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13,200 | class treemap(linkedbinarytreemapbase) """sorted map implementation using binary search tree "" override position class class position(linkedbinarytree position) def key(self) """return key of map key-value pair "" return self elementkey def value(self) """return value of map key-value pair "" return self elementvalue ... |
13,201 | def first(self)"""return the first position in the tree (or none if empty""return self subtree first position(self root)if len(self else none def last(self)"""return the last position in the tree (or none if empty""return self subtree last position(self root)if len(self else none def before(selfp)"""return the position... |
13,202 | def find min(self)"""return (key,valuepair with minimum key (or none if empty""if self is empty)return none elsep self firstreturn ( key) value)def find ge(selfk)"""return (key,valuepair with least key greater than or equal to return none if there does not exist such key ""if self is empty)return none elsemay not find ... |
13,203 | def getitem (selfk)"""return value associated with key (raise keyerror if not found""if self is empty)raise keyerrorkey errorrepr( )elsep self subtree search(self root)khook for balanced tree subclasses self rebalance access(pif ! key)raise keyerrorkey errorrepr( )return valuedef setitem (selfkv)"""assign value to key ... |
13,204 | def delete(selfp)"""remove the item at given position ""inherited from linkedbinarytree self validate(pif self left(pand self right( ) has two children replacement self subtree last position(self left( )from linkedbinarytree self replace(preplacement element) replacement now has at most one child parent self parent(pin... |
13,205 | operation in [ ] [kv delete( )del [kt find position(kt first) last) find min) find maxt before( ) after(pt find lt( ) find le( ) find gt( ) find ge(kt find range(startstopiter( )reversed(trunning time (ho(ho(ho(ho(ho(ho(ho( ho(ntable worst-case running times of the operations for treemap we denote the current height of... |
13,206 | balanced search trees in the closing of the previous sectionwe noted that if we could assume random series of insertions and removalsthe standard binary search tree supports (log nexpected running times for the basic map operations howeverwe may only claim (nworst-case timebecause some sequences of operations may lead ... |
13,207 | search trees in the context of tree-balancing algorithma rotation allows the shape of tree to be modified while maintaining the search tree property if used wiselythis operation can be performed to avoid highly unbalanced tree configurations for examplea rightward rotation from the first formation of figure to the seco... |
13,208 | = = single rotation = = = = (ac= = single rotation = = = = (ba= = double rotation = = = = (cc= = double rotation = = = = (dfigure schematic illustration of trinode restructuring operation( and brequire single rotation( and drequire double rotation |
13,209 | python framework for balancing search trees our treemap classintroduced in section is concrete map implementation that does not perform any explicit balancing operations howeverwe designed that class to also serve as base class for other subclasses that implement more advanced tree-balancing algorithms summary of our i... |
13,210 | def rebalance insert(selfp)pass def rebalance delete(selfp)pass def rebalance access(selfp)pass code fragment additional code for the treemap class (continued from code fragment )providing stubs for the rebalancing hooks nonpublic methods for rotating and restructuring second form of support for balanced search trees i... |
13,211 | def relink(selfparentchildmake left child)"""relink parent node with child node (we allow child to be none""make it left child if make left childparent left child elsemake it right child parent right child if child is not nonemake child point to parent child parent parent def rotate(selfp)"""rotate position above its p... |
13,212 | avl trees the treemap classwhich uses standard binary search tree as its data structureshould be an efficient map data structurebut its worst-case performance for the various operations is linear timebecause it is possible that series of operations results in tree with linear height in this sectionwe describe simple ba... |
13,213 | an immediate consequence of the height-balance property is that subtree of an avl tree is itself an avl tree the height-balance property has also the important consequence of keeping the height smallas shown in the following proposition proposition the height of an avl tree storing entries is (log njustificationinstead... |
13,214 | by substituting the above value of in formula we obtainfor > - + * - ( > - ( > - ( by taking logarithms of both sides of formula we obtain log( ( ) from which we get log( ( ) ( which implies that an avl tree storing entries has height at most logn by proposition and the analysis of binary search trees given in section... |
13,215 | ( (bfigure an example insertion of an item with key in the avl tree of figure (aafter adding new node for key the nodes storing keys and become unbalanced(ba trinode restructuring restores the height-balance property we show the heights of nodes above themand we identify the nodes xyand and subtrees and participating i... |
