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CMT304 Programming Paradigms
创建日期：2024-05-31 15:42:02
标签： CMT304
Programming Paradigms

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CMT304

Programming Paradigms
If you have been granted an extension for extenuating circumstances, then the sub-
mission deadline and return date will be 1 week later than that stated above (same
time).
If you have been granted a deferral for Extenuating Circumstances, then you will be
assessed during the next period the module is run (assuming all other constraints
are met).
This assignment is worth 100% of the total marks available for this module.
If coursework is submitted late (and where there are no extenuating circumstances):
1. If the assessment is submitted no later than 24 hours after the deadline, the mark for
the assessment will be capped at the minimum pass mark;
2. If the assessment is submitted more than 24 hours after the deadline, a mark of 0 will
be given for the assessment.
Extensions to the coursework submission date can only be requested using the Extenuating
Circumstances procedure. Only students with approved extenuating circumstances may
use the extenuating circumstances submission deadline. Any coursework submitted after
the initial submission deadline without approved extenuating circumstances will be treated
as late.
By submitting this assignment you are accepting the terms of the following declaration:
I hereby declare that my submission (or my contribution to it in the case of group
submissions) is all my own work, that it has not previously been submitted for as-
sessment and that I have not knowingly allowed it to be copied by another student.
I understand that deceiving or attempting to deceive examiners by passing off the
work of another writer, as one’s own is plagiarism. I also understand that plagiarising
another’s work or knowingly allowing another student to plagiarise from my work is
against the University regulations and that doing so will result in loss of marks and
possible disciplinary proceedings1.
1
Assignment
Task 1
Consider the following situation:
The public works division in a region has the responsibility to subcontract
work to private companies. There are several types of tasks. Each task is carried
out by a team, but each team is capable of carrying out all different types of tasks.
The region is divided into districts, and the amount of tasks to be done in each
district is known. In particular, the following information is available:
• The region is divided into n districts.
• There are m private companies such that 1 . . . k are experienced and
k + 1 . . .m are non-experienced.
• Each company i has ti teams available, for all 1 ≤ i ≤ m.
• Each district j requires aj many teams, for all 1 ≤ j ≤ n.
• The yearly cost of allocating a team from a company i to a district j is (the
integer) ci,j , for all 1 ≤ i ≤ m, 1 ≤ j ≤ n.
The goal is to write a logic program for helping the public works division with this process.
Using the information above, the program should determine the number of teams from each
company to allocate to each district such that the following constraints are satisfied.
• At least one experienced company must be allocated to each district (as precaution in
case some difficult task arises in that district).
• Enough teams must be allocated to meet the demand in each district.
• No company can be asked to provide more teams than it still has available.
• The cost must be minimised.
Task 1.1:
1. Write a logic program in ASP (problem encoding.lp) which finds all solutions to the
problem, given n, m, k, ti, aj , ci,j for all 1 ≤ i ≤ m, 1 ≤ j ≤ n. Document your code
so the following is clear.
(a) How it should be used.
(b) What the approach to solving the problem is. In particular, you need to explain
what each rule achieves and how the rule achieves it.
Include your name and student id in the comments.
2. Write three problem instances (problem instancei.lp, for all i ∈ {1, 2, 3}) to test your
program. Document your code so it is clear what the instance is modeling.
Task 1.2: Write a short report on logic programming related to the problem:
1. Provide, in up to 300 words, an analysis of the design and functioning of your program
in terms of the Guess-and-Test modeling methodology.
The word limits are an upper limit, not a target length. Text longer than the word limit for
each point will be ignored. Clearly mark each argument in your answer and indicate if it is
2
for and against. Only provide two arguments for and against; additional arguments will be
ignored.
Task 2
Quadratic unconstrained binary optimization (QUBO) is an optimisation problem commonly
arising in many applications such as scheduling, computer vision, computer-aided design,
financial analysis, molecular conformation. QUBO is an NP-hard problem, but small prob-
lems are feasible to solve on standard computers. For this task a simple brute force ap-
proach is sufficient, and can achieve full marks if implemented efficiently and clearly, and is
concisely documented.
QUBO is the problem of maximising a quadratic polynomial
E(x1, x2, . . . , xN ) =
N∑
l=1
N∑
k=1
Hl,kxlxk = x
THx
where xl ∈ {0, 1} for l = 1, . . . , N and Hl,k ∈ R for l, k = 1, . . . , N , and N is a positive
integer. Note that the xl values can only be either 0 or 1, so this is a search over a discrete
space.
