iHiD
commented
1 year ago Exercise: binary
Code
#
# Test binary_convert with some examples
#
# s0 - num of tests left to run
# s1 - address of input word
# s2 - address of expected output word
# s3 - char byte
# s4 - output word
#
# binary_convert must:
# - be named binary_convert and declared as global
# - read input address of string from a0
# - follow the convention of using the t0-9 registers for temporary storage
# - (if it uses s0-7 then it is responsible for pushing existing values to the stack then popping them back off before returning)
# - write integer result to v0
.data
# number of test cases
n: .word 9
# input values (null terminated) & expected output values (word sized ints)
ins: .asciiz "0", "1", "10", "11", "100", "1001", "11010", "10001101000", "000011111"
outs: .word 0, 1, 2, 3, 4, 9, 26, 1128, 31
failmsg: .asciiz "failed for test input: "
okmsg: .asciiz "all tests passed"
.text
runner:
lw $s0, n
la $s1, ins
la $s2, outs
run_test:
move $a0, $s1 # move address of input str to a0
jal binary_convert # call subroutine under test
move $v1, $v0 # move return value in v0 to v1 because we need v0 for syscall
lw $s4, 0($s2) # read expected output from memory
bne $v1, $s4, exit_fail # if expected doesn't match actual, jump to fail
scan:
addi $s1, $s1, 1 # move input address on byte forward
lb $s3, 0($s1) # load byte
beq $s3, $zero, done_scan # if char null, break loop
j scan # loop
done_scan:
addi $s1, $s1, 1 # move input address on byte past null
addi $s2, $s2, 4 # move to next word in output
sub $s0, $s0, 1 # decrement num of tests left to run
bgt $s0, $zero, run_test # if more than zero tests to run, jump to run_test
exit_ok:
la $a0, okmsg # put address of okmsg into a0
li $v0, 4 # 4 is print string
syscall
li $v0, 10 # 10 is exit with zero status (clean exit)
syscall
exit_fail:
la $a0, failmsg # put address of failmsg into a0
li $v0, 4 # 4 is print string
syscall
move $a0, $s1 # print input that failed on
li $v0, 4
syscall
li $a0, 1 # set error code to 1
li $v0, 17 # 17 is exit with error
syscall
# # Include your implementation here if you wish to run this from the MARS GUI.
# .include "impl.mips"Tags:
construct:assignment
construct:comment
construct:data
construct:directive
construct:instruction
construct:int
construct:jump
construct:label
construct:laundry
construct:lw
construct:move
construct:number
construct:parameter
construct:register
construct:string
construct:subroutine
construct:syscall
construct:word
paradigm:imperative
paradigm:structured
ErikSchierboom
Hello lovely maintainers :wave:
We've recently added "tags" to student's solutions. These express the constructs, paradigms and techniques that a solution uses. We are going to be using these tags for lots of things including filtering, pointing a student to alternative approaches, and much more.
In order to do this, we've built out a full AST-based tagger in C#, which has allowed us to do things like detect recursion or bit shifting. We've set things up so other tracks can do the same for their languages, but its a lot of work, and we've determined that actually it may be unnecessary. Instead we think that we can use machine learning to achieve tagging with good enough results. We've fine-tuned a model that can determine the correct tags for C# from the examples with a high success rate. It's also doing reasonably well in an untrained state for other languages. We think that with only a few examples per language, we can potentially get some quite good results, and that we can then refine things further as we go.
I released a new video on the Insiders page that talks through this in more detail.
We're going to be adding a fully-fledged UI in the coming weeks that allow maintainers and mentors to tag solutions and create training sets for the neural networks, but to start with, we're hoping you would be willing to manually tag 20 solutions for this track. In this post we'll add 20 comments, each with a student's solution, and the tags our model has generated. Your mission (should you choose to accept it) is to edit the tags on each issue, removing any incorrect ones, and add any that are missing. In order to build one model that performs well across languages, it's best if you stick as closely as possible to the C# tags as you can. Those are listed here. If you want to add extra tags, that's totally fine, but please don't arbitrarily reword existing tags, even if you don't like what Erik's chosen, as it'll just make it less likely that your language gets the correct tags assigned by the neural network.
To summarise - there are two paths forward for this issue:
If you tell us you're not able/wanting to help or there's no comment added, we'll automatically crowd-source this in a week or so.
Finally, if you have questions or want to discuss things, it would be best done on the forum, so the knowledge can be shared across all maintainers in all tracks.
Thanks for your help! :blue_heart:
Note: Meta discussion on the forum