Harsh-7300/dataset huggingface dataset:
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: Asymptotic notations gives us the information regarding the time and space complexities in various cases like the best , worse and the average cases. It helps us in comparing the efficiency of the program from various angles. It has O() for worst case , omega() for best cases and theta() for average cases.
Score: 2.0

Student answer: Asymptotic notation gives us the information about the space and time complexities in various cases, it could be the best, worst and average case. 
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Student answer: asymptotic notations like big O,omega and theta which represents the possible cases an algorithm can be solved. Big O represents best case scenario ,theta represents average case scenario while omega gives worst case scenario of an algorithm. It is identified by the functions used in algorithm which makes it easier to differentiate and to justifies particular scenario, for space and time complexities.
Score: 2.5

Student answer: There are three asymptotic notations which are used for time complexity. These notations are:\ni) theta ( )\nii) O( ) \niii) omega ( )
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Student answer: to check lower bound of the solution. we use asymptotic notations. 
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Student answer: Big O (O) -worst time complexity\nTheta- Average time complexity\nOmega- Best time complexity
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Student answer: The Notations that are used to denote the functions generated by the algorithms are knows as asymptotic notations. For example, Big Oh, Theta, Omega are the bounds of an algorithm, Big Oh denotes the upper bound, Omega denotes the lower bound and Theta denotes the average.
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Student answer: The notations generated to denote a function generated for the algorithms are called asymptotic notations. Omega, theta and Big oh are the bounds for an algorithm and denote lower, average and upper bound respectively.
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Student answer: Asymptotic notations mean representing the time complexity of an algorithm in the form of an equation (recurrence relation).
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Student answer: big O(n)
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Student answer: The asymptotic notation is to represent the given problem in terms of time complexity. so that if there is chance to reduce its complexity then we can do it by applying suitable complexity. \n1)Big O notation\n2)theta notation\n3)
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Student answer: asymptotic notations are mathematical terms which are used to analyze an algorithm. They are basically used to measure the time taken by an algorithm.\nsome common examples of asymptotic notations are :-\nBig-oh,\nBig- omega\ntheta ,etc. 
Score: 2.5
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: Asymptotic Notations are basically a method to represent the given Algorithm in Mathematical terms . Some specific notations are being defined to check or state whether the time complexity of an algorithm will be in which of the form of asymptotic notations.\nFoe ex; 1. Big-oh\n             2. omega \n             3. theta 
Score: 2.0

Student answer: Asymptotic notations tells about the running time of a program. It tells us how much time can a program take to give an output. Asymptotic notations are divided in big O, theta and omega notations.
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Student answer: asymptotic analysis are big O, theta and omega.
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Student answer: These are a kind of approximations of time and space complexities which tells us the program that in how much time the algorithm is taking to run the program. These are denoted by some kind of symbols such as theta, Small and Big O. 
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Student answer: Asymptotic notations are the ways to represent the time complexity of a program. Example: bigO, omega(w), theta.
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Student answer: Big O\ntheta\nomega\ndelta\netc.\n
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Student answer: Asymptotic notations are the notations used to express complexities, for example:\nBig O\nBig Theta\nBig Omega\nSmall O
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Student answer: Analysis of an Algorithm can be done using notations that give us the information about the lower and upper bounds or exact constant time or space that the algorithm might take:\n1) big O notation - It specifies the  minimum upper bounds of time and space that the algorithm might take.\n2) omega notation - It specifies the highest lower bound of time and space that an algorithm might take.\n3) theta notation - It specifies the average time and space that an algorithm might take.
Score: 2.5

Student answer: it is a method for the  notation of the time complexity of an algorithm. Big oh, theta, small o
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Student answer: big o - O : Worst Case Time Complexity \ntheta- Average Case Time Complexity\nomega- Best case Time Complexity
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Student answer: There are different types of asymptotic notations:\n(i)Big-O\n(ii)Omega\n(iii)Theta\n(iv)Small-o
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Student answer: There are various asymptotic notations like:\n1. Big oh (O) Notation: Calculates the upper bound time complexity. Shows the worst-case input scenario for a particular algorithm.\n2. Theta Notation: Calculates the lower bound time complexity. Shows the best-case input scenario for a particular algorithm.\n3. Omega Notation: Calculates the average case time complexity. Shows the median-case input scenario for a particular algorithm.
Score: 2.5

