Harsh-7300/dataset huggingface dataset:
Question: What are the criteria of algorithm analysis?
Reference answer: An algorithm are generally analyzed on two factors − time and space. That is, how much execution time and how much extra space required by the algorithm.

Student answer: Algorithm analysis works on the criteria of building a solution which is generalized for same category of problems ,we describe the main function which is to be executed to solve the problem.
Score: 0.0

Student answer: The criteria to understand the algorithm analysis is delta, omega theta etc.
Score: 0.0

Student answer: to analysis the algorithm see the number of steps formed number of line 
Score: 0.0

Student answer: There are two criteria for algorithm analysis:-\n1. Time complexity analysis: To determine the time taken by the algorithm.\n2. Space Complexity Analysis: To determine the space used by the algorithm for the whole processing as well as generating output.
Score: 2.5

Student answer: algorithm can be analysed by 4 methods \n1) substitution method \n2) recursive method\n3) tree method\n4) master theorem
Score: 0.0

Student answer: There are some criteria of algorithm analysis:\n--> Subsitution method \n-->
Score: 0.0

Student answer: criteria of algorithm analysis are time complexity , what approach a algorithm is based.\n
Score: 2.0

Student answer: in order to do algorithm analysis we must know firstly the asymptotic notations 
Score: 0.0

Student answer: Space complexity and Time complexity are the two main criteria of algorithm analysis.
Score: 2.5

Student answer: criteria of algorithm analysis is time complexity and space complexity.
Score: 2.5

Student answer: criteria of algorithm analysis is to know about the problem first and divide it into fewer subproblems and come to solution at last
Score: 0.0

Student answer: Criteria of algorithm analysis :-\n1) substitution analysis\n2) interpret analysis\n3) divide and conquer analysis
Score: 0.0

Student answer: The worst case is always given priority when doing algorithm analysis\nWe should look at the complexity when the independent variable which is time is tending to infinity\n
Score: 0.0

Student answer: The basic criteria of algorithm analysis is that problem must be divided into sub problems.
Score: 0.0

Student answer: like we see the time complexity and space complexity that problem has and among various thinking process and approach towards particular problem we are able to know the best technique. 
Score: 2.5

Student answer: criteria of algorithm analysis is to make the code to algo to easy understanding .
Score: 0.5

Student answer: criteria for algorithm analysis is to minimize the time complexity and storage required to run the program.
Score: 2.5

Student answer: The criteria is to maintain the time complexity and optimize a code to get a peak outcome of the product so that the major criteria is time complexity 
Score: 2.0

Student answer: the criteria of algorithm analysis\n1) time efficient\n2) space efficient
Score: 2.5

Student answer: time and storage and resources
Score: 2.5

Student answer: recursive function, time compexity etc.
Score: 2.0
Question: What are the criteria of algorithm analysis?
Reference answer: An algorithm are generally analyzed on two factors − time and space. That is, how much execution time and how much extra space required by the algorithm.

Student answer: the criteria for analysis is that we give anylaze algs on each step and combine all the results that are griven from the indivdual solution 
Score: 0.0

Student answer: criteria of algorithms analysis is notation, searching, time complexity, 
Score: 0.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: asymptotic analysis of an algorithm is to determine the algorithm belongs to BigOh(theta), bigoh(omega), smalloh(theta)
Score: 1.0

Student answer: its calculate the running time of the algorithm
Score: 2.0

Student answer: Asymptotic analysis is used to show three basic cases of any algorithm, namely: 1) The Best Case, 2) The Average Case, 3) The Worst Case; which calculate the complexities for the best case of the algorithm, general case of any algorithm, and the worst case respectively
Score: 2.5

Student answer: Asymptotic analysis is a way of representing the time complexity of an algorithm. It allows us to bound the time taken by the algorithm in 1)Lower bound(minimum time taken) 2) Upper bound(maximum time taken) 3) Average bound. 
Score: 2.5

Student answer: Asymptotic analysis of an algorithm is a type of analysis to find the upper and lower bound of the complexity of algorithm.
Score: 2.0

Student answer: asymptotic analysis of an algorithm is a process of calculating the running time of an algorithm in mathematical unit to find programs limitation. 
Score: 2.0

Student answer: asymptotic analysis of an algorithm inform us about where the time complexity of an algorithm lie whether it is in upper bound (O) avg bound (theta) lower bound (omega)
Score: 2.5

Student answer: Asymptotic analysis divides the time taken by algorithm into three parts that is worst case best case and average case time
Score: 2.0

