: Improving Efficiency With Linked Lists Solved (Best price and Top Grade Guaranteed)

Nobel Prize week has just ended, so this assignment will have a nice tie-in to both what we’ve been talking about in lecture and to these prestigious prizes in science. The 1978 Nobel Prize in physiology and medicine was awarded to Werner Arber, Dan Nathans, and Hamilton Smith for their discovery, study, and application of restriction enzymes. Quoting from the press release1:
Restriction enzymes provide the “chemical knives” to cut genes (= DNA) into defined fragments.
These may then be used (1) to determine the order of genes on chromosomes, (2) to analyse the chemical structure of genes and of regions of DNA which regulate the function of genes, and (3) to create new combinations of genes. These techniques open up new avenues to study the organisation and expression of genes of higher animals and to solve basic problems in developmental biology. In medicine, increased knowledge in this area should help in the
prevention and treatment of malformations, hereditary diseases and cancer.
This assignment will simulate the use of restriction enzymes to cut a DNA strand (“DNA cleavage”) and splice in new genetic material to form recombinant DNA. The science behind this is fascinating but mostly irrelevant to the assignment itself. None of us have to understand the science in order to complete the assignment. The main points of the assignment are (1) to provide experience in developing a software solution in the context of a real problem, (2) to provide experience in developing programs that build linked lists, and (3) to provide insight into how linked lists can offer efficiency advantages over arrays in certain circumstances.
The simulation that we’re implementing is a simplification of one part of the chemical process known as molecular cloning. We’ve provided files for you to work with:
 DnaStrand.java – This is an interface that describes the abstract behavior necessary to simulate
DNA being cleaved by a restriction enzyme and having new genetic material spliced in.
 ArrayStrand.java – This is a class that implements DnaStrand and uses an array (a String, specifically)
to store the DNA “information” (the nucleotides). This class is completely implemented for
you and provides a reference for the expected behavior.
 LinkedStrand.java – Only the shell of this class is provided for you, and it is the implementation
of this class that comprises most of the work for the assignment.
 DNASimulation.java – This is a class that simulates the repeated cleaving and splicing of DNA
strands using restriction enzymes. It’s output displays various statistics about the simulation to help
you gauge the efficiency of the underlying DnaStrand implementations.
1http://www.nobelprize.org/nobel_prizes/medicine/laureates/1978/press.html

COMP 2210
 A5report – This is a plain text file that contains the shell of a “lab report” for this assignment. You must provide good answers to each of the questions/prompts provided. Make sure you keep this a plain text file. Using Markdown2 is fine (it you want), but keep it text.
 ecoli.dat – This is a plain text file that contains the DNA sequence3 for a strain of Escherichia coli4
(E. coli) bacteria (4,639,201 base pairs).
 ecolimed.dat – This is a plain text file that contains a subset of the DNA sequence for a strain of E.
coli (320,101 base pairs).
To complete the assignment, you must do the following things.
(1) Benchmark the array-based implementation. You will use the DNASimulation class to benchmark
the ArrayStrand implementation of DnaStrand, and document this in A5report. Specifically:
a. Show that ArrayStrand.cutAndSplice() is O(N) where N is the size of the recombined strand
returned by the method. Document your work in the appropriate section of A5report. You can use
either ecoli.dat or ecolimed.dat for the simulation.
b. Determine the largest power-of-two sized splice (the string spliced into the DNA strand) that
the simulation supports without generating a java.lang.OutOfMemoryError when run using the
-Xmx512M heap size request. Document your work in the appropriate section of A5report. You
must use ecoli.dat with the restriction enzyme EcoRI (“gaattc”) for the simulation, and the length
of the splice string must be a power of two.
c. Double the size of heap memory available to the simulation (i.e., -Xmx1024M). With twice as much
memory available, can your machine support the large splice that it couldn’t handle before? If so,
how long did it take to produce this next-larger splice? Document your work in the appropriate
section of A5report. You must use ecoli.dat with the restriction enzyme EcoRI (“gaattc”) for the
simulation, and the length of the splice string must be a power of two.
d. Keep doubling the size of heap memory until your machine can no longer support the request.
What splice sizes and running times do you observe for each heap doubling? Document your work
in the appropriate section of A5report. You must use ecoli.dat with the restriction enzyme EcoRI
(“gaattc”) for the simulation, and the length of the splice string must be a power of two.
(2) Implement LinkedStrand. After completing all the analyses in step 1, you must design, code, and test
the LinkedStrand class. A description of the approach to the implementation is given a later section,
and you must adhere to this description.
(3) Empirically Verify LinkedStrand’s Efficiency. Once you have implemented LinkedStrand correctly,
you must empirically verify that the LinkedStrand implementation is more efficient than ArrayStrand,
and document this in the appropriate section of A5report. Specifically:
a. Show that the time complexity of LinkedStrand.cutAndSplice() is independent of N where N
is the size of the recombined strand returned by the method. That is, you will show that the
new implementation is O(1) with respect to the size of the recombinant DNA. Document your work
in the appropriate section of A5report. You can use either ecoli.dat or ecolimed.dat for the
simulation.
