java编程代写、Genetic Improvement 算法代写
Assignment 3: Genetic Improvement of Source Code
with GIN
Formative, Weight(10%), Learning objectives (1,2,3),
Abstraction (4), Design (4), Communication (4), Data (5), Programming (5)
Due date: 11:59pm, 3 November 2017, Weight: 10.0 % of the course
1 Overview
Assignments should be done in groups consisting of two (2) students. If you have problems
finding a group partner use the forum to search for group partners or contact the lecturer.
Quick Summary
Genetic improvement (GI) applies evolutionary algorithms to modify programs to improve
some aspect of their behaviour. Program behaviours that we might use GI to improve
can include: speed, correctness, accuracy, memory footprint and energy use.
The input to a GI process are:
1. The program P to be improved.
2. A set of test cases T which P can be run against.
3. A program M that measures the performance of P(T) (P ran against T).
The program M measures the performance of P in the way that we want the program
improved. For example, if we want to improve program speed of P then M will simply
time P(T) (whilst ensuring that P still passes all of its test cases). As another example,
if we just wanted to improve the correctness of P then we would write M to count the
number of test cases passed.
The output of the GI process is just a patch consisting of a sequence of edits to change
the program. When the GI process finishes it applies the patch and presents us with the
improved program for us to check and deploy.
For this assignment you will conduct a series of experiments in GI using a new GI framework
called GIN (Genetic Improvement in No-time). GIN is small, simple, and easy to
change - and it works on Java programs. At the moment GIN is set up to improve just
one thing: program speed! However, it can also be used to fix simple errors in code and
well use it for that as well. For this assignment you will have to hand in a report briefly
describing a series of four sets of experiments that you will do. In your experiments you
will have to write some code - you will include a listing of the code you wrote at the end
of your report.
Details of each section of the report follow but first we describe how to set up GIN.
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COMP SCI 4409/4809/7409 Search-Based Software Engineering Semester 2, 2017
Getting GIN
GIN is available online at: https://github.com/gintool/gin and the README.md
file tells you what you need to do to run the project. However, to get things started
faster you can download the GIN implementation included in the zip file attached to
this assignment.1 The zip file is simply the GIN distribution with the source code precompiled
and some of the examples tweaked. To run GIN you will need to use a machine
that has Java 1.8, JavaParser and JUnit. To modify GIN (which you will need to do in
Exercise 3) you will also need Gradle. These all tend to work most smoothly on linux
distributions and we have tested them on a linux virtual machine. If you are using the
University machines then you can download the zip file into your home directory.
2 Assignment
Exercise 1 Running GIN and measuring its performance (20 points)
Download the GIN zip file and change to the gin-master/ directory. Type:
java -jar build/gin.jar examples/locoGP/SortBubbleDouble.java
this will call a program called LocalSearch.java which uses evolutionary search to build a
set of patches to fix the SortBubbleDouble.java program. While searching GIN will run
the test programs in SortBubbleDoubleTest.java to ensure that the patches dont break
the program. The output of GIN is a list of patches that it tries. You can see that some
of the patches break the program but some cause it to run faster. You might notice that
the patches start with words like MOVE, COPY and DELETE. This is because GIN
works by moving, copying and deleting existing lines of code in the program. It doesnt
make up any new code.
When GIN has finished you should see a file called SortBubbleDouble.java.optimised in
the examples/locoGP directory. Have a look at this file. Is this code better than the
original program? If so, how?
For this part of the assignment you are to track and graph the performance of GIN on
the following four programs in the locoGP directory:
? SortBubbleDouble.java
? SortBubbleLoops.java
? SortInsertion.java
? SortCocktail.java
The easiest way to collect the initial and running best times for the modified programs
is to run with a grep filter afterwards, for example:
java -jar build/gin.jar examples/locoGP/SortInsertion.java — grep -E ”.*(best—Initial)”
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see https://myuni-canvas.adelaide.edu.au/files/1955412/download?download_frd=1
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COMP SCI 4409/4809/7409 Search-Based Software Engineering Semester 2, 2017
Run these experiments at least 15 times for each of the four programs above. Collect and
graph the data for the best times. After each run quickly check the optimised program and
make a quick description of the change made (and whether it is one that an experienced
programmer would make).
Present the setup and the results of your experiments, including the graphs in your report.
This section must be no more than two pages. In this section make sure you include the
aim of your experiment, the methodology of your experiment and the results and your
interpretation of the results.
Exercise 2 Analysing Patches (20 points)
Choose one of the benchmarks you ran from Exercise 1 which regularly produced patches
more than one edit long (Note: patches consisting of one edit only are not very interesting
for this section). Run the benchmark multiple times. Record the edits in the final patch
each time. Record which edits appear most often and the positions of those edits in the
patch. Provide a visualisation of this data in your report.
Look at the source code of the benchmark program and assess the effect of the edits.
Do they have the same effect as the edits in other patches. From your observations is it
possible to deduce a shortened version of a patch which achieves the same result as the
derived patches? If there is a shorter version (or versions) of a patch describe this patch
and what it does in your report.
As with the first section, describe your aims, your methodology, your results and your
analysis in your report. Again, this section should be no more than two pages long.
Exercise 3 Minimising Patches (40 points)
This exercise is more challenging! For this part of the assignment you will have to
modify the source code of GIN to post-process the patches found so that they contain
the minimum number of edits necessary to produce the same final optimised program.
To do this you need to write code that takes the final patch and uses search to find
which edits in that patch have no effect on the final optimised program. The choice of
search technique is up to you but it has to be effective and it should be efficient. Note
that, because there are multiple patches that will produce the same final program your
modifications wont always produce the same edits but the edits that your search retains
must produce the same result as the original patch.
For this part of the assignment you will need to edit the source code for GIN. As a starting
point read the search() method in the file:
gin-master/src/main/java/gin/LocalSearch.java
The patch minimisation process should be called after the search has finished and the
best patch is found.
For this section of your report you must briefly describe what your changes aim to do,
describe your methodology, in this case, the algorithm you are implementing and the
data structures it is working over. You should also briefly present your results. In the
appendix of the report you must include a listing of the source code changes that you
have made to GIN.
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COMP SCI 4409/4809/7409 Search-Based Software Engineering Semester 2, 2017
Exercise 4 Your Own Case-Study (20 points)
Here, you must create your own case study program to run GIN against. To do this
you will need to provide a benchmark program that is not optimally efficient and run
GIN against it in order to improve its efficiency. The program that you are modifying
can be your own or it can be published and publicly available code (you must provide
adequate references in this latter case). You are allowed to modify the code to introduce
a source of inefficiency or - even better - you can use an example where the inefficiency
was pre-existing.
For this section of the report you should introduce the program (include the program
source in the appendix of the report), the source of inefficiency and then present the
results of running GIN against this program. If your benchmark program has multiple
sources of inefficiency or there are multiple ways to optimise the program then your
analysis can be staged so that GIN first runs against simpler variants of the program
before running against more challenging versions.
3 General procedure for handing in the assignment
Work should be handed in using the course website. The submission should include:
? pdf file of your report
? all source files (if you created any) including the modified GIN implementation
? a file name README.txt that contains instructions to run the code (if any), the
names, student numbers, and email addresses of the group members
? for each group, there should be only 1 submission
Acknowledgment
Many thanks go to Brad Alexander for contributing this assignment.
http://www.6daixie.com/contents/9/1292.html
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