13,216 | + + - - (ah+ + + - (bh+ + + - (cfigure rebalancing of subtree during typical insertion into an avl tree(abefore the insertion(bafter an insertion in subtree causes imbalance at (cafter restoring balance with trinode restructuring notice that the overall height of the subtree after the insertion is the same as before th... |
13,217 | deletion recall that deletion from regular binary search tree results in the structural removal of node having either zero or one children such change may violate the height-balance property in an avl tree in particularif position represents the parent of the removed node in tree there may be an unbalanced node on the ... |
13,218 | performance of avl trees by proposition the height of an avl tree with items is guaranteed to be (log nbecause the standard binary search tree operation had running times bounded by the height (see table )and because the additional work in maintaining balance factors and restructuring an avl tree can be bounded by the ... |
13,219 | python implementation complete implementation of an avltreemap class is provided in code fragments and it inherits from the standard treemap class and relies on the balancing framework described in section we highlight two important aspects of our implementation firstthe avltreemap overrides the definition of the neste... |
13,220 | positional-based utility methods def recompute height(selfp) node height max( node left height) node right height)def isbalanced(selfp)return abs( node left heightp node right height)< def tall child(selfpfavorleft=false)parameter controls tiebreaker if node left height( if favorleft else node right height)return self ... |
13,221 | splay trees the next search tree structure we study is known as splay tree this structure is conceptually quite different from the other balanced search trees we discuss in this for splay tree does not strictly enforce logarithmic upper bound on the height of the tree in factthere are no additional heightbalanceor othe... |
13,222 | zig-zagone of and is left child and the other is right child (see figure in this casewe promote by making have and as its childrenwhile maintaining the inorder relationships of the nodes in (at (bfigure zig-zag(abefore(bafter there is another symmetric configuration where is right child and is left child zigx does not ... |
13,223 | ( ( (cfigure example of splaying node(asplaying the node storing starts with zig-zag(bafter the zig-zag(cthe next step will be zig-zig (continues in figure |
13,224 | ( ( ( figure example of splaying node:(dafter the zig-zig(ethe next step is again zig-zig( after the zig-zig (continued from figure |
13,225 | when to splay the rules that dictate when splaying is performed are as followswhen searching for key kif is found at position pwe splay pelse we splay the leaf position at which the search terminates unsuccessfully for examplethe splaying in figures and would be performed after searching successfully for key or unsucce... |
13,226 | when deleting key kwe splay the position that is the parent of the removed noderecall that by the removal algorithm for binary search treesthe removed node may be that originally containing kor descendant node with replacement key an example of splaying following deletion is shown in figure ( ( ( ( (efigure deletion fr... |
13,227 | python implementation although the mathematical analysis of splay tree' performance is complex (see section )the implementation of splay trees is rather simple adaptation to standard binary search tree code fragment provides complete implementation of splaytreemap classbased upon the underlying treemap class and use of... |
13,228 | amortized analysis of splaying after zig-zig or zig-zagthe depth of position decreases by twoand after zig the depth of decreases by one thusif has depth dsplaying consists of sequence of / zig-zigs and/or zig-zagsplus one final zig if is odd since single zig-zigzig-zagor zig affects constant number of nodesit can be... |
13,229 | an accounting analysis of splaying when we perform splayingwe pay certain number of cyber-dollars (the exact value of the payment will be determined at the end of our analysiswe distinguish three casesif the payment is equal to the splaying workthen we use it all to pay for the splaying if the payment is greater than t... |
13,230 | proposition let be the variation of ( caused by single splaying substep ( zigzig-zigor zig-zagfor node in we have the followingd < ( (xr( ) if the substep is zig-zig or zig-zag < ( (xr( )if the substep is zig justificationwe use the fact (see proposition appendix athatif and blog log log ( let us consider the change in... |
13,231 | proposition let be splay tree with root and let be the total variation of ( caused by splaying node at depth we have < ( (tr( ) justificationsplaying node consists of / splaying substepseach of which is zig-zig or zig-zagexcept possibly the last onewhich is zig if is odd let (xr(xbe the initial rank of xand for clet ri... |
13,232 | when deleting node from splay tree with keysthe ranks of all the ancestors of are decreased thusthe total variation of ( caused by the deletion is negativeand we do not need to make any payment to maintain the invariant when node is deleted thereforewe may summarize our amortized analysis in the following proposition (... |