Task 2.1: Write a Haskell program that can solve this problem by reporting a list of x1, . . . , xN
values that maximises the above functional E for small N . You may try to solve the problem
exactly or approximately (find a vector x for which E is close to the maximum). In the com-
ments, make sure you clearly document your approach, how to call your program with the
input matrix H of size N , and how the output vector x is reported.
Task 2.2: Describe one feature of the functional programming paradigm. Discuss whether
this feature makes it simpler or harder to solve the problem and compare this to another
paradigm of your choice that does not have this feature. Your answer should not be longer
than 400 words (this is not a target, but an upper limit).
Task 3
The attached measurements.csv is a csv file where the first column contains the time t and
the second column a voltage measurement x in the circuit (1, 000 datapoints from time 0 to
2π).
Write a python program using differentiable programming techniques covered in the module
to approximate the measurement data in measurements.csv with a parameterised function
fp : R 7→ R, t → x. You may use pytorch, tensorflow or jax for this (or maybe a combi-
nation of these packages; using numpy and matplotlib for supporting functionality is fine;
other packages should not be needed). You are free to choose any function type (some
analytical function, a neural network, etc). Make sure your code is suitably documented
in the comments and in particular you provide a short justification for your choice of the
representation of fp.
Your code can produce the results in any suitable format, on the terminal, via plots or in files
(do not submit these; your code will be run). Assume measurements.csv is in the directory
your python code is executed in.
3
Task 4
Consider the following quantum circuit:
consisting of several multi-target CNOT and controlled swap gates. It has two two-qubit
input quantum registers |A⟩ and |B⟩ and two two-qubit output quantum registers |A′⟩ and
|B′⟩.
Analyse the operation of the circuit. In particular, derive the full operator of the circuit and
describe the mapping from |A⟩|B⟩ to |A′⟩|B′⟩. You may use code in any language to com-
pute the circuit operator, or compute it manually. There is no need to list all intermediate
numerical results/matrices, but you need to describe and justify how you derived the opera-
tor. Based on the operator, what operation does the circuit implement?
Learning Outcomes Assessed
• Explain the conceptual foundations, evaluate and apply various programming paradigms,
such as logic, functional, scripting, filter-based programming, pattern matching and
quantum computing, to solve practical problems.
• Discuss and contrast the issues, features, design and concepts of a range of program-
ming paradigms and languages to be able to select a suitable programming paradigm
to solve a problem.
Criteria for assessment
Task 1.1: maximum 15 marks, assessed according to the following scale
Fail 0 No code has been submitted.
1− 3 Code does not run or does not produce valid output for any valid input; little
to no relevant documentation.
4− 6 Code is valid without syntax errors and creates a valid output for every
valid input (or produces a suitable error message for valid cases it cannot
process). Even if the output is not a solution, a suitable attempt to solve the
problem is visible. An attempt to document the code has been made.
Pass 7− 8 Code is valid without syntax errors and creates a valid output for every
valid input (or produces a suitable error message for valid cases it cannot
process). A suitable attempt to solve the problem has been made, that
will often find at least one solution (if there is any). The attempt has been
reasonably documented, but no consideration has been given to optimise
the program’s performance.
4
Merit 9− 10 Code is valid without syntax errors and creates a valid output for every
valid input (or produces a suitable error message for valid cases it cannot
process). A suitable attempt to solve the problem has been made, that will
find all solutions (if there are any). The attempt has been well documented.
Distinction 11− 15 Code is valid without syntax errors and creates a valid output for every valid
input. A suitable attempt to solve the problem has been made, that will find
all solutions (if there are any) for all problems, with excellent performance.
The attempt has been well documented and clearly shows an effort to op-
timise the program’s performance, e.g. by using efficient algorithms and
data representations and also some heuristics.
Task 1.2: maximum 10 marks, assessed according to the following scale
Fail 0 No document has been submitted.
1− 3 At most an incomplete attempt to analyse the design and functioning of the
program has been made.
4− 5 An attempt has been made to analyse the design and functioning of the
program.
Pass 5 A suitable attempt has been made to analyse the design and functioning of
the program.
Merit 6 The analysis of the design and functioning of the program is well-developed,
showing a clear understanding of the Guess-and-Test methodology.
Distinction 7− 10 The analysis of the design and functioning of the program shows a clear
understanding of the Guess-and-Test methodology and shows an under-
standing of related performance issues.