Student answer: asymptotic analysis is to analyze the time complexity as well as the space complexity of the given program
Score: 2.5

Student answer: To study the complexity of a given problem such as finding the best or worst or average time complexity  asymptotic notations are being analyzed.
Score: 2.5

Student answer: Asymptotic analysis is done to get the knowledge of time taking at every step of an algorithm and to  know the overall time complexity of the algorithm.
Score: 2.5

Student answer: Asymptotic analysis algorithm is an algorithm which defines the ultimate answer or solutions of the program we are running.
Score: 2.5

Student answer: The calculation of time taken for each statement in the program to execute based on the complexity of that statement is asymptotic analysis.
Score: 2.0

Student answer: asymptotic analysis involves the use of \nbig o \ntheta\nomega notations for knowing the time complexities of a program
Score: 1.0

Student answer: Asymptotic analysis refer to determining a mathematical expression for Time and Space complexity of an algorithm. \n
Score: 1.0

Student answer: Asymptotic analysis refers analyzing the algorithm based on certain parameters such as no of iteration in a loop, no of iterations in a recursive function, etc.\n
Score: 1.0

Student answer: asymptotic notation are used to calculate the time complexities  in term of equal ,less, more 
Score: 2.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis helps us to analize the algorithm using certain notations.
Score: 1.0

Student answer: Asymptotic analysis is the analysis regarding time and space complexities of various cases  like best , worst and average cases in an algorithm. This analysis helps us in improving the overall efficiency of an algorithm.
Score: 2.0

Student answer: Asymptotic notation gives us a method for classifying functions according to their rate of growth. 
Score: 1.0

Student answer: Asymptotic Analysis shows the complexities of algorithm which is being solved through some particular notations,which makes it easier to know which algorithm takes more time and which is optimised. It is recognised by the functions and algorithm used in program.
Score: 1.5

Student answer: Asymptotic analysis of algorithm deals with the time and memory the algorithm uses to function. 
Score: 1.5

Student answer: here we analyise the lower bound of the solution time complexity , like our solution existing time complexity is O(n) then its lower bound should be also O(n)
Score: 1.0

Student answer: To find the time and space taken by an algorithm to function o different types of test cases.
Score: 1.0

Student answer: The analysis of an algorithm in the form of algebraic functions to denote the time or space consumed by the program is knows as Asymptotic analysis. 
Score: 1.0

Student answer: The analysis of an algorithm in the form of an algebraic function and denotes the time and space consumed by the algorithm is known as asymptotic analysis.
Score: 1.5

Student answer: Asymptotic analysis of an algorithm means finding the time complexity of an algorithm on the basis of its recurrence relation or given algorithm using substitution method, recurrence tree method, master's theorem, etc.
Score: 1.5

Student answer: The asymptotic analysis of an algorithm is to represent an algorithm in some type of notation so that we will analysis it further. we analysis the algorithm in many ways :\n1)with the help of Reccurance.  relation\n2)by plotting the graph and analysing it\n3)with the help of master theorem\n
Score: 1.0

Student answer: study of an algorithm in terms of mathematical expression and using math graph is basically asymptotic analysis of algorithm.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm means whether the time complexity of an algorithm will be in big-oh, omega , or theta. There is specific criteria to identify whether we have to take big-oh, omega or in theta. 
Score: 1.0

Student answer: Asymptotic analysis of an algorithm refers to the examining and analysis of a program to calculate its running time. We check the time taken by the program to give an output. 
Score: 1.0

Student answer: It tells the running time of the algorithm.\n
Score: 1.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic Analysis gives us the possible range of time that in how much time the algorithm is taking to run the program.
Score: 1.0

Student answer: Asymptotic analysis is a way to display the time complexity of a particular program in the form of equation by analyzing the code of that program.
Score: 1.0

Student answer: asymptotic analysis refers to the analysis approximated in the order of the fastest changing(growing) term without finding the exact duration for which it runs on the given problem.\n
Score: 1.0

Student answer: Asymptotic analysis of an algorithm is the analysis in order of the fastest changing, term without finding the exact term.
Score: 1.5

Student answer: Analysis of an algorithm for the lowest and upper bounds as well as the average bounds of time and space that the algorithm might consume to devise and compare for the most efficient ones is known as asymptotic analysis of an algorithm.
Score: 2.0

Student answer: writing a time complexity of an algorithm and then going by it is what 
Score: 1.0

Student answer: Asymptotic Analysis is analyzing an algorithm and designating appropriate symbols with its time complexity.
Score: 1.5

