CS 04450代写、代做Java编程设计
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CS 04450 Data Structure, Department of Computer Science, SCUPI
Spring 2024
This coursework sheet explains the work in details. Please read the instructions carefully and
follow them step-by-step. For submission instructions, please read the Sec. 4. If you have any
queries regarding the understanding of the coursework sheet, please contact the TAs or the
course leader. Due on: 23:59 PM, Wednesday, June 5th.
1 Introduction
A developer of a new Java application has asked for your help in storing a large amount of fflm data
efffciently. The application, called SCUPI+, is used to present data and fun facts about fflms, the
cast and crew who worked on them, and some ratings the developer has gathered in there free time.
However, because the developer hasn’t taken the module, they don’t want to design how the data is
stored.
Therefore, this coursework and the task that the developer has left to you, is to design one or more
data structures that can efffciently store and search through the data. The data consists of 3 separate
ffles:
• Movie Metadata: the data about the fflms, including there ID number, title, length, overview
etc.
• Credits: the data about who stared in and produced the fflms.
• Ratings: the data about what different users thought about the fflms (rated out of 5 stars), and
when the user rated the fflm.
To help out, the developer of SCUPI+ has provided classes for each of these. Each class has been
populated with functions with JavaDoc preambles that need to be fflled in by you. As well as this,
the developer has also tried to implement the MyArrayList data structure into a 4th dataset (called
Keywords), to show you where to store your data structures and how they can be incorporated into
the pre-made classes. Finally, the developer has left instructions for you, which include how to build,
run and test you code; and the ffle structure of the application (see Sec. 3).
Therefore, your task is to implement the functions within the Movies, Credits and Ratings classes
through the use of your own data structures.
2 Guidance
First, don’t panic! Have a read through the documentation provided in Sec. 3. This explains how to
build and run the application. This can be done without writing anything, so make sure you can do
that ffrst.
Then you can have a look at the comments and functions found in the Movies, Credits and
Ratings classes. The location of these is described in Sec. 3.5.2. Each of the functions you need to
implement has a comment above it, describing what it should do. It also lists each of the parameters
1for the function (lines starting with @param), and what the function should return (lines starting with
@return).
When you are ready to start coding, We would recommend starting off with the Rating class
ffrst. This is because it is smallest of the 3 required, and is also one of the simplest. When you have
completed a function, you can test it using the test suit described in Sec. 3.5.3. More details about
where the code for the tests are can be found in Sec. 3.4.
3 SCUPI+
SCUPI+ is a small Java application that pulls in data from a collection of Comma Separated Value
(CSV) ffles. It is designed to have a lightweight user interface (UI), so that users can inspect and
query the data. The application also has a testing suit connected to it, to ensure all the functions
work as expected. The functions called in the SCUPI+ UI are the same as those called in the testing,
so if the tests work, the UI will also work.
3.1 Required Software
For the SCUPI+ to compile and run, Java 21 is required, make sure you download this speciffc version
of Java. Whilst a newer version of Java can be utilised, other parts of the application will also have to
be updated and this has not been tested. Although you can always have a try with your own version,
it is highly recommended you download and use Java 21.
3.2 Building SCUPI+
To compile the code, simply run the command shown in the table below in the working directory (the
one with src folder in it).
Linux/DCS System MacOS Windows
./gradlew build ./gradlew build ./gradlew.bat build
3.3 Running the SCUPI+ Application
To run the application, simply run the command shown in the table below in the working directory
(the one with src folder in it).
Linux/DCS System MacOS Windows
./gradlew run ./gradlew run ./gradlew.bat run
This command will also compile the code, in case any ffles have been changed. When this is done,
a window will appear with the UI for the application. The terminal will not be able to be used at this
time. Instead it will print anything required from the program. To stop the application, simply close
the window or press CTRL+C at the same time in the terminal.
23.4 Running the SCUPI+ Test Suit
To run the tests, simply run the command shown in the table below in the working directory (the one
with src folder in it).