Task 2.1: maximum 15 marks, assessed according to the following scale:
Fail 0 No code has been submitted.
1− 3 Code does not run or does not produce valid output for any valid input; little
to no relevant documentation.
4− 6 Code is valid without syntax errors and creates a valid output for every
valid input (or produces a suitable error message for valid cases it cannot
process). Even if the output is not a solution, a suitable attempt to solve the
problem is visible. An attempt to document the code has been made.
Pass 7− 8 Code is valid without syntax errors and creates a valid output for every
valid input (or produces a suitable error message for valid cases it cannot
process). A suitable attempt to solve the problem has been made, that
will often find a solution (if there is at least one). The attempt has been
reasonably documented, but no consideration has been given to optimise
the program’s performance.
Merit 9− 10 Code is valid without syntax errors and creates a valid output for every valid
input (or produces a suitable error message for valid cases it cannot pro-
cess). A suitable attempt to solve the problem has been made, that will
always find a solution (if there is any). The attempt has been well docu-
mented, stating the idea to solve the problem and how it has been imple-
mented.
5
Distinction 11− 15 Code is valid without syntax errors and creates a valid output for every valid
input. A suitable attempt to solve the problem has been made, that will
find a solution (if there is any) for all problems, with excellent performance.
The attempt has been well documented, clearly stating the idea to solve
the problem and how it has been implemented. It clearly shows an effort to
optimise the program’s performance, e.g. by using efficient algorithms and
data representations and also some heuristics.
Task 2.2: maximum 10 marks, assessed according to the following scale:
Fail 0 No document has been submitted.
1− 3 The feature discussed is not related to functional programming paradigm.
4− 5 The feature discussed shows some understanding of the functional pro-
gramming paradigm, but is incomplete / comparison with another paradigm
is not present.
Pass 5 The feature discussed is generally valid for the functional programming
paradigm, but does not consider the specific problem or contains mistakes
in the details. An attempt to compare it to another paradigm has been made
and some understanding of this paradigm is present.
Merit 6 The feature discussed shows a clear understanding of the functional pro-
gramming paradigm, and it relates to the problem. The comparison with
another paradigm is well-developed, showing a clear understanding of both
paradigms and their differences.
Distinction 7− 10 The feature discussed shows a clear understanding of the functional pro-
gramming paradigm and the underlying theoretical concepts and how these
relate to the problem. The comparison with another paradigm is well-
developed, showing a deep understanding of practical and theoretical is-
sues involved, and clearly discusses concrete differences to the other cho-
sen paradigm.
Task 3: maximum 25 marks, assessed according to the following scale:
Fail 0 No code has been submitted.
1− 6 Code does not run.
7− 12 Code is valid without syntax errors and represents a suitable attempt to ap-
proximate the measurements using differentiable programming, but it does
not work for the measurement data provided.
Pass 13− 14 Code is valid without syntax errors and represents a suitable attempt to ap-
proximate the measurements using differentiable programming. It provides
a reasonable approximation of the measurement data. There are some
comments explaining the code.
Merit 15− 17 Code is valid without syntax errors and represents a suitable attempt to
approximate the measurements using differentiable programming. It pro-
vides a good approximation of the measurement data. Comments provide
insights into the operation of the code and the choice of target functional to
match the data.
Distinction 18− 25 Code is valid without syntax errors and represents a suitable attempt to
approximate the measurements using differentiable programming. It pro-
vides a good approximation of the measurement data. Comments provide
insights into the operation of the code and the choice of target functional to
match the data is clearly motivated and provides insights into the data.