Student answer: the asymptotic analysis use certain notation in which the time complexity of an algorithm can be written.\nthose notations are called as asymptotic notation.\nthere are major 3 notations:\n1)Big O\n2)Big omega\n3)Big Theta\n
Score: 2.5
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: Asymptotic Notations are:-\nBig of O\nBig of Theta\nBig of Omega
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Student answer: Asymptotic notations are in the form of Big O(O), small O(o) and omega.
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Student answer: Asymptotic notations are the representation in which the space and time complexities are analyzed and shown. Few asymptotic notations are Big O Notation, Theta Notation etc.
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Student answer: there are the representations to provide the time and space complexity of an algorithm. eg big Oh' (O) , theta, omega.
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Student answer: Asymptotic notations are a way to express the time complexity of an algorithm in computer science. They provide a formal way to describe the rate of growth of the running time of an algorithm as the size of the input increases. The three main asymptotic notations are Big O, Omega, and Theta, which are used to describe the upper, lower, and tight bounds of the time complexity, respectively.
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Student answer: big O notation, the big theta notation and the big omega notation
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Student answer: different notations such as big O, omega and theta , that represent best , average and worst complexity
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Student answer: There are big o , theta and omega.
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Student answer: Asymptotic notations are the notations to represent different test cases - the best case, the average case and the worst case. \nThese notations are theta, big-O notation and the omega notation. The theta is represented for average case, big-O notation for worst cases and the omega for the best test case.
Score: 2.5

Student answer: Asymptotic notations include Big Oh, Theta, and Omega.\nBig Oh is for the worst case time complexity\nTheta is for the closest time complexity\nOmega is for the least time complexity
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Student answer: 1)Big O\n2)Omega
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Student answer: notations used to measure time like big o , theta , omega 
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Student answer: It is used to describe the running time of an algorithm
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Student answer: Its Mathematical notation to compare between two things which is bigger or lesser 
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Student answer: asymptotic notations are: \n1.best case ( omega notation)\n2. average case (theta notation)\n3. worst case (big O notation)
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Student answer: The equations which we made as per the code for finding the running time of a algorithm are known as asympotic notations.
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Student answer: Asymptomatic notation means the amount of time the algorithm will take to run like eg. O(n) or Theta time.
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Student answer: Asymptotic notations are theta, ohm and O(big O) FOR best, worst and average case respectively.
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Student answer: It is a mathematical notations that represent the complexity or performance of an algorithm for large inputs or when the input size changes.
Score: 2.5
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: it is used to describe the run time of a given algorithm it  gives how much time does a algorithm take to run
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Student answer: Asymptotic notations are: \n1. Omega\n2. Theta\n3. Big - O
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Student answer: It is used to show the complexity of the algorithm in best , average or worst case.\nThere are three asymptotic notations :\n1. Big O notation \n2. Theta notation \n3. Omega notation 
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Student answer: Asymptotic notations are the mathematical notations used to describe the running time of an algorithm when the input tends towards a particular value or a limiting value.
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Student answer: Mathematical notation used to describe running time of an algorithm.
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Student answer: Asymptotic notations are the notations which is widely used in order to identify the three cases of time complexity analysis of an algorithm, that are\n->Best case (thetha)\n->Average case(Omega )\n->Worst case(Big O) 
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Student answer: The asymptotic notations are o, big o, and delta. These are notations used to denote the best, average and worst case of an algorithm.
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Student answer: Asymptotic notations are \n1. BIG O (O) worst time complexity\n2. theta(N) Best time complexity \n3. average case time complexity\n
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Student answer: Asymptotic notations are mathematical notations that are used to analyze the runtime of a given algorithm for a large input. It helps us to compare the runtimes of different algorithms without actually calculating their runtimes manually. Asymptotic notations are used only for larger inputs. 
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Student answer: big O, small o, big omega, small omega
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Student answer: big o notaion 
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Student answer: There are symbols depicting the time complexity (Big O, Theta, Omega)
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Student answer: o(n),O(n),T(n),W(n)
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Student answer: Asymptotic Notations are the mathematical notations used to describe the running time of an algorithm when the input tends towards a particular value.
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Student answer: big O\ntheta \nomega \ntime complexities
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Student answer: Asymptotic notations are denoted using O ,THETA AND OMEGA.Big o and small o has f(n)<g(n),big w and small w has  f(n)>g(n) and theta has c1n<fn<c2n
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Student answer: there are the major notations -\nbig o\nbig theta\nomega\ntheta\no
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Student answer: Big Omega, Small Omega, Big O, Small O, Thetha
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Student answer: Asymptotic notations are theta , omega, big o . These are used to show the time complexity of a given code. 
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Student answer: Asymptotic notations are big O , theta and omega notations . 
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Student answer: Big O\nTheta 
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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: These are the notations that denotes the different cases that the algorithm has analyzed Big O denotes worst case , Big Omega denotes average case , theta denotes best case.
Score: 2.5