Linux/DCS System MacOS Windows
./gradlew test ./gradlew test ./gradlew.bat test
This command will also compile the code, in case any ffles have been changed. When ran, this will
produce the output from each test function. It will also produce a webpage of the results, which can
be found in build/reports/tests/test/index.html
3.5 SCUPI+ File Structure
Every effort has been made to keep the ffle structure simple and clean, whilst maintaining good coding
practices. In the following subsections, a brief description of each of the key directories is given, along
with its contents and what you need to worry about in them.
3.5.1 data/
This directory stores all the data ffles that are pulled into the application. There are 4 .csv ffles in
this directory, 1 for each of the datasets described in Sec. 1. Each line in these ffles is a different entry,
with values being separated by commas (hence the name Comma Separated Values). You do not need
to add, edit or remove anything from this directory for your coursework. More details on how these
ffles are structured can be found in Sec. 3.6.
3.5.2 src/main/
This directory stores all the Java code for the application. As such, there are a number of directories
and ffles in this directory, each of which are required for the application and/or the UI to function.
To make things simpler, there are 3 key directories that will be useful for you:
• java/interfaces/: stores the interface classes for the data sets. You do not need to add, edit
or remove anything from this directory, but it may be useful to read through.
• java/stores/: stores the classes for the data sets. This is where the Keywords, Movies, Credits
and Ratings from Sec. 1 are located, the latter 3 of which are the classes you need to complete.
Therefore, you should only need to edit the following ffles:
– Movies.java: stores and queries all the data about the fflms. The code in this ffle relies
on the Company and Genre classes.
– Credits.java: stores and queries all the data about who stared in and worked on the
fflms. The code in this ffle relies on the CastCredit, CrewCredit and Person classes.
– Ratings.java: stores and queries all the data about the ratings given to fflms.
• java/structures/: stores the classes for your data structures. As an example, a array list
MyArrayList has been provided there. Any classes you add in here can be accessed by the classes
in the stores directory (assuming the classes you add are public). You may add any ffles you wish
to this directory, but MyArrayList.java and IList.java should not be altered or removed, as
these are relied on for Keywords.
33.5.3 src/test/
This directory stores all the code that related solely to the JUnit tests. As such, there is a Java ffle
for each of the stores you need to implement. You do not need to add, edit or remove anything from
this directory for your coursework.
3.6 Data used for SCUPI+
All of the data used by the SCUPI+ application can be found in the data directory. Each ffle in
this directory contains a large collection of values, separated by commas (hence the CSV ffle type).
Therefore, each of these can be opened by your favourite spreadsheet program. Most of these values
are integers or ffoating point values, but some are strings. In the cases of strings, double quotation
marks (”) are used at the beginning and end of the value. Where multiple elements could exist in that
value, a JSON object has been used. You do not need to parse these ffles, SCUPI+ will do that for
you in the LoadData class. The data generated by the LoadData class is passed to the corresponding
data store class (Movies, Credits, Ratings and Keywords) using the add function.
To make development easier, we have provided only 1000 fflms present in the data. This means
that there are 1000 entries in the credits data set, and 1000 entries in the keywords data set. However,
some fflms may not have any cast and/or crew (that information may not have been released yet, or
it is unknown), some fflms don’t have keywords and some fflms may not have ratings. In these cases,
an empty list of the required classes will be provided the add function.
3.6.1 Key Stats
Films 1000
Credits
Film Entries 1000
Unique Cast 11483
Unique Crew 9256
Ratings 17625
Keywords
Film Entires 1000
Unique Keywords 2159
3.6.2 Movies Metadata
The following is a list all of the data stored about a fflm using the column names from the CSV ffle, in
the same order they are in the CSV ffle. Blue ffelds are ones that are added through the add function
in the Movies class.
• adult: a boolean representing whether the fflm is an adult fflm.
• belongs to collection: a JSON object that stores all the details about the collection a fflm
is part of. This is added to the fflm using the addToCollection function in the Movies class.
If the fflm is part of a collection, the collection will contain a collection ID, a collection name, a
poster URL related to the collection and a backdrop URL related to the collection.
