PPT-Cse 373 October 6 th – Algorithm Analysis

Assorted minutiae Checkpoint 1 should be in Lat e submissions still to canvas Official grade Monday Half of points lost can be reearned Review Counting operations isnt the best for determining performance. This may be inef64257cient as you are forced to keep computing eigenfunctions after every division There are possibly simpler approaches The algorithm is essentially based on 64257nding a good cut in the graph Finding good cuts an ambiguous term is Introduction to Artificial Intelligence Lecture 8: Search in State Spaces II. 1. A General Backtracking Algorithm. Let us say that we can formulate a problem as a sequence of n successive decisions, with each decision consisting of a picking one choice out of a predefined set of options.. and Shavit-Francez termination algorithms. Index :. Introduction. Experimental Setup. Result Analysis. Conclusion. Future Work. Introduction. Dijkstra-Scholten. algorithm detects the termination of a centralized basic computation.. B. . Steensgaard: . Points-to Analysis in Almost Linear Time. .. POPL 1996. M. Hind. : . Pointer analysis: haven't we solved this problem yet. ?.  . PASTE 2001. Presented by Ronnie . Barequet. 23.03.14. A computer algorithm is. a detailed step-by-step method for. solving a problem. by using a computer.. Problem-Solving (Science and Engineering). Analysis. How does it work?. Breaking a system down to known components. Algorithm. Input. Output. 1. Analysis of Algorithms. How long does this take to open 1) know 2) don’t know. . Analysis of Algorithms. 2. If know combination O(n) . where n is number of rings. . If the alphabet is size m, O(nm). 0010010010. 1001011100. 01010000110000101001. 1001011011. 0010100100. 00100100101. 10001010011. 10001010011010. ataacgtagcacatagtagtccagtagctgatcgtagaactgcatgatccaagctgctgatacgatgaacacctgagatgctgatgctgatagctagtcg. Focus: developing algorithms . abstractly. Independent of programming . language, data types, etc.. Think of a stack or queue: not specific to C , but can be implemented when needed. Addressed in depth during COSC 320. Spring . 2018. Analyzing problems. interesting problem: residence matching. lower bounds on problems. decision trees, adversary arguments, problem . reduction. I. nteresting problem: residence matching. Today’s Lecture. Algorithm . Analysis. Asymptotic analysis. bigO. notation. Project 1. Checkpoint 1 due at 11:30 pm. Submit only the files listed in the deliverables section. If you submit as a group, make sure all files have both team names. Assorted minutiae. HW1P1 due tonight at midnight. HW1P2 due Friday at midnight. HW2 out tonight. Second Java review session: . Friday 10:30 – ARC 147. Today’s Schedu. le. Algorithm Analysis, cont.. . . Michael Saks, . Rutgers University. joint work w. . Ankur. . Moitra. . (2013). Anindya. De and . Sijian. Tang . (2016). Avi. is 60! October 5-8, 2016. Objectives. Determine the running time of simple algorithms. Best case. Average case. Worst case. Profile algorithms. Understand O notation's mathematical basis. Use O notation to measure running time. for Algorithm Analysis Topics. Mohammed . Farghally. Information Systems Department, . Assiut. University, Egypt. Kyu. Han . Koh. Department of Computer Science, CSU . Stanislaus. Jeremy V. Ernst. School of Education, Virginia Tech.