Student answer: big O, theta
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Student answer: there are certain rules in which we make coefficients of lowest power of x equal to the highest power and then find n0,c0 and f(n)
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Student answer: Following are the asymptotic notations:-\n1. O( ): Tells about the worst case complexity\n2. o ( )\n3. Theta ( ): Tells about the average case complexity\n4. Big Omega ( ): Tells about the best case complexity\n5. Small Omega ( )
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Student answer: it basically tells us about the running time of an algorithm
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Student answer: The asymptotic notations are:\n1- Big Oh()\n2- Big Omega()\n3- Big OTheta
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Student answer: Big O , Big omega , theta , small omega , small O
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Student answer: Asymptomatic notations are expressed to denote the different cases of the run time of algorithms. Such as big o for the worst case, theta for the average and omega  for the best case scenario of an algorithm.
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Student answer: like 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 
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Student answer: Notation to represent time/Space Complexity of algorithm.\ntheta(N)\nFrom which we get information about time measurement of algorithm\nwhich is essential to know about whether a algorithm is efficient or not
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Student answer: they are of three types , big o , omega and theta. 
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Student answer: Asymptotic notations are the notations which are used to describe the running time of an algorithm. 3 notations are big O,big thetha and bigf omega.
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Student answer: asymptotic notations are of three types big O, big omega ,big theta.\nasymptotic notations tell us about the upper bound, lower bound and worst cases of the algorithm.
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Student answer: Omega(n)\nTheta(n)\nOhm(n)\nThey are three notations.
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Student answer: Asymptotic notations are used to time the best case, worst case and average case time complexity of a function by using mathematical calculations and approximation comparisions.
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Student answer: asymptotic notations are notations used to represent time and space complexity of an algorithm for best, worst and average case. Ex- big O, theta and omega.
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Student answer: Big O Notation\nTheta Notation\nLittle o notation\nOmega Notation
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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: Asymptotic notations are Big O,  theta and  omega . These denote the worst case, average case and best case time complexities. They are decided according to the upper bound , and lower bounds of the Time taken in different cases.  
Score: 2.0

Student answer: big O notation\nlittle o notation\ntheeta notation \nomega notation
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Student answer: O(n)\nOmega(n)\no(n)
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Student answer: O() for worst case\ntheta() for average case
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Student answer: Mathematical symbols used for asymptotic analsysis like big O, big omega,etc., 
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Student answer: The aymptotic notation denote that given algo is best case,worst case or average case .
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Student answer: They are mathematical notations used to describe the running time of an algorithm  
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Student answer: Asymptotic Notation is used to calculate the running time of an algorithm , how much time an algorithm will take  \
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Student answer: The asymptotic notations are as follows:\n- Big O \n- Small o\n- Theta Notation
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Student answer: Asymptotic notations are mathematical notations that are used to analyze the runtime of a given algorithm for a large input. It helps us to compare the runtimes of different algorithms without actually calculating their runtimes manually.
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Student answer: asymptotic notations are notations that 
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Student answer: 1. Big O\n2. Big Omega\n3. o(n)
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Student answer: Asymptotic notations are a basis to examine the time complexity of an algorithm.
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Student answer: it is a way of finding a comparison point, by which we can compare two algorithm which are used to do the same piece of work but who does more efficiently.
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Student answer: Asymptotic notation is a mathematical notation used to define the run time of an algorithm as the input size reaches infinity. It helps to compare the runtimes of different algorithms without actually calculating their runtimes manually.
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Student answer: 1. big-o notation\n2. small-o notation\n3. theta notation
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Student answer: Notation like omega , big-O ,little -O etc are asymptotic notation
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Student answer: Big and small O.
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Student answer: .
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Student answer: omega ,gamma, theta are the asymptotic notations used for time complexity omega is for average case of a program similarly theta is for worst case of a program and gamma is for best case of a program 
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Student answer: The asymptotic notations are omega(time), theta(time), ohm(time).
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Student answer: asymptotic notation are the mathematical tools which helps to find the time and space complexity of an algorithm
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Student answer: Asymptotic notations are defined as\nBig O notation\nBig omega notations\nBig theta notations
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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: Asymptotic notations are big O, big omega and big theta. Big O means time taken by algorithm is less than it is written, Big theta means time taken is more than it is written.
Score: 2.5