2https://help.github.com/articles/markdown-basics/
3http://www.genome.wisc.edu/sequencing.htm
4http://en.wikipedia.org/wiki/Escherichia_coli
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COMP 2210 Fall 2014
b. Determine the largest power-of-two sized splice (the string spliced into the DNA strand) that
the simulation supports without generating a java.lang.OutOfMemoryError when run using the
-Xmx512M heap size request. Document your work in the appropriate section of A5report. You
must use ecoli.dat with the restriction enzyme EcoRI (“gaattc”) for the simulation, and the length
of the splice string must be a power of two.
c. Double the size of heap memory available to the simulation (i.e., -Xmx1024M). With twice as much
memory available, can your machine support the large splice that it couldn’t handle before? If so,
how long did it take to produce this next-larger splice? Document your work in the appropriate
section of A5report. You must use ecoli.dat with the restriction enzyme EcoRI (“gaattc”) for the
simulation, and the length of the splice string must be a power of two.
d. Keep doubling the size of heap memory until your machine can no longer support the request.
What splice sizes and running times do you observe for each heap doubling? Document your work
in the appropriate section of A5report. You must use ecoli.dat with the restriction enzyme EcoRI
(“gaattc”) for the simulation, and the length of the splice string must be a power of two.
Restriction Enzyme Cleaving
We’ll need a little background information on DNA and restriction enzyme cleaving to understand the
code you’ll be writing, modifying, and analyzing.
DNA is formed by two biopolymer strands coiled around each other in the shape of a double helix.
A strand of DNA is composed of nucleotides, which in turn are composed (in part) of four protein bases
– guanine (G), adenine (A), thymine (T), and cytosine (C). As a simplification, we will model DNA as
having only one strand instead of two, and we will represent this single strand as simply a sequence of
bases, like this: “AGTCGAATTCAAGTCGAATTCAGTCA.”
Enzymes5 are biological catalysts responsible for many biochemical processes. Restriction enzymes6
are enzymes that cut a DNA strand at particular locations. An example restriction enzyme is EcoRI7:
“GAATTC.” A restriction enzymes locates each occurrence of its pattern in the DNA strand and cuts the
strand into two pieces at each of those points (the binding sites or restriction sites), leaving either “blunt” or
“sticky” ends. Other chemical processes can be used to bind genetic material to these blunt or sticky ends
and produce recombinant DNA. As a simplification, we will ignore the distinction of blunt v. sticky ends,
and we will model the cuts and splices as simply string deletion/replacement.
There are two distinct cut-related DnaStrand methods: cutWith(enzyme) and cutAndSplice(enzyme,
splice). The cutWith method cuts the strand of DNA at the first binding site of the specified enzyme.
This method replaces its strand with the sequence that precedes the binding site and returns the sequence
after the binding site. The cutAndSplice method cuts the strand of DNA at every binding site of the
specified enzyme, replacing the enzyme sequence with the specified splice sequence. This method leaves
the original DNA strand unchanged and returns the new recombinant DNA.
As examples of these two operations, consider the DNA sequence shown in Figure 1 and the restriction
enzyme shown in Figure 2. Note that there are two occurrences of the restriction enzyme (i.e., two binding
sites) in the DNA, as shown in Figure 3.
A G T C G A A T T C A A G T C G A A T T C A G T C A
Figure 1: A sample DNA strand.
5http://en.wikipedia.org/wiki/Enzyme
6http://en.wikipedia.org/wiki/Restriction_enzyme
7http://en.wikipedia.org/wiki/EcoRI
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COMP 2210 Fall 2014
G A A T T C
Figure 2: The restriction enzyme EcoRI
A G T C G A A T T C A A G T C G A A T T C A G T C A
Figure 3: A DNA strand with EcoRI binding sites highlighted.
Let dna be the DNA strand in Figure 1, let enzyme be the restriction enzyme in Figure 2, and let splice
be the DNA strand “XXYY.” The behavior of the two cut methods is as follows:
 The effect on dna of dna.cutWith(enzyme) is shown in Figure 4.
 The return value of dna.cutWith(enzyme) is shown in Figure 5.
 The effect on dna of dna.cutAndSplice(enzyme, splice) is shown in Figure 1; i.e., no effect.
 The return value of dna.cutAndSplice(enzyme, splice) is shown in Figure 6.
A G T C
Figure 4: Effect on dna of dna.cutWith(enzyme).
A A G T C G A A T T C A G T C A
Figure 5: Return value of dna.cutWith(enzyme).
A G T C X X Y Y A A G T C X X Y Y A G T C A
Figure 6: Return value of dna.cutAndSplice(enzyme, splice).
An Array-based Implementation
Given the discussion above, an array-based implementation of DnaStrand is an intuitive and natural fit.