Student answer: The time taken by any algorithm for the completion of its full step is known as asymptotic analysis of an algorithm.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm analyzes the algorithm based on notations like theta notation to calculate the best-case scenario of a particular algorithm, big oh notation to calculate the worst-case time complexity and omega for average case. These notations compare the algorithms using graphs of functions used in algorithms.\n\nAsymptotic analysis involves calculating time complexities and space complexities.
Score: 1.5

Student answer: Asymptotic analysis of an algorithm is based a technique to analyze the Time and space complexity using Graph.\nits basically shows how with time the data grows, whether linearly or exponentially.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm is to execute the program in O(n) time complexity.
Score: 1.0

Student answer: asymptotic analysis of an algorithm is representing the time complexities of an algorithm in terms of O, theta and o.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm represents the time complexities of an algorithm in the form of O, o and omega.
Score: 1.0

Student answer: Asymptotic analysis is used to analysis algorithms to give the time complexity and space complexity of the algorithms using certain notations. These are the standard notations developed so that the complexity analyzed throughout remains same. 
Score: 1.0

Student answer: there are the representations to provide the time and space complexity of an algorithm. eg big Oh' (O) , theta, omega.
Score: 1.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis of an algorithm is a method used in computer science to analyze the performance of an algorithm in terms of the input size. It helps to determine how the algorithm's runtime and memory usage grow as the input size increases, and to compare different algorithms in terms of their efficiency.
Score: 1.0

Student answer: the mathematical definition of an algorithm is its asymptotic analysis.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm is calculating time and space complexity and representing them using different notations such as big O, omega and theta , i.e, best , average and worst complexity.
Score: 1.0

Student answer: The asymptotic analysis in done by the concept of best case , worst case and average cases which may occur in a program.
Score: 2.0

Student answer: Asymptotic analysis is the analysis of an algorithm for different test cases - the best case, average case and the worst test case.\n It allows you to find upper and lower bound complexities for your algorithm. 
Score: 2.5

Student answer: Asymptotic analysis of algorithm is used to determine the time complexity of programs
Score: 1.0

Student answer: Asymptotic analysis of an algorithm refers to the finding of best, worst and average time complexity of any algorithm.
Score: 2.5

Student answer: analysis of time taken
Score: 1.5

Student answer: Asymptotic analysis the big O notation and the time complexity of an algorithm so that we can choose the most efficient algo
Score: 1.0

Student answer: omega and big O notation
Score: 1.0

Student answer: asymptotic analysis of an algorithm is the mathematical representation of the run time of a program.
Score: 1.0

Student answer: When we have made a equation to represent the running time of an algorithm and we use it to find out the best , average or worst case running time that could be defined as the asympotic analysis of an algorithm.
Score: 1.0

Student answer: asymptomatic analysis of algorithm is is computing the running time of an algorithm in terms of mathematical function eg. f(n)
Score: 1.0

Student answer: The asymptotic analysis of an algorithm is to analysis it on the basis of its best, average or worst case time complexity.
Score: 2.5

Student answer: Asympotic notations have the bounded the mathematical formula in the algorithm .And with the help of the asympotic notation we can define the complexity of the alghorithm .\n 
Score: 0.0

Student answer: it is the method of analysis in which we meeasure the nest worst and average case scenario of a algorithm .in asymptotic algorithm input is needed if there is no input thrn program will run in constant time
Score: 2.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis goes through every line of the algorithm to find the mathematical equation of the time complexity of an algorithm. We can find either the best case, worst case or average time complexity of an algorithm using asymptotic analysis.
Score: 2.5

Student answer: time taken
Score: 1.0

Student answer: It is the analysis of the algorithm on three scenarios : best case , average case and worst case.\nOn the basis of the performance of the algorithm on these cases , we select the suitable algorithm for the given problem.
Score: 2.5

Student answer: Asymptotic analysis of an algorithm is the the various calculations that take place to calculate the time which a particular code takes from run-time to its final compilation.
Score: 1.5

Student answer: Process of calculating running time of an algorithm.
Score: 2.0

Student answer:  Asymptotic analysis of an algorithm is to analize the algo on the basis of three major cases that are:\n Best case, Average case, Worst case.
Score: 2.5

Student answer: Asymptotic analysis of an algorithm means analyzing an algorithm so that it takes as minimum time as possible and produces the best result.
Score: 1.0

Student answer: the asymptotic analysis of the algorithm is finding the trend of  time complexity of the algorithm when the number of elements (n) varies in the algorithm discarding other factors\nit can be exponential, log(N),o(N) and other 
Score: 1.0