Student answer: asymptotic notations are used to denote the maximum time that an algorithm can take in its execution, minimum time that an algorithm can take in its execution and it can also denote that the time complexity of an algorithm lies between maximum time taken and minimum time taken. the asymptotic notations are O(n) omega(n) and theta(n)
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Student answer: The 3  asymptotic notations are big omega(maximum time and space required),theta(average time and space required),and the last one which describes the minimum time and space required for the program.
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Student answer: asymptotic notations are used for analysis of algorithms for best average and worst case according to their complexities. big O big theta and big omega 
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Student answer: BIG O notation \n o notation \nthetha notation\nbig omega  
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Student answer: The asymptotic notations are O(n), theta(n), and omega(n). They are  for upper bound, middle bound and lower bound respectively. 
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Student answer: Used to define running time of an algorithm
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Student answer: Asymptotic notations are  the notations which denote  the maximum or we can say that the worst case time scenario and the minimum or the best case time scenario which that particular algorithm will take while executing .
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Student answer: the notations to describe the time complexity of algorithm like O(n), etc...
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Student answer: These are notations used to define complexities of algorithm , Examples of which are Big O, Big Omega, Small O, Small Omega etc. These notations are used in order to represent complexity of the algorithm we have written and at par helping the programmer to write more efficient code.
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Student answer: Big O\nBig omega \nBig theta
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Student answer: Asymptotic notations are big omega which describes the best case , then theta which describes the average case and the third one describes the worst case.
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Student answer: asymptotic notations includes big omega ,big theta, big oh. These are used to set upper and lower bound of how much time an algorithm will take.
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Student answer: big O, small o, omega are the notations.
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Student answer: big O\nsmall o\ntheta\n\n
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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: Asymptotic notations are the notations used to analyse the time and space complexity of different algorithms and hence it become very easy to compare any two algorithms.\nThere are three major asymptotic notations-\n1- Bit-O notation- In this notation we try to find out an upper tight bound on an algorithm time and space complexity.\n2-Big-Omega notation- In this notation, we try to find out an lower tight bound on an algorithm time and space complexity.\n3-Theta notation-This notation provides an average bound of an algorithm to it's time and space complexity.
Score: 2.0

Student answer: there are three main notations in asymptotic notations:\n1) big O\n2) big omega\n3) theta
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Student answer: Asymptotic notation for :\nWorst case- O(n)\nAverage case- Q(n) (theta of n)\nBest Case- Rho(n)
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Student answer: These notations tell us more about the time complexity in best, average and worst case. Example: big o, big omega, theta.
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Student answer: Asymptotic notations are used 
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Student answer: Function of n, used to find time and space complexity of an algorithm
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Student answer:  asymptotic notations  are  used to represent time complexity of asymptotic .
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Student answer: The asymptotic notations are Omega, Big Oh, and Theta. Big Oh tells best case time, Theta gives us the average case and Omega gives worst time.  They tell us how in different cases the algorithm is performing. giving us time and space complexities in form of polynomial and their degrees. 
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Student answer: Big O notation\nBig Omega notation\nBig Theta notation
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Student answer: asymptotic notation are theta(time), omega (time), ohm(time).
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Student answer: They are the mathematical notations used to describe the running time of an algorithm.
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Student answer: Theta Notation\nBigO(n) Notation\nOmega Notation
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Student answer: Asymptotic Notations are Big O ,Theta, omega
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Student answer: Asymptotic notations are notations used for mathematical describe the run time of algorithms.
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Student answer: The asymptotic notations may be gamma , omega , theta 
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Student answer: asymptotic notations are used to tell the complexity of an algorithm or program
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Student answer: Big O, Big Omega and Big theta are the asymptotic notations
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Student answer: there are three asymptotic noitaions in algorithm analysis namely Big O(O) that finds out worst case complexities, Theta notation that finds out average case complexities and omega notations which find out best case complexities.
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Student answer: Theta, Omega, Gamma
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Student answer: There are 3 asymptotic notations .\n1)Big O notation\n2)Theta Notation \n3)omega notation
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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: Asymptotic notation is a the way to describe the run time of an algorithm. big O notation, theta notation, omega notation are the basic examples.
Score: 1.5

