• 들어가기 전에
  : 해당 강좌는 MIT 의 OpenCourseWare 수업을 듣고 내용을 정리한 것이다.
  : 강좌명은 Introduction To Computer Science And Programming In Python, 6.0001 이며 링크는 다음과 같다.
  https://ocw.mit.edu/courses/6-0001-introduction-to-computer-science-and-programming-in-python-fall-2016/video_galleries/lecture-videos/

배울 내용

1. Testing
2. Debugging
3. Exceptions
4. Assertions

1. Good Programming

• Defensive Programming
  : Write specifications for functions
  : Modularize
  : Check conditions for inputs/outputs

• Testing / Validation
  : Compare input / output

• Debugging
  : Study events leading up to an error

2. Testing

Set yourself up for easy testing and debugging

• 처음부터 디버깅이 쉽게 코드를 짜라
• Modularize
• Document constraints on modules
  : what do you expect the input to be?
  : what do you expect the output to be?
• Document assumptions behind code design

Classes of tests

1. Unit testing
   : validate each piece of program
   : testing each function separately

2. Regression testing
   : add test for bugs
   : catch reintroduced errors -> return to step 1

3. Integration testing
   : does overall program work?
   : catch error -> return to step 1

Testing Approaches

• Black box testing
  : explore paths through specification

• Glass box testing
  : explore paths through code

Black Box Testing

• Designed without looking at the code

• Paths through specification
  : build test cases in different natural space partitions
  : also consider boundary conditions (empty lists, singleton list, large numbers, small numbers)

• Input을 넣었을 때 Output이 어떻게 되는가?

Glass Box Testing

• Use code directly to guide design of test cases
• Called path-complete if every potential path through code is tested at least once

1. Branches
   : exercise all parts of a conditional

2. For loops
   : loop not entered
   : body of loop executed exactly once
   : body of loop executed more than once

3. While loops
   : same as for loops, cases that catch all ways to exit loop

• example

def abs(x) : 
  """
  Assumes x is an int
  Returns x if x >= 0 and -x otherwise
  """

  if x < -1 :
    return -x
  
  else : 
    return x

: a path-complete test suite coud miss a bug
: path-complete test suite : 2 and -2
: but abs(-1) incorrectly returns -1 -> should still test boundary cases

3. Debugging

• Steep learning curve
• Tools
  : built-in to IDLE and Anaconda
  : Python Tutor
  : print statement (특히 함수 내에서) -> good way to test hypothesis, 매우 중요하다

Don't and Do

• Don't
  : Write / Test / Debug entire program
  : Change code -> Remember where bug was -> Test code -> Forget where bug was or what change you made -> panic
• Do
  : Write / Test / Debug a function
  : Backup code -> change code -> write down potential bug in a comment -> Test code -> Compare new version with old version

4. Exceptions

Exceptions

• IndexError
  : Trying to access beyond list limits

  	test = [1, 7, 4]
  	test[4]

• TypeError
  : Trying to convert an inappropriate type

  	int(test)

• NameError
  : Referencing a non-existing variable

• TypeError
  : Mixing data types without coercion (강제)

• SyntaxError
  : Python can't parse program

• AttributionError
  : attribute reference fails

• ValueError
  : operand type okay, but value is illegal

• IOError
  : IO system reports malfunction (e.g. file not found)

Dealing with exceptions

• See this code

try : 
  a = int(input("Tell me one number:"))
  b = int(input("Tell me another number:"))
  print(a/b)
except : 
  print("Bug in user input.")

• Exceptions raised by any statement in body of try are handled by the except statement and execution continues with the body of the except statement

• 예를 들어 a와 b 모두 정수를 입력해주면 print(a/b) 가 정상적으로 실행되고, a나 b에 float number를 넣어주면 (ValueError) except : 이후의 코드를 실행한다.

Handling Specific Exceptions

• Exception Type에 따라 다른 코드를 실행하도록 할 수 있다.

try : 
  a = int(input("Tell me one number:"))
  b = int(input("Tell me another number:"))
  print("a/b = ", a/b)
  print("a+b = ", a+b)
except ValueError :
  print("Could not convert to a number")
except ZeroDivisionError : 
  print("Can't divide by zero")
except : 
  print("Something went very wrong.")

• 코드를 실행해 보면, float number를 넣으면 ValueError에 해당하는 코드가, b에 0을 넣으면 ZeroDvisionError에 해당하는 코드가 실행되는 것을 볼 수 있다.

Other Exceptions

• else
  : when try body completes with no exceptions
• finally
  : always executed after try, else, and except clauses, even if they raised another error or executed a break, continue or return

Exceptions As Control Flow

• Raise an exception when unable to produce a result consistent with function's specification

raise <exceptionname> (<arguments>
// exceptionname : value of error you want to raise
// arguments : optional, but typically a string with a message
// example

raise ValueError("something is wrong")

• Example

def get_ratios(L1, L2) : 
  """
  Assumes : L1 and L2 are lists of equal length of numbers
  Returns : a list containing L1[i]/L2[i]
  """

  ratios = []
  for index in range(len[L1]) : 
    try : 
      ratios.append(L1[index] / L2[index])
    except ZeroDivisionError : 
      ratios.append(float('nan')) # nan = not a number
    except : 
      raise ValueError('get_ratios called with bad arg')
    
    return ratios

5. Assertions

• Want to be sure that assumptions on state of computation are as expected
  : Use an assert statement to raise an AssertonError exception if assumptions not met

• An example of good defensive programming

• Format :

def avg(grades) : 
  assert len(grades) != 0, 'no grades data'
  return sum(grades) / len(grades)

• Raises an AssertionError if it is given an empty list for grades, otherwise runs ok
• assert 'condition' 에서 condition에 원하는 assumptions이 들어가야한다.

Assertions as Defensive Programming

• Assertions don't allow a programmer to control response to unexpected conditions

• Ensure that execution halts whenever an expected condition is not met

• Typically used to check inputs to functions, but can be used anywhere

• Can be used to check outputs of a function to avoid propagating bad values

• Can make it easier to locate a source of a bug

Where to use Assertions?

• Goal is to spot bugs as soon as introduced and make clear where they happened
• Use as a supplement to testing
  : Raise exceptions if user supplies bad data input
• Use assertions to
  : check types of arguments or values
  : check that invariants on data structures are met
  : check constraints on return values
  : check for violations of constraints on procedure