• budget: a long integer that stores the budget of the fflm in US Dollars. If the budget is not
known, then the budget is set to 0. Therefore, this will always be greater than or equal to 0.
• genres: a JSON list that contain all the genres the fflms is part of. Each genre is represented
as a key-value pair, where the key is represented as an ID number, and the value is represented
as a string. SCUPI+ passes this as an array of Genre objects.
4• homepage: a string representing a URL of the homepage of the fflm. If the fflm has no homepage,
then this string is left empty.
• tmdb id: an integer representing the ID of the fflm. This is used to link this fflm to other pieces
of data in other data sets.
• imdb id: a string representing the unique part of the IMDb URL for a given fflm. This is added
using the setIMDB function in the Movies class.
• original language: a 2-character string representing the ISO 639 language that the fflm was
originally produced in.
• original title: a string representing the original title of the fflm. This may be the same as
the title ffeld, but is not always the case.
• overview: a string representing the an overview of the fflm.
• popularity: a ffoating point value that represents the relative popularity of the fflm. This value
is always greater than or equal to 0. This data is added by the setPopularity function in the
Movies class.
• poster path: a string representing the unique part of a URL for the fflm poster. Not all fflms
have a poster available. In these cases, an empty string is given.
• production companies: a JSON list that stores the production countries for a fflm. Each entry
in the JSON list has a key value pair, where the key is the ID of the company, and the value is
the name of the company. SCUPI+ parses each list element into a Company object. This object
is the added using the addProductionCompany in the Movies class.
• production countries: a JSON list that stores the production countries for a fflm. Each entry
in the JSON list has a key value pair, where the key is the ISO 3166 2-character string, and the
value is the country name. SCUPI+ parses only handles the key, and uses a function to match
this to the country name. This string is added using the addProductionCountry in the Movies
class.
• release date: a long integer representing the number of seconds from 1
st January 1970 when
the fflm was released. SCUPI+ passes this into a Java Calendar object.
• revenue: a long integer representing the amount of money made by the fflm in US Dollars. If
the revenue of the fflm is not known, then the revenue is set to 0. Therefore, this will always be
greater than or equal to 0.
• runtime: a ffoating point value representing the number of minutes the fflm takes to play. If the
runtime is not know, then the runtime is set to 0. Therefore, this will always be greater than or
equal to 0.
• spoken languages: a JSON list that stores all the languages that the fflm is available in. This
is stored as a list of key-value pairs, where the key is the 2 -character ISO 639 code, and the
value is the language name. SCUPI+ parses these as an array of keys stored as strings.
• status: a string representing the current state of the fflm.
• tagline: a string representing the poster tagline of the fflm. A fflm is not guaranteed to have
a tagline. In these cases, an empty string is presented.
• title: a string representing the English title of the fflm.
• video: a boolean representing whether the fflm is a ”direct-to-video” fflm.
5• vote average: a floating point value representing an average score as given by a those on IMDb
at the time the data was collected. As such, it is not used in the Review dataset. The score will
always be between 0 and 10. This data is added using the setVote function in the Movies class.
• vote count: an integer representing the number of votes on IMDb at the time the data was
collected, to calculate the score for vote average. As such, it is not used in the Review dataset.
This will always be greater than or equal to 0. This data is added using the setVote function
in the Movies class.
3.6.3 Credits
The following is a list all of the data stored about the cast and crew of a film using the column names
from the CSV file, in the same order they are in the CSV file. All these fields are used by SCUPI+:
• cast: a JSON list that contains all the cast for a particular film. In the JSON list, each cast
member has details that relate to there role in the film and themselves. SCUPI+ passes this
into an array of Cast objects, with as many fields populated as possible.
• crew: a JSON list that contains all the crew for a particular film. In the JSON list, each crew
member has details that relate to there role in the film and themselves. SCUPI+ passes this
into an array of Crew objects, with as many fields populated as possible.
• tmdb id: an integer representing the film ID. The values for this directly correlates to the id
field in the movies data set.
