sic","front":"What property must rules and constraints have for a computer to test them?","back":"They must be precise.","points":1},{"id":"a5c57908-0c1e-4295-90d3-7d0fb9322864","cardType":"cloze","front":"A computational solution should be a [ ], called an [ ].","back":"A computational solution should be a finite sequence of steps, called an algorithm.","points":null},{"id":"177a4674-f7a1-417f-a2c9-a5d8d908cb8d","cardType":"basic","front":"Which problem type finds the best solution by a measure like shortest time or lowest cost?","back":"Optimisation.","points":1},{"id":"856f91d7-a531-420c-aa8c-f0f044b8facd","cardType":"basic","front":"Which problem type assigns data to categories, such as spam or not spam?","back":"Classification.","points":1},{"id":"4e35f4e5-2e50-4d64-852a-a6415a6732e9","cardType":"cloze","front":"[ ] means spotting the underlying computational problem inside a real-world description.","back":"Problem recognition means spotting the underlying computational problem inside a real-world description.","points":null},{"id":"a549e6d4-56d2-42a5-867d-e615028bf7d0","cardType":"basic","front":"Why is a decomposed problem easier to work with?","back":"Smaller subproblems are easier to understand, solve, test and maintain.","points":2},{"id":"42f115bc-f951-40ae-8659-cf86996d1db9","cardType":"basic","front":"After decomposition, what can each subproblem be designed as?","back":"A separate module, function or procedure.","points":1},{"id":"b89e40b9-e9bb-484b-a18f-3e4592fcc760","cardType":"basic","front":"How does divide and conquer differ from ordinary decomposition?","back":"

Decomposition: different kinds of subproblem.
Divide and conquer: smaller versions of the same problem.

","points":3},{"id":"7b4532e8-3c5d-4939-98d7-9bd02a805e08","cardType":"cloze","front":"A [ ] algorithm calls itself; a [ ] stops the recursion.","back":"A recursive algorithm calls itself; a base case stops the recursion.","points":null},{"id":"132c1e5c-55e1-4c38-812c-636e9d671cfe","cardType":"basic","front":"What must be true of a list before binary search can be used?","back":"The list must be sorted.","points":1},{"id":"203c1941-2fae-421e-b3a5-4b4504aa856d","cardType":"basic","front":"In binary search, if items[mid] < target, which part is searched next?","back":"The right half, from mid + 1 to high.","points":1},{"id":"93cb2bc1-10d6-451d-b002-11525e303a79","cardType":"cloze","front":"Good abstraction keeps details that [ ] and ignores details that [ ].","back":"Good abstraction keeps details that affect the answer and ignores details that do not.","points":null},{"id":"ce934afc-3716-413d-9fd7-083c6fb6f43d","cardType":"basic","front":"In abstraction, what should you do if removing a detail could change the answer?","back":"Keep that detail.","points":1},{"id":"e0db66f9-dfd8-4931-bdea-6c36c0606f56","cardType":"basic","front":"What does backtracking do when a partial solution cannot become valid?","back":"

Undo the invalid choice.
Try another branch.

","points":2},{"id":"4b8341aa-d16b-4921-9a7b-fcb6a1911eb6","cardType":"basic","front":"Which method suits constraint problems such as Sudoku, mazes or timetables?","back":"Backtracking.","points":1},{"id":"db3a3899-9724-4425-9cf6-9662a2ca2dd6","cardType":"cloze","front":"Dat

Computational methods Flashcards

Computational methods Flashcards