Student answer: Asymptotic analysis is the process of calculating the running time of an algorithm or its run-time performance. The goal is to determine the best case, worst case and average case time required to execute a given task.
Score: 1.0

Student answer: it is the analysis of how much time an algorithm or line of code will take to execute. it can be calculated for the worst case scenario or average scenario.
Score: 2.0

Student answer: uper and lower bound is done in this
Score: 2.0

Student answer: Asymptotic analysis of an algorithm provides the necessary means to compare multiple algorithms and to find the best among them.\n
Score: 1.0

Student answer: exact time analysis,worst case time complexity and best case time complexity is the asymptotic analysis of the algorithm
Score: 1.0

Student answer: Asymptotic analysis of an algorithm refers to defining the framing of its run-time performance.
Score: 1.0

Student answer: asymptotic analysis is finding the best average and worst time complexities that a algorithm would take
Score: 2.0

Student answer:  Asymptotic analysis of an algorithm is done to find the complexity of the program such as time and space complexity so that we minimize the complexity if it takes more than required and make it an efficient and optimal algorithm
Score: 1.0

Student answer: analysis of algorithm based on it's graph function 
Score: 1.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis of an algorithm is mathematical foundation of its run time performance.
Score: 1.0

Student answer: asymptotic analysis of an algorithm helps us to calculate maximum and minimum time complexity of given function.  
Score: 2.0

Student answer: Analysis of the the time and space complexities of an algorithm
Score: 1.0

Student answer: Asymptotic analysis are the criteria of analysis is done there are worst case , best case , average case analysis.
Score: 2.5

Student answer:  explicit conplexities of algorithm.
Score: 1.0

Student answer: Asymptotic analysis tells us the degree of an algorithm.\nFor example: bubble sort has the time complexity O(N^2).\nHere O( ) is the asymptotic notation which tells the time complexity of the algorithm.
Score: 1.0

Student answer: it basically tells about the running time of an algorithm using the mathematial computation like 
Score: 1.0

Student answer: Asymptotic analysis of an algorithm means studying the algorithm on the basis of its upper bound or lower bound conditions that is analysis on the basis of best case , worst case and average case time complexities.
Score: 2.5

Student answer: In asymptotic analysis of an algorithm we find upper bound and lower bound 
Score: 2.0

Student answer: Asymptomatic analysis means when we analyze the algorithm on the basis if the most dominating term and do not consider the terms which don't have that much impact on the value of the time and space complexity
Score: 1.0

Student answer: asymptotic analysis of an algorithm refers to in how much time our program runs and how much space it requires to run to keep that in mind to design a best program.\nlike BIG OH (O(n)) here BIG OH refers to upper bound it will be maximum this value and not be greater than this.\nnext can be OMEGA (N) it refers to lower bound means min value, it will be greater than this value for sure.\nTHETA (N) refers to exact complexity of that particular algorithm 
Score: 1.0

Student answer: One of the method to analysis algorithm\nAsymptotic Analysis of algorithm is mainly actual time analysis of algorithm\nFrom which we get information about time measurement of algorithm
Score: 2.0

Student answer: asymptotic notations are basically a measure of time that a code takes to compile and run . \n
Score: 0.5

Student answer: The asymptotic analysis of an algorithm is the process of calculating the running time of an algorithm in mathematical units to find program limitations or run-tme performance.
Score: 1.0

Student answer: the most time can an algorithm take ,what is its upper bound,  least time it can take or its lower bound value and its worst case.\nafter this we have knowledge about each and every aspect of an algorithm.
Score: 2.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: it define the mathematical foundation of its run-time performance.  by using this we can conclude the best case, average case, and worst case scenario of an algorithm.
Score: 1.0

Student answer: We try to write equation of time complexity using asymptotic analysis. For example -> T(n)= 3*O(n^2)+2*O(n)
Score: 1.0

Student answer: Asymptotic analysis uses mathematical operations to find the best case, worst case and average case time complexity of an algorithm. It uses the plot of the assumed and approximate values and then perform operation to find complexities.
Score: 1.0

Student answer: asymptotic analysis is analyzing an algorithm for its best, worst and average case and finding the time and space complexity for respective cases.
Score: 1.0

Student answer: Asymptotic notation are used to compare and find the space and time complexities of the algo and optimize it
Score: 1.0

Student answer: Asymptotic analysis of an algorithm refers to analysis of time where time tends to infinity, covering all possible cases.
Score: 1.0

