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COMP9312 Data Analytics for Graphs
创建日期：2024-06-19 15:11:33
标签： COMP9312
Data Analytics for Graphs

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COMP9312  Data

Analytics for Graphs
Assignment 1
Graph Storage and Graph Traversal
Summary
Submission Submit an electronic copy of all answers on Moodle
(only the last submission will be used).
Required
Files
A .pdf file is required. The file name should be
ass1_Zid.pdf
Deadline 9pm Friday 21 June (Sydney Time)
Marks 30 marks (15% toward your total mark for this
course)
Late penalty. 5% of max mark will be deducted for each additional day
(24hr) after the specified submission time and date. No submission is
accepted 5 days (120hr) after the deadline.
START OF QUESTIONS
2024/6/5 15:03 COMP9312 24T2 Assignment 1
https://cgi.cse.unsw.edu.au/~cs9312/24T2/assignment/ass1/ 1/5
Figure 1
Figure 2
Figure 3
Q1. Required knowledge covered by Topic 1.1 (4 marks)
Please determine whether the following statements for the graph in
Figure 1 are TRUE or FALSE.
a. In some correct BFS traversal starting from H, M can be traversed
before N.
2024/6/5 15:03 COMP9312 24T2 Assignment 1
https://cgi.cse.unsw.edu.au/~cs9312/24T2/assignment/ass1/ 2/5
b. In some correct DFS traversal starting from I, E can be traversed
before A.
c. In any correct DFS traversal starting from E, G must be traversed
after F.
d. In any correct BFS traversal starting from K, L must be traversed
after H.
e. In any correct BFS traversal starting from A, N must be traversed
before G.
f. In any correct DFS traversal starting from P, A must be traversed
before Q.
g. In some correct DFS traversal starting from M, Q can be traversed
after K.
h. In some correct BFS traversal starting from J, A can be traversed
after E.
Marking for Q1: 0.5 mark is given for each correct TRUE/FALSE
answer.
Q2. Required knowledge covered by Topic 1.1 (5 marks)
Consider the undirected graph in Figure 2 stored by the adjacency list.
For each vertex, the neighbors are arranged alphabetically (e.g., the
neighbor list of A is [B,E,P]). Describe an algorithm to compute all
connected components using the disjoint-set data structure. Show the
tree structure after each union operation.
Marking for Q2: Full marks are given if each intermediate disjoint-set
tree structure is correct.
Q3. Required knowledge covered by Topic 1.1 (5 marks)
Consider the directed graph in Figure 3 stored by the adjacency list.
The neighbors of each vertex are arranged alphabetically. Compute the
topological order of vertices in the graph. Show intermediate steps.
Marking for Q3: Full marks are given if the described process of each
vertex is correct and the order of vertices are correct.
Q4. Required knowledge covered by Topic 0 (6 marks)
2024/6/5 15:03 COMP9312 24T2 Assignment 1
https://cgi.cse.unsw.edu.au/~cs9312/24T2/assignment/ass1/ 3/5
We consider an undirected, unweighted graph with n vertices and m
edges. Design a data structure to store the graph that can efficiently
support the following three operations:
1) Scanning all neighbours of a given vertex,
2) Inserting a new edge that does not exist in the original graph
3) Deleting a vertex from the graph, including all edges related to it.
Justify the time complexity of each operation and the space complexity
of the data structure.
Marking for Q4: Two factors are evaluated in marking: (1) How good is
your time complexity and space complexity; (2) Does your algorithm
match your time complexity. (3) Does your data structure match your
space complexity. Full marks are given if your time complexity is not
larger than our expected one and your algorithm corresponds with your
time complexity.
Q5. Required knowledge covered by Topic 1.1 (5 marks)
We consider an undirected, unweighted graph with n vertices and m
edges organized using an adjacency list. Design an algorithm to
determine whether there exists a cycle that contains the given query
vertex (i.e., the input is a vertex ID, and the result should be TRUE or
FALSE). Please write your code in pseudocode and justify the time
complexity of each subpart, as well as the total time complexity of your
algorithm.
Marking for Q5: Two factors are evaluated in marking: (1) How good is
your time complexity; (2) Does your algorithm match your time
complexity. Full marks are given if your time complexity is not larger
than our expected one and your algorithm corresponds with your time
complexity.
Q6. Required knowledge covered by Topic 1.1 (5 marks)
We consider a directed, unweighted graph stored by the adjacency list
(an array of out-neighbors is stored for each vertex). Design an
algorithm to compute the shortest distance between two query
vertices (i.e., the input is two vertex IDs, and the output should be the
shortest distance). The queue data structure is not allowed in your
solution (e.g., the dequeue object in Python). Please write your
pseudocode and justify the time complexity of each subpart, as well as
the total time complexity of your algorithm.