Specifically, the DNA strand information could be stored as an array of strings, and we can rely on methods
from class String and StringBuilder to implement the DnaStrand methods. In this implementation,
Figures 1 through 6 look identical to our underlying representations (minus the indexes).
The class ArrayStrand is a full implementation of the DnaStrand interface using strings as the underlying
physical representation. Your first step in the assignment will be to study this implementation.
Make sure you understand the implementation of each DnaStrand method, and make sure you understand
each String and StringBuilder method that is used. jGRASP viewers should be very helpful
here. For example, Figure 7 shows the source code for the cutAndSplice method, and Figure 8 shows a
jGRASP viewer canvas depicting the execution of this method during a debug session.
Although this array-based implementation may be intuitive, it is inefficient with respect to both time
and memory usage. For example, the operation that physically splices in new DNA (recombined.append(splice)
in Figure 7) is O(N) for a splice of length N. Thus the cost of creating a recombinant strand, that is, the
time complexity of cutAndSplice with an N-length splice with B binding sites is B [1] N, which is O(N).
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COMP 2210 Fall 2014
public DnaStrand cutAndSplice(String enzyme, String splice){
String toSplit = ” “+dnaInfo+” “;
String[] all = toSplit.split(enzyme);
if (all[0].trim().equals(dnaInfo)){
return EMPTY_STRAND;
}
StringBuilder recombined = new StringBuilder(all[0]);
for (int k = 1; k < all.length; k++) {
recombined.append(splice);
recombined.append(all[k]);
}
return new ArrayStrand(recombined.toString().trim());
}
Figure 7: Source code for ArrayStrand.cutAndSplice.
Figure 8: A jGRASP viewer canvas during the execution of ArrayStrand.cutAndSplice.
The amount of memory required is also linear in the size of the splice. Memory on the order of
B [1] N + M is required to splice an N-length strand into a M-length strand with B binding sites. This
more than the time complexity significantly limits the scalability of the array-based solution.
Alternate Implementation: Linked Lists
We can make a significant improvement in efficiency by basing our implementation on a linked list rather
than a single array/string. A linked node representation will enable cutAndSplice and append to be
implemented by adding nodes to a linked list rather than copying arrays.
You must develop LinkedStrand as an alternate implementation of DnaStrand based on linked nodes,
subject to the following items.
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COMP 2210 Fall 2014
 The node class has been written for you as a nested class in LinkedStrand. Do not make any
changes to the Node class.
 The LinkedStrand class must maintain two fields, front and rear that reference the first and last
nodes respectively of the linked list. These fields have been declared for you as public. Do not
change the visibility of these fields. They must be public.
 An empty LinkedStrand object has front and rear set to null. This is embodied in the parameterless
contructor provided for you. Do not change this constructor.
 A non-empty LinkedStrand object starts out with exactly one node, which front and rear both
reference. For example, the effect of new LinkedStrand(“AGTCGAATTCCATTG”) is shown in Figure 9.
 The size method must be O(1).
 The cutWith method must be O(1).
 The cutAndSplice method must be O(1) with respect to the size of the splice, but may be linear
with respect to the number of binding cites of the enzyme.
 The cutAndSplice method must not call the String.split() method like the ArrayStrand implementation
does. Instead, it should call the String.indexOf(str, fromIndex) method and one or
more of the String.substring() methods.
 The cutAndSplice method must not create a larger string, append to a string, or use a StringBuilder
as the ArrayStrand implementation does. Instead, it must create and link new nodes to model splicing
material into several binding sites. For example, if dna is the LinkedStrand shown in Figure 9,
the the return value of dna.cutAndSplice(“GAATTC”, “XXYY”) is shown in Figure 10.
 The cutWith and cutAndSplice methods should only operate on newly initialized strands; that
is, those containing a single node. These methods throw an IllegalStateException if the strand
contains multiple nodes.
 The append(DnaStrand) and append(String) methods must be O(1).
A G T C G A A T T C C A T T G
front
rear
Figure 9: A newly initialized LinkedStrand
A G T C X X Y Y C A T T G
front rear
Figure 10: A LinkedStrand after a cutAndSplice operation.
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COMP 2210 Fall 2014
Assignment Submission
You must turn in both LinkedStrand.java and A5report to Web-CAT for grading. While not required,
it is strongly recommended that you also submit your own test cases. Note the following rules regarding
your Web-CAT submissions:
 The feedback hints for failed test cases will be unavailable beginning one day prior to the assignment
due date.
 You can submit to Web-CAT no more than ten times for this assignment.
 The last submission that you make to Web-CAT will be used to determine your grade on the assignment,
even if its score is lower than that of an earlier submission.
 Submissions made within the 24 hour period after the published deadline will be assessed a late
penalty of 15 points.
 No submissions will be accepted more than 24 hours after the published deadline.
Acknowledgment
This assignment was adapted from an idea and assignment originally developed by Owen Astrachan.
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