Student answer: asymptotic analysis is used for the efficiency of algorithms when  there are very large inputs also or inpits are tending to infinity.
Score: 2.0

Student answer: Comparison of time complexity based on the three notations.
Score: 2.0

Student answer: Analysis of the algorithm in the best, worst and average case is called asymptotic analysis.
Score: 2.0

Student answer: Helps to find the higher time limit of the algorithm( worst case), lower limit (best case) , average time (average case). It is done with help of asymptotic notations. Helps in comparison bw two algos
Score: 1.5

Student answer: In these type of notation the algorithm is judged on the basis of best case,worst case or average case scenarios.
Score: 1.5

Student answer: Defining a mathematical statement in order to compute the time taken by the algorithm in best case, worst case ,average case.
Score: 1.5

Student answer: Asymptotic analysis is the process of calculating the running time of an algorithm in mathematical units to find the programâ€™s limitations, or run-time performance. The goal is to determine the best case, worst case and average case time required to execute a given task.
Score: 2.0

Student answer: asymptotic analysis is used with the help of regression
Score: 2.0

Student answer: in which we compare time complexties of algorotihms on notations line big O\nomega etc.
Score: 1.0

Student answer: Asymptotic analysis is to anlayze an algorithm on the basis of notations like Big Oh, Big Omega and Big Theta.
Score: 2.5

Student answer: theta notation, bigO notation, o notation, omega notation
Score: 2.0

Student answer: The asymptotic analysis is the process of calculating the run time of a program in mathematical units to find the program's limitations or run-time performance.
Score: 2.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: asymptotic analysis is a process in which time complexity and space complexity of the algorithms are represented in the form of asymptotic notations like big-o and small-o in the order of n, log(n), n*log(n) and many more.
Score: 1.0

Student answer: analysis of algorithm on the basis of time complexity is called asymptotic analysis
Score: 1.0

Student answer: Asymptotic analysis refers to a criteria to determine the efficiency or complexity of the algorithms by the use of some symbols called \
Score: 1.0

Student answer: yes, algorithm  is asymptotic analysis   
Score: 2.0

Student answer: the analysis in which we calculate the running time 
Score: 2.0

Student answer: asymptotic analysis is when we take different testcases for an algorithm and try to found out its best, worst and mainly the average case of the approach using various methods like Master Theorem.
Score: 2.0

Student answer: In asymptotic analysis, We use Mathematical tools and calculation to analyze the time and space complexity of the algorithm. 
Score: 2.0

Student answer: asymptotic analysis of an algorithm are the analysis of space complexity and time complexity of the algorithms
Score: 1.0

Student answer: asymptotic analysis of an algorithm is analysis of algorithm as a function of time like O(n) this tells the order of function in which the analysis of algorithm takes place but it does not tell the exact time the algorithm's analysis has taken 
Score: 1.5

Student answer: The asymptotic analysis of algorithm helps in defining the best, average and worst time and space complexity of the program.
Score: 1.0

Student answer: in asymptotic analysis we analyse the best average an worst cases for a particular problem solution and compare them in their complexities.
Score: 1.0

Student answer: asymptotic analysis is finding the value of asymptotic notations like BIGO(n). o(n), thetha(n), each notation represent different thing .
Score: 2.0

Student answer: Asymptotic analysis of an algorithm is the process in which we approximate or try to calculate the max amount of a time a process can take. For example the some of the major problems require time complexities like O(n), O(n^2), etc these mean that in the case of n inputs that maximum time that the process can take is of n^2 complexity. Asymptotes are lines that come very close to one another but never touch each other. Similarly in asymptotic analysis the process can come very close to the complexity we have calculate but it never touches or exceeds it. 
Score: 2.0

Student answer: Defining the mathematical foundation of its run-time performance.
Score: 2.0

Student answer: The asymptotic analysis of an algorithm is that how much time that particular algorithm will take considering an average time criteria whether it should be less or more.
Score: 1.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: asymptotic analysis is about finding the range of time and space complexity
Score: 2.0

Student answer: Asymptotic notations stand for notations used to define or to structure their complexities. There are many types of asymptotic notations that are big-O, Big-Omega, Small o ,small Omega. Analysis by which we define and find the complexities of the algorithm we have structured is called asymptotic analysis.
Score: 2.0

Student answer: asymptotic analysis refer to the time limitations while solving a particular problem that is when the time tends to infinitely large number what is the behaviour of the graph of the function.
Score: 2.0

Student answer: Asymptotic analysis of an algorithm is getting the worst, average and best time complexity and space complexity of a problem. 
Score: 1.5

