid argument and print a user guide from the function user-guide and exit script.
If the action is to add a record, check if a second argument was given - if a second argument was not given, prompt the user for the record description. Append the record to a file named .finances in the user’s HOME directory. Let the user know the record was added and exit script.
If the action is to remove a record, check if a second argument was given - if a second argument was not given, prompt the user for the record description. Remove the record from the file named .finances in the user’s HOME directory based on the description. Let the user know if the record was successfully removed or if it was not found and exit script.
If the action is to view, output all records in the file named .finances in the user’s HOME directory and exit script.
If the action is to clear, prompt the user to confirm that they would like to remove all records, then remove the file named .finances in the user’s HOME directory and exit script.
If the action is to help, call the function user-guide and exit script.
The function user-guide must output, using good formatting, guidance and examples of how the user can interact with your script to have it add a record, remove a record, view all records, or show help.
Resources
Reformat the user-guide you have in your function to use markdown to cleanly present usage information.
Include some sample runs (using copy and paste in code blocks) of your script in action.
Use your AWS instance for this part since your repository is cloned there and that is where your script should be.
The lab answer template will prompt you for notes and justifications for this part.
Choose a directory that is available in any user’s PATH variable - not one that would be uniquely appended only if the folder exists in their HOME directory.
Read up on symbolic links vs hard links in Linux. Below is a reference - additional research is recommended to make sure you grasp the difference, and / or run some test cases to verify your understanding of how they work.
Create either a symbolic or a hard link between your ft script in your GitHub repository to one of the directory locations listed in PATH.
Make any required modifications to permissions and ownership.
Test that you can run your ft script from any location on the filesystem.
Test that other user’s on the system can also execute the ft script.
BEFORE YOU BEGIN Your commit history must still show a working version of the script with the original requirements.
Make the ft script better. Ideas:
super-show that shows all records in all .finances files in any user’s HOME directory - the output should indicate which user in addition to that user’s recordsIf you have additional ideas, run them by the TA’s first to see if they are worthy of this extra credit.
Lab04 folder in your GitHub repo
Lab04 folder should contain (at minimum):
README.mdftYour files should be cleanly presented in your GitHub repository. Citations should be included as needed. Include which generative AI system was used and what prompts were used if generative AI was used.