reverted all unecessary header changes as request

Author: dejmail

README.md

@@ -2,10 +2,7 @@
 
 An introduction to testing and continuous integration using Python.
 
-Much of this lesson came from the book
-*[Effective Computation in Physics]
-(http://www.amazon.com/Effective-Computation-Physics-Anthony-Scopatz/dp/1491901535/)*
-by Anthony M. Scopatz and Kathryn D. Huff.
+Much of this lesson came from the book *[Effective Computation in Physics] (http://www.amazon.com/Effective-Computation-Physics-Anthony-Scopatz/dp/1491901535/)* by Anthony M. Scopatz and Kathryn D. Huff.
 
 > ## Note
 >

_episodes/01-basics.md

@@ -3,13 +3,13 @@ title: Basics of Testing
 teaching: 5
 exercises: 0
 questions:
-- "Why would you not want to test?"
+- "Why test?"
 objectives:
 - "Understand the place of testing in a scientific workflow."
 - "Understand that testing has many forms."
 keypoints:
-- "Tests compare that the result observed from running code is the same as what was expected ahead of time."
-- "Tests should be written at the same time as the code they are testing is written."
+- "Tests check whether the observed result, from running the code, is what was expected ahead of time."
+- "Tests should ideally be written before the code they are testing is written, however some tests must be written after the code is written."
 - "Assertions and exceptions are like alarm systems embedded in the software, guarding against exceptional bahavior."
 - "Unit tests try to test the smallest pieces of code possible, usually functions and methods."
 - "Integration tests make sure that code units work together properly."

_episodes/02-assertions.md

@@ -3,7 +3,7 @@ title: Assertions
 teaching: 10
 exercises: 0
 questions:
-- "How do I make sure the value I want is the value I receive?"
+- "How can we compare observed and expected values?"
 objectives:
 - "Assertions are one line tests embedded in code."
 - "Assertions can halt execution if something unexpected happens."
@@ -75,7 +75,7 @@ def mean(num_list):
 > Hint: Use the [isinstance function](https://docs.python.org/2/library/functions.html#isinstance).
 {: .callout}
 
-> ## Testing similarity between variables
+> ## Testing Near Equality
 >
 > Assertions are also helpful for catching abnormal behaviors, such as those
 > that arise with floating point arithmetic. Using the assert keyword, how could

_episodes/03-exceptions.md

@@ -3,7 +3,7 @@ title: Exceptions
 teaching: 10
 exercises: 0
 questions:
-- "How do I capture errors that I do not anticipate?"
+- "How do I handle unusual behavior while the code runs?"
 objectives:
 - "Understand that exceptions are effectively specialized runtime tests"
 - "Learn when to use exceptions and what exceptions are available"
@@ -79,7 +79,7 @@ def mean(num_list):
 ~~~
 {: .python}
 
-> ## Remember
+> ## What else could go wrong?
 >
 > 1. Think of some other type of exception that could be raised by the try 
 > block.

_episodes/04-units.md

@@ -3,7 +3,7 @@ title: Unit Tests
 teaching: 10
 exercises: 0
 questions:
-- "How much is a unit of code?"
+- "What is a unit of code?"
 objectives:
 - "Understand that functions are the atomistic unit of software."
 - "Understand that simpler units are easier to test than complex ones."
@@ -30,7 +30,7 @@ project and language to language.  A good guideline is that if the code cannot
 be made any simpler logically (you cannot split apart the addition operator) or
 practically (a function is self-contained and well defined), then it is a unit. 
 
-> ## Note to self
+> ## Functions are Like Paragraphs
 >
 > Recall that humans can only hold a few ideas in our heads at once. Paragraphs
 > in books, for example, become unwieldy after a few lines. Functions, generally,

_episodes/06-edges.md

@@ -31,7 +31,7 @@ Anecdotally, it is important to test edges cases because this is where errors te
 arise. Qualitatively different behavior happens at boundaries. As such,
 they tend to have special code dedicated to them in the implementation.
 
-> ## Consider a Fibonacci sequence
+> ## Consider the Fibonacci sequence
 >
 > Take a moment to recall everything you know about the Fibonacci sequence.
 >
@@ -88,7 +88,7 @@ noninteger values are not valid inputs. Tests for these classes of numbers serve
 you well if you want to make sure that the function fails as expected. Indeed, we
 learned in the assertions section that this is actually quite a good idea.
 
-> ## Implement these points
+> ## Test for Graceful Failure
 >
 > The `fib()` function should probably return the Python built-in
 > `NotImplemented` value for negative and noninteger values.
@@ -158,7 +158,7 @@ def test_edge_y():
 ~~~
 {: .python}
 
-> ## Final steps
+> ## Write a Corner Case
 >
 > The sinc2d example will also need a test for the corner case, where both x
 > and y are 0.0.