3.6.4 Ratings
The following is a list all of the data stored about the ratings for a film using the column names from
the CSV file, in the same order they are in the CSV file. Blue fields are ones that are actually used
by SCUPI+:
• userId: an integer representing the user ID. The value of this is greater than 0.
• movieLensId: an integer representing the MovieLens ID. This is not used in this application, so
can be disregarded.
• tmdbId: an integer representing the film ID. The values for this directly correlates to the id field
in the movies data set.
• rating: a floating point value representing the rating between 0 and 5 inclusive.
• timestamp: a long integer representing the number of seconds from 1st January 1970 when the
rating was made. SCUPI+ passes this into a Java Calendar object.
3.6.5 Keywords
The following is a list all of the data stored about the keywords for a film using the column names
from the CSV file, in the same order they are in the CSV file. All these fields are used by SCUPI+:
• tmdb id: an integer representing the film ID. The values for this directly correlates to the id
field in the movies data set.
6• keywords: a JSON list that contains all the keywords relating to a given film. Each keyword is
represented as a key-value pair, where the key is represented as an ID number, and the value is
represented as a string. SCUPI+ passes this into an array of Keyword objects.
4 Submission
You should submit one .zip file, containing the following files:
• (50 marks) Three data store files for marking the unit tests:
– src/main/java/stores/Movies.java
– src/main/java/stores/Credits.java
– src/main/java/stores/Ratings.java
Also, submit any data structure files that has been created by you (DO NOT submit the
MyArrayList we provided). Please note that when using these data structures, please place
them under the directory src/main/java/structures, as what we will do when running your
program.
• (50 marks) A PDF report (≤ 1500 words) discussing the data structure(s) you have implemented
for the 3 data stores. More specifically:
– (20 marks) Justify your choice of the data structure(s) among so many other data structures.
–
(20 marks) Discuss how you use the data structure(s) to build the required operations in
the 3 data stores.
– (10 marks) An extra 10 marks are for the organisation and presentation of your report.
In the end, please don’t forget to compress all these files into a .zip file, and name the .zip file as:
CS 04450 Data Structure, Department of Computer Science, SCUPI
Spring 2024
This coursework sheet explains the work in details. Please read the instructions carefully and
follow them step-by-step. For submission instructions, please read the Sec. 4. If you have any
queries regarding the understanding of the coursework sheet, please contact the TAs or the
course leader. Due on: 23:59 PM, Wednesday, June 5th.
1 Introduction
A developer of a new Java application has asked for your help in storing a large amount of fflm data
efffciently. The application, called SCUPI+, is used to present data and fun facts about fflms, the
cast and crew who worked on them, and some ratings the developer has gathered in there free time.
However, because the developer hasn’t taken the module, they don’t want to design how the data is
stored.
Therefore, this coursework and the task that the developer has left to you, is to design one or more
data structures that can efffciently store and search through the data. The data consists of 3 separate
ffles:
• Movie Metadata: the data about the fflms, including there ID number, title, length, overview
etc.
• Credits: the data about who stared in and produced the fflms.
• Ratings: the data about what different users thought about the fflms (rated out of 5 stars), and
when the user rated the fflm.
To help out, the developer of SCUPI+ has provided classes for each of these. Each class has been
populated with functions with JavaDoc preambles that need to be fflled in by you. As well as this,
the developer has also tried to implement the MyArrayList data structure into a 4th dataset (called
Keywords), to show you where to store your data structures and how they can be incorporated into
the pre-made classes. Finally, the developer has left instructions for you, which include how to build,
run and test you code; and the ffle structure of the application (see Sec. 3).
Therefore, your task is to implement the functions within the Movies, Credits and Ratings classes
through the use of your own data structures.
2 Guidance
First, don’t panic! Have a read through the documentation provided in Sec. 3. This explains how to
build and run the application. This can be done without writing anything, so make sure you can do
that ffrst.
Then you can have a look at the comments and functions found in the Movies, Credits and
Ratings classes. The location of these is described in Sec. 3.5.2. Each of the functions you need to
implement has a comment above it, describing what it should do. It also lists each of the parameters
1for the function (lines starting with @param), and what the function should return (lines starting with
@return).