13,233 | ( , trees in this sectionwe consider data structure known as ( , tree it is particular example of more general structure known as multiway search treein which internal nodes may have more than two children other forms of multiway search trees will be discussed in section multiway search trees recall that general trees ... |
13,234 | ( ( (cfigure (aa multiway search tree (bsearch path in for key (unsuccessful search)(csearch path in for key (successful search |
13,235 | searching in multiway tree searching for an item with key in multiway search tree is simple we perform such search by tracing path in starting at the root (see figure and when we are at -node during this searchwe compare the key with the keys kd- stored at if ki for some ithe search is successfully completed otherwisew... |
13,236 | ( , )-tree operations multiway search tree that keeps the secondary data structures stored at each node small and also keeps the primary multiway tree balanced is the ( treewhich is sometimes called - tree or tree this data structure achieves these goals by maintaining two simple properties (see figure )size propertyev... |
13,237 | of ( treewe must have at least nodes at depth at least nodes at depth and so on thusthe number of external nodes in is at least in additionby proposition the number of external nodes in is thereforewe obtain < < taking the logarithm in base of the terms for the above inequalitieswe get that <log( < hwhich justifies our... |
13,238 | (au ww (bc (cfigure node split(aoverflow at -node (bthe third key of inserted into the parent of (cnode replaced with -node and -node ( ( ( ( ( ( figure an insertion in ( tree that causes cascading split(abefore the insertion(binsertion of causing an overflow(ca split(dafter the split new overflow occurs(eanother spli... |
13,239 | ( ( ( ( ( ( ( ( ( ( ( (lfigure sequence of insertions into ( tree(ainitial tree with one item(binsertion of (cinsertion of (dinsertion of which causes an overflow(esplitwhich causes the creation of new root node( after the split(ginsertion of (hinsertion of which causes an overflow(isplit(jafter the split(kinsertion of... |
13,240 | analysis of insertion in ( , tree because dmax is at most the original search for the placement of new key uses ( time at each leveland thus (log ntime overallsince the height of the tree is (log nby proposition the modifications to single node to insert new key and child can be implemented to run in ( timeas can singl... |
13,241 | ( ( ( ( ( ( ( (hfigure sequence of removals from ( tree(aremoval of causing an underflow(ba transfer operation(cafter the transfer operation(dremoval of causing an underflow(ea fusion operation( after the fusion operation(gremoval of (hafter removing |
13,242 | fusion operation at node may cause new underflow to occur at the parent of wwhich in turn triggers transfer or fusion at (see figure hencethe number of fusion operations is bounded by the height of the treewhich is (log nby proposition if an underflow propagates all the way up to the rootthen the root is simply deleted... |
13,243 | red-black trees although avl trees and ( trees have number of nice propertiesthey also have some disadvantages for instanceavl trees may require many restructure operations (rotationsto be performed after deletionand ( trees may require many split or fusing operations to be performed after an insertion or removal the d... |
13,244 | figure an illustration that the red-black tree of figure corresponds to the ( tree of figure based on the highlighted grouping of red nodes with their black parents if is -nodethen keep the (blackchildren of as is if is -nodethen create new red node ygive ' last two (blackchildren to yand make the first child of and be... |
13,245 | justificationlet be red-black tree storing entriesand let be the height of we justify this proposition by establishing the following factlog( < < log( let be the common black depth of all nodes of having zero or one children let be the ( tree associated with and let be the height of (excluding trivial leavesbecause of ... |
13,246 | case the sibling of is black (or none(see figure in this casethe double red denotes the fact that we have added the new node to corresponding -node of the ( tree effectively creating malformed -node this formation has one red node (ythat is the parent of another red node ( )while we want it to have the two red nodes as... |
13,247 | case the sibling of is red (see figure in this casethe double red denotes an overflow in the corresponding ( tree to fix the problemwe perform the equivalent of split operation namelywe do recoloringwe color and black and their parent red (unless is the rootin which caseit remains blacknotice that unless is the rootthe... |
13,248 | ( ( ( ( ( ( ( ( ( ( ( (lfigure sequence of insertions in red-black tree(ainitial tree(binsertion of (cinsertion of which causes double red(dafter restructuring(einsertion of which causes double red( after recoloring (the root remains black)(ginsertion of (hinsertion of (iinsertion of which causes double red(jafter rest... |
13,249 | ( ( ( ( (qfigure sequence of insertions in red-black tree(minsertion of which causes double red(nafter restructuring(oinsertion of which causes double red(pafter recoloring there is again double redto be handled by restructuring(qafter restructuring (continued from figure |