Student answer: these are symbols used to describe the running time and complexity of any algorithm.\nthere are three notations:\n1. big O\n2. big theta\n3. big omega
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Student answer: Asymptotic notations are used in cases where algorithm behaves differently in different cases it includes theta notation.
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Student answer: there are mainly three types of notations omega, theta and bigO.
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Student answer: Asymptotic notations are mathematical notations that are used to analyze the runtime of a given algorithm for a large input. It helps us to compare the runtimes of different algorithms without actually calculating their runtimes manually. \nThere are mainly three asymptotic notations:\nBig-O Notation (O)\nOmega Notation\nTheta Notation \n
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Student answer: big o, omega ,theta
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Student answer: asymptotic notations\nare the notations to represent of time of complexity of any code \nexample:-\nBig O notation \nTheta  notation\nomega Notation
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Student answer: big O(n), omega of(n),theta(n)
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Student answer:  increases the time complexity of the same. Space complexity increases with say each 1d array taking O(n) time, 2d array taking O(n^2), etc.
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Student answer: Asymptotic Notation is used to describe the running time of an algorithm and  how much time an algorithm takes with a given input, n.
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Student answer: O( )\nOmega( )\n
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Student answer: Asymptotic Notations are the symbols/notations to denote the time and space complexity of an algorithm.\nEg: Big-O (O) , Big-theta , Omega, etc.
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Student answer: Asymptotic notations are the special characters or symbols used to represent time /space taken by the specific algorithm.
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Student answer: Asymptotic notations are symbols or notations used to represent complexity of an algorithm.\nThese are omega,theta and big O wherein they represent the best case,average case and worst case complexities
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Student answer: These are characters and symbols that are used to define the time complexity of the algorithm.\neg: BIG O, Omega etc.
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Student answer: Asymptomatic Notations like Big Oh (represented by O), Omega and Theta are notations used to define various cases that the algorithm is run. Big Oh can be seen as the analogous to Worst Case, Omega can be seen as the analogous to Best Case and Theta is used for exact calculations or maybe in some cases - Average Case.\nOmega is the least used among the three. Apart from these, we also have small Oh etc. (but they are not taught in the syllabus much for the sake of avoiding confusion or maybe some uniformity/brevity)
Score: 2.0
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: asymptotic notations are notations which define the complexities of algorithm like big O notation , theta notation ,omega notation, where bigO gives upperbound ,omega gives best case.
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Student answer: asymptotic notations are symbols used to denote different time complexities like big o, theta and omega
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Student answer: asymptomatic notations are symbols used to denote different time complexities like big O, theta and omega.
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Student answer: The asymptotic notations is a method in which we find a function which is is greater than the time function of our algorithm and we say that function will take maximum time less than that.
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Student answer: There are various notations like BIG O ,BIG THETA,BIG OMEGA describing the worst case, average case and best case time complexity respectively.
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Student answer: big O notation\nsigma notation\n(small) o notation\ntheta notation
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Student answer: The asymptotic notation are-\nbig O. omega, theta
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Student answer: asymtotic notations are big O ,big omega and big theta. Thats describe the upper bound ,lower bound and exactb time which nthe algorith will take .
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Student answer: they describe the manner of time that is required to run a particular function. big O, big omega, big theta are asymptotic notations. 
Score: 2.5