When you are ready to start coding, We would recommend starting off with the Rating class
ffrst. This is because it is smallest of the 3 required, and is also one of the simplest. When you have
completed a function, you can test it using the test suit described in Sec. 3.5.3. More details about
where the code for the tests are can be found in Sec. 3.4.
3 SCUPI+
SCUPI+ is a small Java application that pulls in data from a collection of Comma Separated Value
(CSV) ffles. It is designed to have a lightweight user interface (UI), so that users can inspect and
query the data. The application also has a testing suit connected to it, to ensure all the functions
work as expected. The functions called in the SCUPI+ UI are the same as those called in the testing,
so if the tests work, the UI will also work.
3.1 Required Software
For the SCUPI+ to compile and run, Java 21 is required, make sure you download this speciffc version
of Java. Whilst a newer version of Java can be utilised, other parts of the application will also have to
be updated and this has not been tested. Although you can always have a try with your own version,
it is highly recommended you download and use Java 21.
3.2 Building SCUPI+
To compile the code, simply run the command shown in the table below in the working directory (the
one with src folder in it).
Linux/DCS System MacOS Windows
./gradlew build ./gradlew build ./gradlew.bat build
3.3 Running the SCUPI+ Application
To run the application, simply run the command shown in the table below in the working directory
(the one with src folder in it).
Linux/DCS System MacOS Windows
./gradlew run ./gradlew run ./gradlew.bat run
This command will also compile the code, in case any ffles have been changed. When this is done,
a window will appear with the UI for the application. The terminal will not be able to be used at this
time. Instead it will print anything required from the program. To stop the application, simply close
the window or press CTRL+C at the same time in the terminal.
23.4 Running the SCUPI+ Test Suit
To run the tests, simply run the command shown in the table below in the working directory (the one
with src folder in it).
Linux/DCS System MacOS Windows
./gradlew test ./gradlew test ./gradlew.bat test
This command will also compile the code, in case any ffles have been changed. When ran, this will
produce the output from each test function. It will also produce a webpage of the results, which can
be found in build/reports/tests/test/index.html
3.5 SCUPI+ File Structure
Every effort has been made to keep the ffle structure simple and clean, whilst maintaining good coding
practices. In the following subsections, a brief description of each of the key directories is given, along
with its contents and what you need to worry about in them.
3.5.1 data/
This directory stores all the data ffles that are pulled into the application. There are 4 .csv ffles in
this directory, 1 for each of the datasets described in Sec. 1. Each line in these ffles is a different entry,
with values being separated by commas (hence the name Comma Separated Values). You do not need
to add, edit or remove anything from this directory for your coursework. More details on how these
ffles are structured can be found in Sec. 3.6.
3.5.2 src/main/
This directory stores all the Java code for the application. As such, there are a number of directories
and ffles in this directory, each of which are required for the application and/or the UI to function.
To make things simpler, there are 3 key directories that will be useful for you:
• java/interfaces/: stores the interface classes for the data sets. You do not need to add, edit
or remove anything from this directory, but it may be useful to read through.
• java/stores/: stores the classes for the data sets. This is where the Keywords, Movies, Credits
and Ratings from Sec. 1 are located, the latter 3 of which are the classes you need to complete.
Therefore, you should only need to edit the following ffles:
– Movies.java: stores and queries all the data about the fflms. The code in this ffle relies
on the Company and Genre classes.
– Credits.java: stores and queries all the data about who stared in and worked on the
fflms. The code in this ffle relies on the CastCredit, CrewCredit and Person classes.
– Ratings.java: stores and queries all the data about the ratings given to fflms.
• java/structures/: stores the classes for your data structures. As an example, a array list
MyArrayList has been provided there. Any classes you add in here can be accessed by the classes
in the stores directory (assuming the classes you add are public). You may add any ffles you wish
to this directory, but MyArrayList.java and IList.java should not be altered or removed, as
these are relied on for Keywords.