13,250 | deletion deleting an item with key from red-black tree initially proceeds as for binary search tree (section structurallythe process results in the removal node that has at most one child (either that originally containing key or its inorder predecessorand the promotion of its remaining child (if anyif the removed node... |
13,251 | we consider three possible cases to remedy deficit case node is black and has red child (see figure we perform trinode restructuringas originally described in section the operation restructure(xtakes the node xits parent yand grandparent zlabels them temporarily left to right as aband cand replaces with the node labele... |
13,252 | case node is black and both children of are black (or noneresolving this case corresponds to fusion operation in the corresponding ( tree as must represent -node we do recoloringwe color redandif is redwe color it black (see figure this does not introduce any red violationbecause does not have red child in the case tha... |
13,253 | case node is red (see figure because is red and theavy has black depth at least must be black and the two subtrees of must each have black root and black depth equal to that of theavy in this casewe perform rotation about and zand then recolor black and red this denotes reorientation of -node in the corresponding ( tre... |
13,254 | ( ( ( ( ( ( ( ( ( ( (kfigure sequence of deletions from red-black tree(ainitial tree(bremoval of (cremoval of causing black deficit to the right of (handled by restructuring)(dafter restructuring(eremoval of ( removal of causing black deficit to the right of (handled by recoloring)(gafter recoloring(hremoval of (iremov... |
13,255 | performance of red-black trees the asymptotic performance of red-black tree is identical to that of an avl tree or ( tree in terms of the sorted map adtwith guaranteed logarithmic time bounds for most operations (see table for summary of the avl performance the primary advantage of red-black tree is that an insertion o... |
13,256 | python implementation complete implementation of redblacktreemap class is provided in code fragments through it inherits from the standard treemap class and relies on the balancing framework described in section we beginin code fragment by overriding the definition of the nested node class to introduce an additional bo... |
13,257 | positional-based utility methods we consider nonexistent child to be trivially black def set red(selfp) node red true def set black(selfp) node red false def set color(selfpmake red) node red make red def is red(selfp)return is not none and node red def is red leaf(selfp)return self is red(pand self is leaf(pdef get re... |
13,258 | support for deletions def rebalance delete(selfp)if len(self= special caseensure that root is black self set black(self root)elif is not nonen self num children(pif = deficit exists unless child is red leaf next(self children( )if not self is red leaf( )self fix deficit(pcelif = removed black node with red child if sel... |
13,259 | exercises for help with exercisesplease visit the sitewww wiley com/college/goodrich reinforcement - if we insert the entries ( )( )( , )( )and ( )in this orderinto an initially empty binary search treewhat will it look liker- insertinto an empty binary search treeentries with keys (in this orderdraw the tree after eac... |
13,260 | - the rules for deletion in an avl tree specifically require that when the two subtrees of the node denoted as have equal heightchild should be chosen to be "alignedwith (so that and are both left children or both right childrento better understand this requirementrepeat exercise assuming we picked the misaligned choic... |
13,261 | - consider tree storing , entries what is the worst-case height of in the following casesa is binary search tree is an avl tree is splay tree is ( tree is red-black tree - draw an example of red-black tree that is not an avl tree - let be red-black tree and let be the position of the parent of the original node that is... |
13,262 | - describe how to perform an operation remove range(startstopthat removes all the items whose keys fall within range(startstopin sorted map that is implemented with binary search tree and show that this method runs in time ( )where is the number of items removed and is the height of - repeat the previous problem using ... |
13,263 | - if the approach described in the previous problem were implemented as part of the treemap classwhat additional modifications (if anywould be necessary to subclass such as avltreemap in order to maintain the efficiencyc- for standard binary search treetable claims ( )-time performance for the delete(pmethod explain wh... |
13,264 | - the standard splaying step requires two passesone downward pass to find the node to splayfollowed by an upward pass to splay the node describe method for splaying and searching for in one downward pass each substep now requires that you consider the next two nodes in the path down to xwith possible zig substep perfor... |
13,265 | - write python class that can take any red-black tree and convert it into its corresponding ( tree and can take any ( tree and convert it into its corresponding red-black tree - in describing multisets and multimaps in section we describe general approach for adapting traditional map by storing all duplicates within se... |
