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2.3.4.7 Data Memory Taxonomy

Return to Data Taxonomy

Data is tied to the memory where it is used during the Data-In-Use state. Basically, there are six different taxons that cover Data-In-Use. Although memory categories presented in Figure 1 are shown as having definite boundaries with definite rules governing the use of the categories; there are situations where these classification and boundaries deviate from the definiton. For example, the use dynamic code written as strings and processed at runtime, intepretive code, and reflection.

Figure 1: Traditional Memory Taxonomy

Instruction Data

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A computer program is a ordered sequence of computer instructions that when executed in order accomplish a goal or task. Each computer architecture defines its own Instruction Set. When a program is executed, a Program Counter is set to the first instruction in the program. As the program executes each individual instruction, the program can modify data within the Variable area or it can modify the program counter (i.e., GO TO a specific instruction in the instruction set). As a general rule, the Instruction data can not be changed during the execution of a program. When the programs do change the contents of the excuting program, it is usually considered a fault and the program stops executing (see Segmentation Fault (SEGFAULT)).

Constant Data

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Constant Data is a value that is expected to remain constant overtime (i.e., the number of pennies in a dollar, the number of seconds in a minute, the value of Pi, the gravitation constant, speed of light, etc.). In software, constants are usually hardcoded into the software and require a recompile and link in order to change them. Therefore, although in programming constants can change, it is generally not a trival task. Sometimes constants might need to change or updated is when the precision used to represent the constant value needs to change (i.e., the value of Pi going from single precison 3.1415927 to double precision 3.14159265358979323846. Constants in programming should not change during the normal execution of the program. Sometimes the “constancy” canbe violated or pruposely circumvented by by overwriting the memory location where the value is stored or by using self-modifying code or dynamic code. Using constants in software can:

  • Alow for compile-time or editing-time checking of operations such as assigning a value to a constant. In the following examle, most modern editors and all compilers raise erros on the second line.
      const float PI = 3.1415927;
      PI = 42;
  • Increase reability (i.e., myVar*PI where PI is the value of the numerical constant 3.1415927 is more readable than myVar*3.1415927)
      const float PI = 3.1415927;
      float radius = 4;
      float areaVar = 0;
      areaVar = PI * (radius*radius); -- PI*r^2
  • Icrease performance by aiding in compiler optimation (i.e., allocating memory once to hold the constant rather than once per usage)
      const float PI = 3.1415927;
      float radius1 = 4;
      float radius2 = 6;
      float areaVar1 = 0;
      float areaVar2 = 0;
      areaVar1 = 3.1415927 * (radius1*radius1); 
      areaVar2 = 3.1415927 * (radius2*radius2);

There are two kinds of Constants used in most programming languages:

Literal Constants

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Literal Constansts are the actual numeric values (i.e., 3.1415927) or are characters (i.e., 'H'), or strings of characters (i.e., “Hello World”) used in the software. In the following example, “Helo World! %d”, 42 and 0 are literal constants.

int main()
{  cout<<"Hello World! %d", 42;
   return 0;
}

Named Constants

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Named Constants are similar to variables in most programming languages, however, by convention many programmers will use-upper case names for the Constants to help the programmer visually “see” they are working with a Named Constant rather than a variable. In the following example, ANSWER and GREETING are named constants. “%s %d” and 0 are literal constants.

int main()
{  const int ANSWER = 42;
   const string GREETING = "Hello World";
   cout<<"%s %d", greeting, answerToUniverse;
   return 0;
}

Variable Data

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Variable Data, in contrast to Constant Data, is a data item whose value can change during the program’s execution. In other words, the Variable Data value varies over time. There are two main categories based on the lifespan of the of Variable Data:

Static Data

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Static Data is data that does not change after it has been set. Static Data is usually defined during startup or initialization os a system or subsystem. Some comon examples of Static Data are setup parameters of a system; or properties or attributes of objects within a system (i.e., constructor settings). Data that is static differs form immutable data because immutable data can have newer values, but the original values are never replaced, lost or destroyed. Generally, newer immutable data has pointers to the privious values of the data.

It is a fixed data set. Experts contrast static data with dynamic data, where dynamic data may change after it is recorded, and has to be continually updated.

Dynamic Data

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Dynamic Data is usually data is created, updated and maintained by the programs. It is generally divided into two areas, the Heap and the Stack. The two areas are organized and managed differently and the boundary between the two areas is fluid (i.e., the amount of space allocated to either the Heap or the Stack can expand and contract as long as the total amount of memory in the Heap or the Stack does not exceed the amount of Dynamic Data allocated for the program.

Stack Data

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Stack Memory is generally allocated and unallocated from contiguous blocks of memory automatically during the execution of a program. When a program is executed, memory is allocated for all the parameters passed to the program and all the variables declared in the program. Upon the completion of the program, all the memory allocated for the program is released to be used by the next program. Often, the first program executed is often referred to as the Main program.