33.5.3 src/test/
This directory stores all the code that related solely to the JUnit tests. As such, there is a Java ffle
for each of the stores you need to implement. You do not need to add, edit or remove anything from
this directory for your coursework.
3.6 Data used for SCUPI+
All of the data used by the SCUPI+ application can be found in the data directory. Each ffle in
this directory contains a large collection of values, separated by commas (hence the CSV ffle type).
Therefore, each of these can be opened by your favourite spreadsheet program. Most of these values
are integers or ffoating point values, but some are strings. In the cases of strings, double quotation
marks (”) are used at the beginning and end of the value. Where multiple elements could exist in that
value, a JSON object has been used. You do not need to parse these ffles, SCUPI+ will do that for
you in the LoadData class. The data generated by the LoadData class is passed to the corresponding
data store class (Movies, Credits, Ratings and Keywords) using the add function.
To make development easier, we have provided only 1000 fflms present in the data. This means
that there are 1000 entries in the credits data set, and 1000 entries in the keywords data set. However,
some fflms may not have any cast and/or crew (that information may not have been released yet, or
it is unknown), some fflms don’t have keywords and some fflms may not have ratings. In these cases,
an empty list of the required classes will be provided the add function.
3.6.1 Key Stats
Films 1000
Credits
Film Entries 1000
Unique Cast 11483
Unique Crew 9256
Ratings 17625
Keywords
Film Entires 1000
Unique Keywords 2159
3.6.2 Movies Metadata
The following is a list all of the data stored about a fflm using the column names from the CSV ffle, in
the same order they are in the CSV ffle. Blue ffelds are ones that are added through the add function
in the Movies class.
• adult: a boolean representing whether the fflm is an adult fflm.
• belongs to collection: a JSON object that stores all the details about the collection a fflm
is part of. This is added to the fflm using the addToCollection function in the Movies class.
If the fflm is part of a collection, the collection will contain a collection ID, a collection name, a
poster URL related to the collection and a backdrop URL related to the collection.
• budget: a long integer that stores the budget of the fflm in US Dollars. If the budget is not
known, then the budget is set to 0. Therefore, this will always be greater than or equal to 0.
• genres: a JSON list that contain all the genres the fflms is part of. Each genre is represented
as a key-value pair, where the key is represented as an ID number, and the value is represented
as a string. SCUPI+ passes this as an array of Genre objects.
4• homepage: a string representing a URL of the homepage of the fflm. If the fflm has no homepage,
then this string is left empty.
• tmdb id: an integer representing the ID of the fflm. This is used to link this fflm to other pieces
of data in other data sets.
• imdb id: a string representing the unique part of the IMDb URL for a given fflm. This is added
using the setIMDB function in the Movies class.
• original language: a 2-character string representing the ISO 639 language that the fflm was
originally produced in.
• original title: a string representing the original title of the fflm. This may be the same as
the title ffeld, but is not always the case.
• overview: a string representing the an overview of the fflm.
• popularity: a ffoating point value that represents the relative popularity of the fflm. This value
is always greater than or equal to 0. This data is added by the setPopularity function in the
Movies class.
• poster path: a string representing the unique part of a URL for the fflm poster. Not all fflms
have a poster available. In these cases, an empty string is given.
• production companies: a JSON list that stores the production countries for a fflm. Each entry
in the JSON list has a key value pair, where the key is the ID of the company, and the value is
the name of the company. SCUPI+ parses each list element into a Company object. This object
is the added using the addProductionCompany in the Movies class.
• production countries: a JSON list that stores the production countries for a fflm. Each entry
in the JSON list has a key value pair, where the key is the ISO 3166 2-character string, and the
value is the country name. SCUPI+ parses only handles the key, and uses a function to match
this to the country name. This string is added using the addProductionCountry in the Movies
class.
• release date: a long integer representing the number of seconds from 1
st January 1970 when
the fflm was released. SCUPI+ passes this into a Java Calendar object.