13,266 | notes some of the data structures discussed in this are extensively covered by knuth in his sorting and searching book [ ]and by mehlhorn in [ avl trees are due to adel'son-vel'skii and landis [ ]who invented this class of balanced search trees in binary search treesavl treesand hashing are described in knuth' sorting ... |
13,267 | sorting and selection contents why study sorting algorithms merge-sort divide-and-conquer array-based implementation of merge-sort the running time of merge-sort merge-sort and recurrence equations alternative implementations of merge-sort quick-sort randomized quick-sort additional optimizations for quick-sort studyin... |
13,268 | why study sorting algorithmsmuch of this focuses on algorithms for sorting collection of objects given collectionthe goal is to rearrange the elements so that they are ordered from smallest to largest (or to produce new copy of the sequence with such an orderas we did when studying priority queues (see section )we assu... |
13,269 | merge-sort divide-and-conquer the first two algorithms we describe in this merge-sort and quick-sortuse recursion in an algorithmic design pattern called divide-and-conquer we have already seen the power of recursion in describing algorithms in an elegant manner (see the divide-and-conquer pattern consists of the follo... |
13,270 | we can visualize an execution of the merge-sort algorithm by means of binary tree called the merge-sort tree each node of represents recursive invocation (or callof the merge-sort algorithm we associate with each node of the sequence that is processed by the invocation associated with the children of node are associate... |
13,271 | ( ( ( ( ( ( figure visualization of an execution of merge-sort each node of the tree represents recursive call of merge-sort the nodes drawn with dashed lines represent calls that have not been made yet the node drawn with thick lines represents the current call the empty nodes drawn with thin lines represent completed... |
13,272 | ( ( ( ( ( (lfigure visualization of an execution of merge-sort (combined with figures and |
13,273 | ( ( ( (pfigure visualization of an execution of merge-sort (continued from figure several invocations are omitted between (mand (nnote the merging of two halves performed in step (pproposition the merge-sort tree associated with an execution of mergesort on sequence of size has height log nwe leave the justification of... |
13,274 | array-based implementation of merge-sort we begin by focusing on the case when sequence of items is represented as an (array-basedpython list the merge function (code fragment is responsible for the subtask of merging two previously sorted sequencess and with the output copied into we copy one element during each pass ... |
13,275 | sorting and selection def merge sort( ) """sort the elements of python list using the merge-sort algorithm "" len( if return list is already sorted divide mid / [ :midcopy of first half [mid:ncopy of second half conquer (with recursionsort copy of first half merge sort( sort copy of second half merge sort( merge result... |
13,276 | merge-sort tree as portrayed in figures through can guide our analysis consider recursive call associated with node of the merge-sort tree the divide step at node is straightforwardthis step runs in time proportional to the size of the sequence for vbased on the use of slicing to create copies of the two list halves we... |
13,277 | sorting and selection merge-sort and recurrence equations there is another way to justify that the running time of the merge-sort algorithm is ( log (proposition namelywe can deal more directly with the recursive nature of the merge-sort algorithm in this sectionwe present such an analysis of the running time of merge-... |
13,278 | alternative implementations of merge-sort sorting linked lists the merge-sort algorithm can easily be adapted to use any form of basic queue as its container type in code fragment we provide such an implementationbased on use of the linkedqueue class from section the ( log nbound for merge-sort from proposition applies... |
13,279 | (as (bs (cs (ds ( ( ( (hs (ifigure example of an execution of the merge algorithmas implemented in code fragment using queues |
13,280 | bottom-up (nonrecursivemerge-sort there is nonrecursive version of array-based merge-sortwhich runs in ( log ntime it is bit faster than recursive merge-sort in practiceas it avoids the extra overheads of recursive calls and temporary memory at each level the main idea is to perform merge-sort bottom-upperforming the m... |
13,281 | quick-sort the next sorting algorithm we discuss is called quick-sort like merge-sortthis algorithm is also based on the divide-and-conquer paradigmbut it uses this technique in somewhat opposite manneras all the hard work is done before the recursive calls high-level description of quick-sort the quick-sort algorithm ... |
13,282 | like merge-sortthe execution of quick-sort can be visualized by means of binary recursion treecalled the quick-sort tree figure summarizes an execution of the quick-sort algorithm by showing the input and output sequences processed at each node of the quick-sort tree the step-by-step evolution of the quick-sort tree is... |