Student answer: Asymptotic means tends to infinity. By asymptotic analysis we mean to find how our algorithm will work when it is given large inputs which are tending to infinity.
Score: 1.5

Student answer: asymptotic analysis is analysing the algorithm according to its max and min time it takes.
Score: 2.0

Student answer: asymptotic analysis is the analysis of a code done before the code runs.
Score: 2.0

Student answer: Asymptotic analysis of an algorithm is the analysis of Time and space complexities as per tight upper boud, tight lower bound and tight average boud according to the requirement.
Score: 2.0

Student answer: a asymptotic analysis of a algorithm is to analyze an algorithm based on loops its takes in time complexity or new space used in space complexity
Score: 2.0

Student answer: Asymptotic analysis of an algorithm refers to the time analysis of a program based on its worst, average, and best case .
Score: 2.0

Student answer: it is a method to calculate time complexity of any algorithm.
Score: 2.0

Student answer: Asymptotic analysis of an algorithm has an 
Score: 2.0

Student answer: It is the mathematical approach of finding time or space complexity of an algorithm in which an algorithm is defined as a function of n (f(n)). 
Score: 2.0

Student answer: asymptotic analysis of algorithm is describe the mathematical framing while it is running
Score: 1.0

Student answer: The asymptotic analysis of an algorithm includes see how the function is growing over time using mathematical functions. we are more interested in degree of the polynomials. We don't need to look at all the cases but get a brief overview. Like we can look at the best case, worst case and average case and see overall and get idea of how the algorithm would be performing. these analysis then help us compare the different algorithms. 
Score: 1.5

Student answer: asymptomatic analysis of an algorithm is when algo is analyzed on the basis of input size.
Score: 1.5
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: in asymptotic analysis we take different test cases and find the best, worst and average test  case
Score: 1.5

Student answer: It is the process of calculating the run time of an algorithm.\n
Score: 2.0

Student answer: The asymptotic analysis of an algorithm is done to find out the Best, Average or worst case for the Time or Space complexity of a program
Score: 1.5

Student answer: Asymptotic analysis of the algorithm is to calculate or estimate the running time of the algorithm and therefore calculating the worst best and average case of the particular algorithm
Score: 1.5

Student answer: Asymptotic Analysis of an algorithm is 
Score: 1.5

Student answer: Asymptotic analysis of an algorithm is 
Score: 1.5

Student answer: The process of calculate the running time of algorithms in mathematical units to find the program limitations.
Score: 1.0

Student answer: It refers to giving mathematical foundation of its runtime performance.
Score: 1.0

Student answer: the analysis of the upper and lower bound of an algorithm is called its asymptotic analysis
Score: 1.5

Student answer: The asymptotic analysis refers to the study of running time of an algorithm.
Score: 1.5

Student answer: Analysis based on algorithm's time complextiy is called asmptotic analysis
Score: 2.0

Student answer: asymptotic ananlysis is the study of upper bound time or lower bound time complexity analysis of a particular algorithm.
Score: 2.0

Student answer: Asymptotic analysis is the process in which we  calculating the run time of an algorithm in mathematical units to find the programâ€™s limitations and run time perfomance.
Score: 2.0

Student answer: refers to computing the running time of any algorithm in mathematical units of computation.
Score: 1.0

Student answer: Asymptotic analysis include finding worst case time , best case time and average case time complexity for a particular algorithm.
Score: 2.0

Student answer: approx time complexity analysis of an algorithm.
Score: 1.0

Student answer: Asymptotic analysis of an algorithm refers to defining the mathematical foundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case, and worst-case scenario of an algorithm.\n
Score: 1.0

Student answer: it is the analysis in which we analyze the running time complexity of an algorithm for best ,average and worst case.
Score: 1.0

Student answer: An asymptotic analysis  of an algorithm is to analyze the code time complexity at every operation of the proposed algorithm so that we can get \nthe information about the time complexity of code\n
Score: 2.0

Student answer: asymptotic analysis of algorithm is analysis of algorithm in best time case ,average time case, and worst time case
Score: 2.0

Student answer:  increases the time complexity, any \
Score: 1.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis of an algorithm refers to defining the mathematical foundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case, and worst case scenario of an algorithm.
Score: 2.0

Student answer: In which we compare the problem statement at hand with a pre-existing analyzed statement. And we just try to reduce the complexities in the form of the other one. In this manner we can comment on the best case, worst case and average case time complexities.
Score: 1.0