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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 EARN 5 FE 825 IERG 5130 STAT 8178 EE161 ADS2 G54FUZ CS326 113B ECN 226 QBUS6860 ELEC3202 COMP9334 MGT11B MET CS 777 STA238 00099F Python SMM306 CMT206 EC116 SP MAST90084 CS480/680 BCPM0091 CMPT 300 ECON2209 FY20 STAT 432 CVEN9625 MATH1712 CMP9771M CMP3750M CIS 325 AI506 MAT344H1S MGT7180 PSTAT 160B CSYS5010 1D STAT 453/558 ME152B STA304H1F CSCI-128 ME428 CO3002 FINE 7640 COMP3234 ECSE 223 EE497 – 3D MATH5905 ECS648U ENG5009 MATH10242 EC665 A CPI221 ISOM5220 MACE40402 MGT B456F COMP9315 AFM 113 STAT 778 CS 564 MA231 CS 230 CS 124 COMP5511 CSC317 ITEC1010 ELEC207 INFT 3019 7CCMFM06 EE 161 5G ECLT5810 MATH 7349 CS526 O2 COMP90054 ELE00063M ACCT5034 ARC1015 CSCI 40 CSCI E40 FIN 524B CS 462 389COM CMT309 MFIN703 COMP4250 STA304 STA304H1S STA 1003 FIN 448 BUFN 732 CS520 CVEN3701 ECMT6006 PHAS0100 CSIT314 MDIA 5028 CSCI 2134 MAT 451 CMPT 459 STAT 457 INFO20003 COMP4141 IELE8066 F540 ECM9 CSE 6321 FIN 430 MATH3911 BFC5916 COMP1011 EEE 6209 STATS 240 CW3 COMP206 COMP1003 4331W ISE 530 CMPT 295 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 MGMTMFE 405 25579 1ECE 273 M122 COMP4434 1ELEC ELEC5620M STAT0010 BFF2401 MXB361 MATH3811 CS330 CMT307 FIT1033 CptS 583 UP 431 MATH6005 AF5343 CS2435 ECOM30002 ES50061 CS 2506 ECMT6002 CODE 00099F MT4539 ESSAY ICM317 MATH1231 MFIT5010 BMA547 MATH334 CIVL2201 MATH39032 T-04 CIVE97119 EMESTER CAB302 CAB301 59PM STAT802 ISYS3412 RM3 COSC 2123 AcF 311 MATH2022 1FINAL 4CCS1PHC ICM 142 ENVS3023 Math 4023 I1 ACSE8 FIN B385F CS-275 STA 4109-01 A31021 EE140 MT1 EE124 ECO-6004B Inf2-IADS CS126 IS2184 UL18 MATH5092 ECOM009 COMP 6211 ELEC202 MKT3019 IAB230 FIT5046 584-S21 COMP3210 CO250 A29401 MATH 136 MGT6174 ECMT6007 DATA2001 MAT 443 MATH10222 PHDE0071 ELE00123M COSC1295 MAT00045H MATH32032 1004GRC MAS223 COMP10001 DATA3404 CIVL2110 STAT2008 FNCE10002 EEE6431 COM6515 COMP9120 NBS8185 ECTE942 ECON 405 MATH314301 STAT 2011 COMPSCI 350 COMP20007 CMPSC-132 ECON5002 STA 35 MTH6108 FIT5147 MTH6150 100C FINA 5260 DESC9115 ECON4998 NBS8257 GMM ECON 6070 BSA2 ECE599 STATS 102B STA120 INFS601 BFC3241 MATH20602 COMP532 MAS275 COMP5318 COMP4002 FIT5086 MAST20004 FIT3152 FIT5129 CIS2380 CS521 COMP 1005 EECMS CITS5501 ECE 462 ECON 6002 ENG 4051 CSC 648 CMT654 MECHENG 713 PHYS1002 AMME 2000 FP0060 DDES3200 MECHENG 743 BINF90002 FIT2081 ISYS90081 ELECTENG 722 BUS 360 ECOS3010 BUS2810 ETF2100 ENG2048 STAT5002 COMP2017 CEME 2003 MATS3004 COMP9319 PHYS1001 COMP5349 AMME2261 COMP-381 FIT3173 COSC2757 ENG4025 QBUS2820 COMP9414 MATH2021 EOSC118 MFIN6690 PMATH 321 CSE-141L MATH575A COMPSCI5002 COMP1511 management comp2123 FINS3616 COMP 3331 COMS30034 DTSC 71 AcF 702 AcF702 DTSC71 MAT021 ELE8083 ACFI213 EG-127J 127J FIT5163 FIT2001 ELE00113M CMT310 CS 245 ENGL 1101 MTH6115 EE497 CS 325 Math 124A MTH5130 MBA502 MGT 5380 ARCH 1261 F033800 20LLP109 ELE4009 FINANCIAL COMP3331 Computer ECE4179 20T3 COMP9311 COMP9311 UNSW MFIN6210 ACCT 5930 EE590 ENG2029 ECO100 SIT315 ACCT3610 COMP3600 STK2100 FIT2004 COMP30020 ACTL1101 Stat 101B BANA 200 COSC2473 ENGG1400 AI COMP90043 MMF 1914H PHYS 127 CS584 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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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