_episodes/07-integration.md

@@ -3,7 +3,7 @@ title: Integration and Regression Tests
 teaching: 10
 exercises: 0
 questions:
-- "What is beyond a unit test?"
+- "How do we test more than a single unit of software?"
 objectives:
 - "Understand the purpose of integration and regression tests"
 - "Understand how to implement an integration test"
@@ -19,7 +19,7 @@ the gears and cogs that make up the system. On their own, they can be of the hig
 quality. Unit tests verify that each gear is well made. However, the clock still
 needs to be put together. The gears need to fit with one another.
 
-> ## Further explanation
+> ## Telling The Time
 >
 > _Integration tests_ are the class of tests that verify that multiple moving
 > pieces and gears inside the clock work well together. Where unit tests
@@ -104,7 +104,7 @@ the expected result should be, regression tests look to the past for the
 expected behavior. The expected
 result is taken as what was previously computed for the same inputs.
 
-> ## Further explanation
+> ## The Past as Truth
 >
 > Regression tests assume that the past is "correct." They are great for
 > letting developers know when and how a code base has changed. They are not

_episodes/08-ci.md

@@ -3,7 +3,7 @@ title: Continuous Integration
 teaching: 10
 exercises: 0
 questions:
-- "How can I make sure my changes are compatable with the larger code base?"
+- "How can I automate running the tests on more platforms than my own?"
 objectives:
 - "Understand how continuous integration speeds software development"
 - "Understand the benefits of continuous integration"
@@ -12,7 +12,7 @@ objectives:
 keypoints:
 - "Servers exist for automatically running your tests"
 - "Running the tests can be triggered by a GitHub pull request"
-- "CI allows cross platform build testing"
+- "CI allows cross-platform build testing"
 - "A `.travis.yml` file configures a build on the travis-ci servers"
 - "Many free CI servers are available"
 ---
@@ -23,7 +23,7 @@ As its name implies, continuous integration integrates the test suite into the
 development process. Every time a change is made to the repository, the
 continuous integration system builds and checks that code.
 
-> ## Example
+> ## Thought Experiment: Does Your Software Work on Your Colleague's Computer?
 >
 > Imagine you developed software on a MacOSX computer. Last week, you helped
 > your office mate build and run it on their Linux computer. You've made some
@@ -40,7 +40,7 @@ repository, rebuild the code, and run the tests. If you don't have a build
 system, it could take all afternoon just to see if your new changes are
 compatible.
 
-> ## It saves you time!
+> ## Let The Computers Do The Work
 >
 > Scientists are good at creative insights, conceptual understanding, critical
 > analysis, and consuming espresso. Computers are good at following instructions.
@@ -66,7 +66,7 @@ repository, we'll need to put our code online to make use of this kind of
 server (unless we are able/willing to set up our own CI server).
 
 
-> ## First steps...
+> ## Set Up a Mean Git Repository on GitHub
 >
 > Your `mean.py` `test_mean.py` files can be the contents of a repository on
 > GitHub.

_episodes/09-tdd.md

@@ -11,7 +11,7 @@ keypoints:
 - "Test driven development is a common software development technique"
 - "By writing the tests first, the function requirements are very explicit"
 - "TDD is not for everyone"
-- "TDD requires vigilance for success (cheating leads to failure)"
+- "TDD requires vigilance for success"
 ---
 
 Test-driven Development (TDD) takes the workflow of writing code and writing
@@ -26,7 +26,7 @@ needed, you write another test and then go back and modify the function.  You
 repeat this process of test-then-implement until the function is completely
 implemented for your current needs.
 
-> ## Where it comes from
+> ## The Big Idea
 >
 > This design philosophy was most strongly put forth by Kent Beck in his book
 > _Test-Driven  Development: By Example_.
@@ -44,7 +44,7 @@ you start writing code, you should be considering how to test that code. The
 tests should be written and presented in tandem with the implementation. **Testing
 is too important to be an afterthought.**
 
-> ## Who is using it?
+> ## You Do You
 >
 > Developers who practice strict TDD will tell you that it is the best thing since
 > sliced arrays. However, do what works for you. The choice whether to pursue