Student answer: There are three asymptotic notations - \nO -> This one is used to show worst case scenario.\nTheta -> This is used to show the average case.\nOmega -> This is used to show best case.
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Student answer: These are notations used to represent the time and space complexities of an algorithm, these are:\n1. big Omega\n2. small Omega\n3. big O\n4. small O\n5. big theta\n6. small theta
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Student answer: Big O :-For checking the upper bound\nBig Omega :- For checking the lower bound\nBig Theta :- Fore the average case scenario
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Student answer: Asymptotic Notations of an Algoithm basically defines the algorithm which tend towards infinity 
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Student answer: BigO : Average case\nBigTheta : Best case\nBigOmega : Average case
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Student answer: Asymptotic notations are a way of representing the time complexity of a particular algorithm by representing the time complexity in terms of big o and big omega where big o notation is considered to be the best as it gives the average of the time complexity of the algorithm.  Generally we preffer to judge an algorithm in terms of its worst time complexity as by judging to algorithms by their best case will not give us the better result.
Score: 2.5

Student answer: these are the tools which are used to analyze a particular algorithm\nBig O\nbig omega\nbig alpha
Score: 2.5
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: these are the symbols used to define the complexity of the algorithm in the best case , worst case and the average case, then there are loose bound and tight bound notationns\nthese are donated by symbols O, sigma and theta
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Student answer: These notations take use of special symbols how efficient a program is by considering 3 things best case(Omega), middle case(Rho) and the worst case( Big(O)) 
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Student answer: Notations made to perform asymptotic analysis are asymptotic notations . They are:\n1. Big Oh: it is the tight upper bound.\n2.Big omega: tight lower bound.\n3. Theta: average case\n4.Little oh: loose upper bound.\n5. Little omega: loose lower bound.
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Student answer: asymptotic notation  is when  time complexity of an algorithm is  expressed using theta and omega notation
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Student answer: this is used to define the running time of algorithm
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Student answer: various types of asymptotic notations are \n1) big O(n)-best case \n2) theta(n)-\n3) sigma (n)-worst case
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Student answer: Asymptotic notation are used to denote the time complexity of the program / algorithm:-\n1:- Big O \n2;- Big Omega\n3:- Big theta
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Student answer: asymptotic notation   are the notation that are complex in nature
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Student answer: Asymptotic Notations are the calculations of time complexity of an algorithms.\nSome of them are:-\nBig Oh: Denotes the maximum time taken by the algorithm!\nBig Omega: Denotes the minimum time taken by the algorithm!\nBig Theta: Is the average time between the two!\n
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Student answer: asymptomatic notations are notations through which we can give time complexity or space complexity of algorithm
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Student answer: these are Big 0 , omega ie , low level and theta notation
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Student answer: i) Big O Notation : Upper Bound of algorithm  c1g(n) > f(n)\nii) Omega Notation:  Lower Bound of algorithm  c2g(n) <= f(n)\niii) Theta Notation:  main function  c1g(n)> f(n) >= c2g(n)
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Student answer: Big O, Big Omega, Big Thetha
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Student answer: Asymptotic notations are mathematical notations to represent the complexity of the algorithm. The three most popular asymptotic notations are Big O, Big Omega and Big Theta notation. Other two notations are small omega and small o.
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Student answer: asymptotic notations are those which is used to represent the time and space complexity as a function of an algorithm.
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Student answer: big theta\nomega\n
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Student answer: Big oh of n\nTheta of n\nOmega of n\netc
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Student answer: Asymptotic notation is the mathematical term to measure the performance of the algorithm like optimization's in the term of time complexity and maintaining the system power and the space consumption of the server 
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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: some asymptotic notations - O(worst case), Theta(average case) and omega(best case)
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Student answer: big oh\nomega \ntheata
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Student answer: big omega & big theta.
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Student answer: the notation such as big o ,omega and theta are asymtotic notations and used for telling the time complexity for the algorithms 
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Student answer: asymptotic notation are the notation which is  
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Question: What is linear data structure?
Reference answer: A linear data-structure has sequentially arranged data items. The next time can be located in the next memory address. It is stored and accessed in a sequential manner. Array and list are example of linear data structure.

