Computational Thinking for Problem Solving, Thoughts

Maxi Wu
2 min readJan 20, 2021

Gone through lesson 1 of the course. This course is from UPenn. Just want to write down my thoughts.

For seasoned developers, they don’t define step by step process. They just do them parallelly in they head. But that may not work when working on non-programming problems. The perspective of four pillars is refreshing and help guide us while we are analyzing problems. I think all four pillars are the break down of a type of problem analyzing methodology.

To define the four pillars as clear as possible. I would write it down like this:

  • decomposing (optional)
  • find pattern (optional)
  • Design data structure and abstraction
  • Algorithm

For problem which is not complex or the scope is small enough. It doesn’t need to further break down into components. Oh you may read this from algorithm text book as divide and conquer. The second pillar, is not necessary if the problem is well defined. For example, Check if a sentence contains any invalid punctuation. Finding pattern usually means you are given some data and are being asked to design a method to reach an outcome which specific requirements. The last two pillars are more essential and should not be skipped.

To do this though process using a real world example. Let’s say you are an administration officer. You boss tells you to find a solution to help fellow colleagues to have a satisfying lunch in a efficient fashion. Then you need all four pillars to help you come up with a sound solution.

Decomposing the problem could be the followings: provide a list of restaurant, take orders, prepare a payment method and delivering to your colleges. Each of these is a smaller problem. Then we need to find patterns like when do they prefer to have lunch, what types of food do people like, how long the lunch break is, etc.

To summarize, I think this course start out light but still informative and could apply to a wide variation of problems. For people with or without software engineering background.

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Maxi Wu

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