• revenue: a long integer representing the amount of money made by the fflm in US Dollars. If
the revenue of the fflm is not known, then the revenue is set to 0. Therefore, this will always be
greater than or equal to 0.
• runtime: a ffoating point value representing the number of minutes the fflm takes to play. If the
runtime is not know, then the runtime is set to 0. Therefore, this will always be greater than or
equal to 0.
• spoken languages: a JSON list that stores all the languages that the fflm is available in. This
is stored as a list of key-value pairs, where the key is the 2 -character ISO 639 code, and the
value is the language name. SCUPI+ parses these as an array of keys stored as strings.
• status: a string representing the current state of the fflm.
• tagline: a string representing the poster tagline of the fflm. A fflm is not guaranteed to have
a tagline. In these cases, an empty string is presented.
• title: a string representing the English title of the fflm.
• video: a boolean representing whether the fflm is a ”direct-to-video” fflm.
5• vote average: a floating point value representing an average score as given by a those on IMDb
at the time the data was collected. As such, it is not used in the Review dataset. The score will
always be between 0 and 10. This data is added using the setVote function in the Movies class.
• vote count: an integer representing the number of votes on IMDb at the time the data was
collected, to calculate the score for vote average. As such, it is not used in the Review dataset.
This will always be greater than or equal to 0. This data is added using the setVote function
in the Movies class.
3.6.3 Credits
The following is a list all of the data stored about the cast and crew of a film using the column names
from the CSV file, in the same order they are in the CSV file. All these fields are used by SCUPI+:
• cast: a JSON list that contains all the cast for a particular film. In the JSON list, each cast
member has details that relate to there role in the film and themselves. SCUPI+ passes this
into an array of Cast objects, with as many fields populated as possible.
• crew: a JSON list that contains all the crew for a particular film. In the JSON list, each crew
member has details that relate to there role in the film and themselves. SCUPI+ passes this
into an array of Crew objects, with as many fields populated as possible.
• tmdb id: an integer representing the film ID. The values for this directly correlates to the id
field in the movies data set.
3.6.4 Ratings
The following is a list all of the data stored about the ratings for a film using the column names from
the CSV file, in the same order they are in the CSV file. Blue fields are ones that are actually used
by SCUPI+:
• userId: an integer representing the user ID. The value of this is greater than 0.
• movieLensId: an integer representing the MovieLens ID. This is not used in this application, so
can be disregarded.
• tmdbId: an integer representing the film ID. The values for this directly correlates to the id field
in the movies data set.
• rating: a floating point value representing the rating between 0 and 5 inclusive.
• timestamp: a long integer representing the number of seconds from 1st January 1970 when the
rating was made. SCUPI+ passes this into a Java Calendar object.
3.6.5 Keywords
The following is a list all of the data stored about the keywords for a film using the column names
from the CSV file, in the same order they are in the CSV file. All these fields are used by SCUPI+:
• tmdb id: an integer representing the film ID. The values for this directly correlates to the id
field in the movies data set.
6• keywords: a JSON list that contains all the keywords relating to a given film. Each keyword is
represented as a key-value pair, where the key is represented as an ID number, and the value is
represented as a string. SCUPI+ passes this into an array of Keyword objects.
4 Submission
You should submit one .zip file, containing the following files:
• (50 marks) Three data store files for marking the unit tests:
– src/main/java/stores/Movies.java
– src/main/java/stores/Credits.java
– src/main/java/stores/Ratings.java
Also, submit any data structure files that has been created by you (DO NOT submit the
MyArrayList we provided). Please note that when using these data structures, please place
them under the directory src/main/java/structures, as what we will do when running your
program.
• (50 marks) A PDF report (≤ 1500 words) discussing the data structure(s) you have implemented
for the 3 data stores. More specifically:
– (20 marks) Justify your choice of the data structure(s) among so many other data structures.
–
(20 marks) Discuss how you use the data structure(s) to build the required operations in
the 3 data stores.
– (10 marks) An extra 10 marks are for the organisation and presentation of your report.
In the end, please don’t forget to compress all these files into a .zip file, and name the .zip file as: