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The compiler demands a block of memory for the operating system. The compiler utilizes this block of memory executing the compiled program. This block of memory is called storage management. One of the important tasks that a compiler must perform is to allocate the resources of the target machine to represent the data objects that are being manipulated by the source program.A compiler must decide the runtime representation of the data objects in the source program. In the source program, runtime representations of the data objects, such as integers and real variables, usually take the form of equivalent data objects ... Read More
Symbol Table is a data structure that supports an effective and efficient way of storing information about various names appearing in the source program. These names are used in the source code to identify the different program elements, like a variable, constants, procedures, and the labels of statements.The symbol table is searched each time a name is encountered in the source text. When a new name or new data about an existing name is found, the content of the symbol table modifies.Therefore, the symbol table must have an efficient mechanism for accessing the data held in the table also for ... Read More
To find the percentage of values that lie within a range in R data frame column, we can follow the below steps −First of all, create a data frame.Then, use sum function along with extreme values for range and length function to find the percentage of values that lie within that range.ExampleCreate the data frameLet’s create a data frame as shown below −Var
SolutionThe first number the production as below −Step1− Construct Augmented Grammar(0) S′ → S(1) S → A a(2) S → b A c(3) S → d c(4) S → b d a(5) A → dStep2− Find Closure & goto. Find the canonical set of LR (1) items for the Grammar.In the states, I0 to I10, no states have a similar first element or core. So, we cannot merge the states. Some states will be taken for building the LALR parsing table.LALR Parsing TableParsing of String "bdc"StackInput StringAction$ 0bdc $Shift 3$ 0 b 3dc $Shift 7$ 0 b 3 d 7c ... Read More
To find the mean of a column summarized by other column names and common values in those columns in data.table object in R, we can follow the below steps −First of all, create a data.table object.Then, melt the data.table object using melt function from reshape2 package.After that, use dcast function to find the mean of a column summarized by other column names and common values in those columns.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) ID
To find the total by year column in an R data frame, we can use aggregate function with sum function.For Example, if we have a data frame called df that contains a year colmn say Year and a numerical column say Demand then we can find the total Demand by Year with the help of command given below −aggregate(df["Demand"],by=df["Year"],sum)Example 1Following snippet creates a sample data frame −Year
Problem Statement Verifying whether the string id * id + id is accepted by a given grammar using SLR parsingConsider the SLR parsing table for the GrammarE → E + TE → TT → T ∗ FT → FF → (E)F → idCheck whether the string id * id + id is accepted or not by using the SLR parsing table constructed in the example. SolutionInitially, LR Parser in state 0.Put $ at the end of the string, i.e., id * id + id $.StackInput StringReason0id ∗ ... Read More
To standardize selected columns in data.table object in R, we can follow the below steps −First of all, create a data.table object.Then, use scale function and cbind function with subsetting to standardize selected columns.ExampleCreate the data.table objectLet’s create a data.table object as shown below −library(data.table) var1
To save a matrix as CSV file using R, we can use write.matrix function of MASS package. For Example, if we have a matrix called M and we want to save it as CSV file then we can use the below mentioned command −write.matrix(M,file="Mat.csv")ExampleFollowing snippet creates a sample matrix −M
To repeat column values in R matrix by values in another column, we can follow the below steps −First of all, create a matrix.Then, use rep function along with cbind function to repeat column values in the matrix by values in another column.ExampleCreate the matrixLet’s create a matrix as shown below −x