Student answer: Asymptotic analysis represent to analyzing respective algorithm on basis of time and space:\nIt includes finding upper bound, lower bound ,average bound of a system by studying f(n),g(n) and respective best case, worst case and average case.  
Score: 1.0

Student answer: Asymptotic analysis of an algorithm is the ananlysis of algorithm to figure out the complexity of the algorithm.
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Student answer: Asymptotic analysis is done to check the time complexity of a program so that we can get an idea about the best and worst time it is taking to run a particular program.
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Student answer: Asymptomatic analysis gives a rough idea of the time the algorithm will take in execution given we have the variables like user-defined inputs.\nIt can be used for the analysis of the time complexity, space complexity or any required auxiliary space.
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Student answer: asymptotic analysis is done to check how good the Algorithm is and how much time it would be taking it is mainly used in calculating time complexity of a algorithm . there are different types of asymptotic notations like big O, theta, omega,
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Student answer: it is the analysis of time complexity of a given algorithm to get the complexity in best, average and worst time cases
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Student answer: It is the best , average and worst case time complexity of an algorithm. These can be used for comparison. 
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Student answer: It is analysis of the algorithm using a criteria in which we find time complexity of an algithm.
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Student answer: asymptotic analysis of an algorithm is a process to determine the time complexity of an algorithm using various theorems ,laws etc. , like master theorem can be used to find it's complexity effectively.
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Student answer: it  helps in giving the time complexity of a problem
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Student answer: It is the analysis of time complexty and space occupied.
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Student answer: thats the time depending approch for algorith.means that how much time will take the algorithm running ,like its have notation for describe the time complexity.  
Score: 2.0

Student answer: the analysis of the running time of a particular algorithm is called asymptotic analysis. it is algebraic or graphical in nature.
Score: 2.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: Asymptotic analysis of algorithm is an analysis where we calculate the time complexity of the algorithm.
Score: 2.0

Student answer: It refers to the analysis of time and space complexities of an algorithm
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Student answer: Determination of how an algorithm in perform in its best case and its worst case scenario helping .Time complexities are denoted with the symbols accordingly
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Student answer: Asymptotic Analysis of an algorithm 1)best case2)average case 3)worst case 
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Student answer: Asymptotic analysis deals with best case worst case and average case of an algorithm
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Student answer: The asymptotic notation of an algorithm is the representation of time and space complexity of the algorithm in terms of  Big O, Big omega notations, By this we can judge two algorithms whether the given algorithm should preffered over other or not.
Score: 2.5

Student answer: this the analysis of space and time complexity using asymptotic notations like \nbig O\nbig alpha\nbig omega
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Student answer: asymptotic analysis is the analysis of algorithm based on two complexities time and space. in asymptotic analysis we use asymptotic notation to give best case, worst case and average case  out comes of the algorithm.
Score: 2.5

Student answer: Asymptotic Analysis of an algorithm refers to the analyss
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Student answer: Considering the efficiency of algo in three cases \nThe Best Case\nThe Worst Case\nThe Middle Case 
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Student answer: \nBig theta : average case\n\nBigO: best case 
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Student answer: Asymptotic analysis of algorithm refers to analysing time and space complexities using various notations to fit various  requirements like having time or space complexity less than, greater than or equal to a certain order of n.\n
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Student answer: asymptotic analysis is obtaining the time complexity using mathematical expressions  
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Student answer: asymptotic analysis means to find the various and more efficient approach to a problem using the different asymptotic notations 
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Student answer: big omega, big theta, big delta
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Student answer: Asymptotic analysis of an algorithm is the measurements of time taken by the algorithms in asymptotic denotions(namely, oh, omega and theta). In those too, it is divided into different parts, such as big oh, big omega, small oh, small omega.
Score: 2.0

Student answer: asymptomatic notations can be analysed in 3 types \n1) big o notation - it is the upper bound\n2) omega notation - it is the lower bound\n3) theta notation -
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Student answer: there are three type of asymptotic analysis of an algorithm:\n--> Big O notation.\n--> Omega notation.\n-->Theta notation.
Score: 2.0
Question: What is asymptotic analysis of an algorithm?
Reference answer: Asymptotic analysis of an algorithm, refers to defining the mathematical boundation/framing of its run-time performance. Using asymptotic analysis, we can very well conclude the best case, average case and worst case scenario of an algorithm.