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EMESTER1 MAS8383 ECO 512 STAT 8310 CMN3102 MA577 CMPT 225 COMP0045 Methods Equations MATH 113 Math 3283W ICS-33 EN4302/ENT603 BIA B350F MA318 MTHM506 MECH 5315M ECONOMICS MAS8382 COM 2004 PX3142 XJEL 3662 STAT 231 MGT B399F PX4131 COM2108 30AM MSCI521 ECONM1015 ACFI304 GR5241 MATH10101 ECON 2070 COMS31900 EFIM20011 CSE 250B ACSE-5 STAT4207 SOFT2412 ELEC 331 AY2020 MSIN0209 FIT2094 CS 241L ST404 CS 411 3D CA3 INF4002 COMP3506 SIT718 CS 188 CS 170 MATH 138 CSE 251A CMT118 DATA5207 CMPT307 CMPT459 T1 PGEE11108 COSC 3P32 ME 163 MATH96007 7QQMM203 EE6227 BA 574 STA 4234 ECO206Y1Y ECO2008 MT2300 MATH 11158 CS 527 MACM 316 CSE474 2DI70 ISE 525 COMP3411 EMAT30007 7CCSMBDT MFIN704 MFIN704W21 MfIB ECE 438 CS 436 F36 CS5344 FE 621A FE621 TBA 612 ECM3151 ECMM422 MF1 MSIN0107 ESSMENT CS 5854 MFIT 5008 MIPS R4000 ENG5274 BU52018 ENG2079 BIOA02 STA2570 F0 INF553 STAT 440 STAT3008 COMP9417 COMP6451 6COM1042 BU52006 ST303 HW-1 CISC-235 CS 510 MATH3161 ECN 140 ECE391 Comp 3613 CVEN 9625 PRG455 UESTION 1 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MATH 239 QF5203 INFR08010 IT114105 FIT2093 ECON3124 ECON1195 MATH 337 STAT 3006 COMP202 COMP3130 MATH3609 COMP 250 CS6140 IEEE ELE00041I FIN40090 CIV 5899 MATH3066 IGNMENT MATH 2009 STAT3405 HIST 101 MATH 3281 CEGE0042 ICT532 LAB 7 LAB 5 MCO455 CSIT214 Q4 IFB104 A1 ECO220Y5Y DA5020 CMPSC473 FIN9007 DSCI553 MSCI534 COMP3308 CSE-112 CMPT 310 EE104 F 2C P20 ALY2010 BUSM060 STA258 ECO00030M R BIOSTAT 274 COS6012-B FIT3155 CMPUT 340 EC421 INFS4205 ECOM135 NATS 1740 COMP809 MBE 6005 STA465 CSSE2310 CIVL2700 DATA4700 CMPSC 473 ISE 529 CS5044 MAST30020 COMP2207 ENGG1001 COMP0046 FIT3165 STAT GR5241 MECH0007 vATHK1001 ANALYTIC ATHK1001 MATH352001 HW3 S1 BMAN 24662 COMP 636 Stat-461 STAT 302 STAT 2132 STAR534 ENG4137 CMP3752M CS3103 BISM3222 STA 135 ME155A IIMT3601 ECON3371 ECON 3371 HW4 FINA 5840 DT211C CTEC3902 MAT005 MATH2148 S261F Econ 332 MATH3734 MIS41270 7CCMFM13 SYST 664 CIS434 CENG10014 MT4111 MT4527 ECMM424 CMT219 Math 136 MATH 3120 COMP10002 MAST20009 MATH0058 BEEM117 ISYE 6420 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MOEC0021 STA 106 ENGG 1300A ENGG 1300 OLET1139 STAT 3503 STAT 206 FEM11149 ELEN 4720 COMP20003 SOLA1070 CS574 C11CS LINB29H3 MAST90083 ECON7200 STAT 610 LINB29 DSM-5 COMP3161 EEEN40010 MATH 4431 K353 STA 3386 IERG4300 COMS W4167 ENG5298 AMME 2302 CS3910 COMPSCI 320 STATS 369 GR5242 COSC 328 CSCI435 MGTS1301 INFS2200 COMP3900 CIS 375 Module AE03 COMP3121 CS260 HAM503 MGMT5050 INT3075 COSC 285 GEOL0029 GEGE2X01 STAT1201 MATH1061 MMF1941H STAT 5060 CS 520 COMP 4320 MSIN0104 000T FINS3648 ECMT2160 ECON4003 Phys 129L CSE 142 CS 3130 MGEB01 EECS 340 Finance (20443/20444) ECMM149 COMP5310 EEEN60180 CSC 111 AT2 CSCI 4430 STAB57 MA/CSC 427 MATH322 D100 CSCI544 CITS3004 CI6227 CSE 565 APCO 1P01 852L1 ELEC S411F COMP3207 STATS330 ECON7530 FIT5149 CSI4104 CMPT 371 COMP201 SEHS4696 FI4003 MATH6182 CG1 WS MATH401 MGT 205 QTM 110 COMP 0137 MACE12201 FIT5210 ECE 544 BISM7206 HUDM 6055 ECON3203 STATS 210 MSCI 570 MATH6173 COMPSCI4039 Accounting COM3503 AOE2024 ECON213 PSYC10004 Control Data 100/200A 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