Student answer: linear data structure are those which store data in a linear form and not in the form of levels examples include array, stack,queue,linked list
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Student answer: linear data structure ,data structure where elements are arranged linearly or sequencially like array ,queue
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Student answer: Linear Data Structure are the data structures that store data in the memory contiguously, i.e, data is stored one after another
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Student answer: Linear data structure is a data structure that is represented in memory contiguously. For example, array is a linear data structure. Each element is represented in memory one after other. If one element is at 4000 then next element of array will be at 4001(in case of char array).\n\nNon linear data structure would be a linked list where different nodes are present at different location in memory and each one is linked using pointers to their memory addresses.
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Student answer: Linear data structures are data structures used to store data in a 1-dimensional array. \nTraversing the total data structure will only take take O(n) time complexity.\nExamples : array,string
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Student answer:  linear data structure is one where data items are arranged in a linear fashion.  each member is attached to its neighboring element. the structure allows single level data storage because the data elements are stored in linear fashion. 
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Student answer: Linear data structure is a 1 dimensional data structure like 1-D array  link list 
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Student answer:  Data structure where data elements are arranged linearly where each and every element is attached to its previous and next adjacent is called a linear data structure .
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Student answer: linear data structure is basically the data structure in which the static memory is used to allocate space in the memory.\nex- arrays. linked list
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Student answer: Data structures that use linear time complexity or we can say 0(n) this time complexity's to evaluate any algorithm . 
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Student answer: Linear data structure is the place which stores the data in a linear or single form.
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Student answer: Linear data structure include arrays 
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Student answer: a data structure which stores value in a single order are called linear data structures .\nex: array.
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Student answer: Storing data/values in consecutive manner for example Array, Linked List.
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Student answer: Data structures that store the data in a linear format are called linear data structures\n\nExample: array, Linked List
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Student answer: There are many data structures which stores the data in different manners or ways.\nLinear data structures, stores the data linearly in themselves. 
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Student answer: linear data structures are one dimention in space just like 1D array .
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Question: What is linear data structure?
Reference answer: A linear data-structure has sequentially arranged data items. The next time can be located in the next memory address. It is stored and accessed in a sequential manner. Array and list are example of linear data structure.

Student answer: Linear data structure is the data structure which uses 1 dimension such as list, 1-D array, stack, queue,
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Student answer: A linear data structure is a data structure where all the individual elements are arranged in a linear order so traversal and many other operations become very simple. \nIn linear data structures like an array or linked list the elements are connected in a single order without any branches . Every other element is only connected to two other \nelements unlike graphs and trees.
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Student answer: a linear data structure is one where the elements are arranged in a linear order. Examples of linear data structure- linked list
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Student answer: Data Structures are basic unit to develop an algorithm.Data Structures which can be solved in linear time complexities are termed as Linear data structures. If the algorithm carries time and space complexity of O(n) it can be classifies under linear data structures. 
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Student answer: Linear data structures are those data structures which occupy space in memory in form of continuous blocks. Some examples of linear data structures can be array, stacks, queues, etc. 
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Student answer: liner data structure take  O(n) space  , such as array , linked list , stack and queue .where our most of the operations  take  linear time to give us solution.
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Student answer: Arrays , Linked list, stacks , queues which have elements in one line are linear data structures. searching in them is done in O(n) time. 
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Student answer: A data structure that that has no child nodes(levels or heights) and can be stored in the form of a single 1-d array are called as linear data structures. For ex, linked lists, stacks, queues, arrays etc.
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Student answer: A structure which has no child noes ( Height of the tree is 1), this can be stored in a 1-D array . Examples are linked lists and arrays
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Student answer: linear data structure are those data structure which store data in only one direction that is either row wise or column wise. like array ,vector, linked list etc. here we can see the array, linked list store data one by each node of the linked list contain the address of the other and we do nt find two path (either left or right) while traversing from one node.
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Student answer: A data structure that stores data linearly (adjacent to each other) in continuous memory location is known as linear data structure.
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Student answer: linear data structure are structures in which the tasks are performed one by one linearly
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Student answer: linear data structure  involves simple data structure like sorting ,searching .
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Question: What is linear data structure?
Reference answer: A linear data-structure has sequentially arranged data items. The next time can be located in the next memory address. It is stored and accessed in a sequential manner. Array and list are example of linear data structure.