Any other programs (i.e., subprograms) called during the program are again allocated more memory for its parameters and declared variables from the Stack. Upon termination of the subprogram, the memory allocated to the subprogram is released back to the system to be reused for other subprograms. Note: the original memory allocated for the main (or calling program) program remains allocated until that program ends. This repetitive and successive allocation creates a stack of allocation, with the most recent subprogram being at the top of the stack. The stack gets deeper and shallower depending on the depth of subprogram allocations.

Figure 2 illustrates a simple example of how the stack works:

  1. A program is written into a file that contains two routines: greetings and a main
  2. During compilation of the file, the compiler determines the amount of memory required to run main routine
  3. During compilation of the file, the compiler determines the amount of memory required to run greetings routine
  4. The main program is executed from the command lime and the amount of memory required to run the main is allocated and placed on the stack
  5. When the main program executes the line that invokes the greetings routine, the memory required for it is allocated and place onto the stack
  6. When the greetings routine is finished, the memory used to execute the routine is removed from the stack and released for re-use
  7. When the main routine is finished, the memory used to execute the routine is removed from the stack and released for re-use
Figure 2: A Simple Example of Stack Memory

Heap Data

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The Heap Memory is essentially a large pool of memory (typically per process) from which a running program requests chunks of memory for use within the program. The memory is dynamically allocated during the execution of a program using allocation operations such as malloc or new operators on arrays or objects. When the program (i.e., process terminates, the chunks of memory allocated during the execution of the program are returned. Because the memory is allocated as it is needed and returned as it is required, the memory available for allocation often gets fragmented into small blocks which is very difficult to use and can result in memory exhaustion. This is why modern programming languages have implemented automatic memory management and a process called garbage collection.

  1. A program is written into a file that contains a main. Note: During compilation of the file, the compiler determines the amount of memory required to run main routine
  2. The main program is executed from the command lime and the amount of memory required to run the main is allocated and placed on the stack
  3. When the main program executes the line that invokes the malloc statement, the memory required for it is allocated from the heap
  4. When the main program executes the line that invokes the free statement, the memory required for it is returned to the *Heap for later use (see - When the main program executes the line that invokes the next malloc statement, the memory required for it is allocated from the *Heap. Note: This may or may not be the same memory allocated in the previous malloc.
  5. When the main program executes the line that invokes the next free statement, the memory required for it is returned to the Heap for later use
  6. When the main routine is finished, the memory used to execute the routine is removed from the stack and released for re-use
Figure 3: A Simple Example of Heap Memory

Attribute / Property Data

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Often the two terms: Attribute and Property are used interchageable in Computer Science because we often use them to describe the elements of an Object in an Object-Oriented Programming (OOP). However, it is useful to understand the difference between the two gramatically:

  • An Attribute is a quality or object that we attribute to someone or something. For example, intelligence is an attribute of a person. You can not go to the store and buy intelligence, it is an attribute of the individual. Another example would be a planet belonging to a solar system. Planets do not usually exist outsice of a solar system.
  • A Property is a quality that exists without any attribution. Geometric shapes are properties in their own right. They can be used to independenty descibe many things. For example, a planet or a ball can be described as a sphere1). A definition of the sphere exists without the attribution to a planet or a ball. Therefore, we say that a planet or a ball have sperical properties.

In UML, an Attribute and a Property both represent an structural association between two entities. Attributes are most oiften represented as Composition2), while Property is best represented by Aggregation 3).

In Unified Modeling Language (UML) according to Lenny Delligatti4), “UML Attributes are DataTypes (e.g., Strings, Integers, etc.) whereas Systems Modeling Language (SysML) properties are ValueTypes (e.g., can be assigned computed values).”

Mutable Data

Immutable Data

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1)
Sphere, In geometry, the set of all points in three-dimensional space lying the same distance (the radius) from a given point (the centre), or the result of rotating a circle about one of its diameters. The components and properties of a sphere are analogous to those of a circle.https://www.britannica.com/science/sphere
2)
The Composition is a part of aggregation, and it portrays the whole-part relationship. It depicts dependency between a composite (parent) and its parts (children), which means that if the composite is discarded, so will its parts get deleted. It exists between similar objects. https://www.javatpoint.com/uml-association-vs-aggregation-vs-composition
3)
Aggregation is a subset of association, is a collection of different things. It represents has a relationship. It is more specific than an association. It describes a part-whole or part-of relationship. It is a binary association, i.e., it only involves two classes. It is a kind of relationship in which the child is independent of its parent. https://www.javatpoint.com/uml-association-vs-aggregation-vs-composition
4)
Lenny Delligatti, SysML Distilled: A Brief Guide to the Systems Modeling Language, FIrst Edition, Addison-Wesley Professional , 8 November 2013, ISBN-13: 978-0321927866
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