13,283 | ( ( ( ( ( ( figure visualization of quick-sort each node of the tree represents recursive call the nodes drawn with dashed lines represent calls that have not been made yet the node drawn with thick lines represents the running invocation the empty nodes drawn with thin lines represent terminated calls the remaining no... |
13,284 | ( ( ( ( ( (lfigure visualization of an execution of quick-sort note the concatenation step performed in ( (continues in figure |
13,285 | ( ( ( ( ( (rfigure visualization of an execution of quick-sort several invocations between (pand (qhave been omitted note the concatenation steps performed in (oand ( (continued from figure |
13,286 | performing quick-sort on general sequences in code fragment we give an implementation of the quick-sort algorithm that works on any sequence type that operates as queue this particular version relies on the linkedqueue class from section we provide more streamlined implementation of quick-sort using an array-based sequ... |
13,287 | running time of quick-sort we can analyze the running time of quick-sort with the same technique used for merge-sort in section namelywe can identify the time spent at each node of the quick-sort tree and sum up the running times for all the nodes examining code fragment we see that the divide step and the final concat... |
13,288 | randomized quick-sort one common method for analyzing quick-sort is to assume that the pivot will always divide the sequence in reasonably balanced manner we feel such an assumption would presuppose knowledge about the input distribution that is typically not availablehowever for examplewe would have to assume that we ... |
13,289 | now consider recursion trace for randomized quick-sort this trace defines binary treet such that each node in corresponds to different recursive call on subproblem of sorting portion of the original list say that node in is in size group if the size of ' subproblem is greater than ( / ) + and at most ( / ) let us analy... |
13,290 | additional optimizations for quick-sort an algorithm is in-place if it uses only small amount of memory in addition to that needed for the original input our implementation of heap-sortfrom section is an example of such an in-place sorting algorithm our implementation of quick-sort from code fragment does not qualify a... |
13,291 | divide step is performed by scanning the array simultaneously using local variables leftwhich advances forwardand rightwhich advances backwardswapping pairs of elements that are in reverse orderas shown in figure when these two indices pass each otherthe division step is complete and the algorithm completes by recurrin... |
13,292 | although the implementation we describe in this section for dividing the sequence into two pieces is in-placewe note that the complete quick-sort algorithm needs space for stack proportional to the depth of the recursion treewhich in this case can be as large as admittedlythe expected stack depth is (log )which is smal... |
13,293 | studying sorting through an algorithmic lens recapping our discussions on sorting to this pointwe have described several methods with either worst case or expected running time of ( log non an input sequence of size these methods include merge-sort and quick-sortdescribed in this as well as heap-sort (section in this s... |
13,294 | permutations and of are associated with the same external nodethen there are at least two objects xi and such that xi is before in but xi is after in at the same timethe output associated with must be specific reordering of swith either xi or appearing before the other but if and both cause the sorting algorithm to out... |
13,295 | linear-time sortingbucket-sort and radix-sort in the previous sectionwe showed that ( log ntime is necessaryin the worst caseto sort an -element sequence with comparison-based sorting algorithm natural question to askthenis whether there are other kinds of sorting algorithms that can be designed to run asymptotically f... |
13,296 | it is easy to see that bucket-sort runs in ( ntime and uses ( nspace hencebucket-sort is efficient when the range of values for the keys is small compared to the sequence size nsay (nor ( log nstillits performance deteriorates as grows compared to an important property of the bucket-sort algorithm is that it works corr... |
13,297 | sorting and selection to gain intuition before answering this questionwe consider the following example example consider the following sequence (we show only the keys) (( )( )( )( )( )( )( )( )if we sort stably on the first componentthen we get the sequence (( )( )( )( )( )( )( )( )if we then stably sort this sequence ... |
13,298 | comparing sorting algorithms at this pointit might be useful for us to take moment and consider all the algorithms we have studied in this book to sort an -element sequence considering running time and other factors we have studied several methodssuch as insertion-sortand selection-sortthat have ( )-time behavior in th... |
13,299 | quick-sort although its ( )-time worst-case performance makes quick-sort susceptible in real-time applications where we must make guarantees on the time needed to complete sorting operationwe expect its performance to be ( log )-timeand experimental studies have shown that it outperforms both heap-sort and merge-sort o... |
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