Student answer: asymptotic analysis of an algorithm  basically a notations in which a  algorithm is performed
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Student answer: asymptotic analysis of an algorithm reffers to the practice of analysis on the basis of notation in which complexity can be expressed
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Student answer: In asymptotic analysis of an algorithm we categorize the algorithm in 3 categories so that we can figure out what max time our algo will take in worst case and min time in best and avg. time in avg. case. With the help of analyzation we can find Time Complexity of the Algorithm.
Score: 2.5

Student answer: asymptotic analysis of an algorithm is the analysis of the time complexity the algorithm takes, where big omega is for best case big thetha for average case and big O for worst case time complexity.  We analyse through these aasymptotic algorithm so we can analyse our code for time complexity.
Score: 2.5

Student answer: asymptotic analysis of an algorithm is to analyse the problem and divide thye problem into fewer subproblems.
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Student answer: Types of asymptotic analysis are :-\nBig O notation = upper bound graph\nOmega notation = mid bound graph\nTheta notation = lower bound graph
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Student answer: Asymptotic analysis is the practice of figuring out the space and time complexity of the algorithms in order to determine which algorithm would be the best to use. A key point here is that we take the complexity of the functions into consideration when the independent variable is tending to infinity. Hence, the name asymptotic.
Score: 2.5

Student answer: Asymptotic analysis of an algorithm is to understand the space and time complexity of any algorithm. 
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Student answer: in which we get the best average and worst case of algorithm and according to that we can apply the suitable technique.
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Student answer: asymptotic analysis refers to using substitution method or master theorem to find out the mathematical complexity of our algorithm
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Student answer: asymptotic analysis of an algo is is we measure a performance of algo in the term of different mathematical notation like big o and many more 
Score: 2.5

Student answer:  asymptotic analysis is the analysis of the code in terms of time complexity of the code.\nsome asymptotic notations - O(worst case), Theta(average case) and omega(best case)
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Student answer: min time omega\nmax time  big oh\navg time  theta\nsame as storage
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Student answer: they can never change the time.
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Student answer: the analysis which uses asymptotic notations for telling the time complexity of given program or problem 
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Student answer: asymptotic analysis are basically for the prefix , suffix problem in a given question.
Score: 0.0
Question: What are asymptotic notations?
Reference answer: Asymptotic analysis can provide three levels of mathematical binding of execution time of an algorithm – (1) Best case is represented by Ω(n) notation. (2) Worst case is represented by Ο(n) notation. (3) Average case is represented by Θ(n) notation.

Student answer: BigOh(theta), bigoh(omega), smalloh(theta)
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Student answer: its calculate the running time of the algorithm
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Student answer: There are three asymptotic notations: 1) O(): The big O notation shows the worst case complexities, 2) theta: The theta notations show the average case complexity, 3) omega: The omega notation shows the best case complexities
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Student answer: In asymptotic notations we have Big oh notation which is the upper bound, Theta notation which is average, Omega which is the lower bound.
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Student answer: The asymptotic notations are bigoh(n),average o(n) and omega(n).
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Student answer: asymptotic notations is used  to describe the running time of an algorithm .how much time algorithm takes with a given input 'n'. there are three notations. \nbig O \nbig theta\nbig omega.
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Student answer: Big oh , omega ,theta.
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Student answer: -> Big oh - worst case time - the algorithm will not take more than this time\n-> theta - average case time - the algorithm will take average this much time\n-> omega - best case - the algorithm will take minimum this much time
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Student answer: Asymptotic notation is a mathematical notation used to analyze the time complexity and runtime of an algorithm for a large input
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Student answer: To study the time complexity and space complexity of a given problem we use notations that are known as asymptotic notations.
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Student answer: Notation used to represent the time , whether it is linear , quadratic , cubic , and etc. .\nsome of the notations are :\n0(1) --> constant\no(n) --> linear
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Student answer: Asymptotic notations are which declares the meaning like ending the code, comparing the values, using brackets etc.
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Student answer: The asymptotic notations include Big O notation, theta notation and omega notation. These are used to denote the upper bound, lower bound and average time taken by any algorithm to function. eg O(nlogn), o(n^2)
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Student answer: asymptotic notations are :\nbig o \ntheta\nomega
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Student answer: We have various asymptotic symbol :-\n- Big O is for determining upper bound.\n- Omega is for determining lower bound.\n- Theta if for determining exact value.
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Student answer: 1. best case analysis --> sigma Notation\n2. average case --> theta Notation\n3.worst case --> Big Oh Notation
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Student answer: they are omega, theta, big O.
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Student answer: examples are:\n1)Big O : f(n)<=g(n)\n2)Big Omega : f(n)>=g(n)\n3)Little o : f(n)<g(n)\n4)Little omega : f(n)>g(n)
Score: 2.5