Student answer: linear data structure is a data structure which is in linear form in memory and can be traversed linearly in one - direction (parallel and anti-parallel).\nevery memory block is linked to only one memory block.\ncommon examples are array, linked list etc. 
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Student answer: In data structure tasks are performed linearly one by one.
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Student answer: A linear data structure is a data structure which takes time complexity of O(n)\nFor ex: 1. 1-D Array\n            2. pointers\n            3. linked list
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Student answer: Linear data structure is a data structure in which the elements are arranged linearly. All the elements can be traversed in one go.
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Student answer: elements are in liner order in linear data structure like array.
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Student answer: The data structures which can be traversed only at a 1 dimensional plane or they are 1 D in nature are know as Linear data structures .\nEg: 1-D array, Linear Linked List
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Student answer: Liner Data Structure are the data structures which has only one link to the next element.\n1. array.\n2. linked list
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Student answer: a linear data structure has only a single link to the next element like array, linked list,etc.
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Student answer: A data structure in which the data is stored in a linear format such as an array or a linked list.
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Student answer: Those data structure that has no ambiguity while accessing the next or previous element as they are arranged in a linear format , one after another. are called linear data structure. They have only one element succeeding or preceding them.
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Student answer: linear data structure includes arrays, queues, string, linked list. In linear data structure you perform operations like merge sort, bubble sort, quick sort, etc
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Student answer: Linear data structure is one that stores data linearly. \nE.g.: Array, Linked List.
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Student answer: A data structure which store values linearly one by one as in an array,is known as linear data structure.
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Student answer: Linear data structures are those that stores the data in linear form where a chain like memory is formed in and data are linked to each other in successive format. Example queue, linked list, etc.
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Student answer: A linear data structure is such that that can be implemented using one\nEg: Array, Stack, Queue
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Student answer: A linear data structure is a type of data structure that can be implemented in 1D.\nEx: Array, stack, queue, etc.,
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Student answer: a linear data structure is a data structure which stores data in 1-D such as arrays, stack, queue, etc.
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Question: What is linear data structure?
Reference answer: A linear data-structure has sequentially arranged data items. The next time can be located in the next memory address. It is stored and accessed in a sequential manner. Array and list are example of linear data structure.

Student answer: Linear data structure are those data structures which works on a single level. They do not form multiple levels. They store the data in 1-D such as queue, stack, etc.
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Student answer: Linear data structure is defined as a type of data structure that stores data or information one after the other linearly. Ex :Arrays
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Student answer: Data structure which stores data linearly is called linear data structure.
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Student answer: Data structure where data elements are arranged sequentially or linearly where each and every element is attached to its previous and next adjacent is called a linear data structure.\n\n
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Student answer: it is a data structure with linear data.
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Student answer: Linear data structures are basic data structures which do not have children or branches. The elements are inserted in a sequence. Ex-> Array, Linked list, etc.
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Student answer: Linear data structures are the data structures in which the data is stored in a linear 1-D format. In these data can be stored in only a unidirectional way. Eg. - array, vector. 
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Student answer: the data structure with only 1 hashing involved are known as linear data structure
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Student answer: Linear data structure are those which occupies linear space in the memory. For example - Arrays, Linked List
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Student answer: Linear data structures are data structure that go in only one direction. You don't have different paths from a particular point. Arrays, linked lists, vectors are linear data structures. Trees, graphs are non linear data structure
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Student answer: Linear data structure refers to the approach to any solution within linear time complexity. Example: Linear search
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Student answer: data is stored linearly
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Student answer: A linear data structure is where data is stored linearly with the neighbor element connected to each other
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Student answer: data structure which have fixed size and we can update it that called linear data structure
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Student answer: linear data structures are those where data is stored in a linear format. example linked list, stacks and queues
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Student answer: A data structure that could be defined in which items are inserted or arranged in a linear order. Example- Array, linked list.
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Student answer: Data structures that take the input value linearly and eject the values in the same way are linear data structures. Example of such data structures are as FIFO (first in first out), LIFO (last in first out)
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Student answer: A linear data structure is a type of data structure which perform its operations linearly like insertion, deletion, updating and searching/
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