Record (computer science)

A record may have zero or more keys. A key maps an expression to a value, or a set of values, in the record. A primary key is a key this is unique throughout all stored records; only one if this key exists.[7] In other words, no duplicate may exist for any primary key. For example an employee file might contain employee number, name, department, and salary. The employee number will be unique in the organization and would be the primary key. Depending on the storage medium and file organization the employee number might be indexed—that is also stored in a separate file to make lookup faster. The department code is not necessarily unique; it may also be indexed, in which case it would be considered a secondary key, or alternate key.[8] If it is not indexed the entire employee file would have to be scanned to produce a listing of all employees in a specific department. Keys are usually chosen in a way that minimizes the chances of multiple values being feasibly mapped to by one key. For example, the salary field would not normally be considered usable as a key since many employees will likely have the same salary. Indexing is one factor considered when designing a file.

Journal sheet from 1880 United States Census, showing tabular data with rows of data, each a record corresponding to a single person.

The concept of a record can be traced to various types of tables and ledgers used in accounting since remote times. The modern notion of records in computer science, with fields of well-defined type and size, was already implicit in 19th century mechanical calculators, such as Babbage's Analytical Engine.[9][10]

Hollerith punched card (1895)

The original machine-readable medium used for data (as opposed to control) was punch card used for records in the 1890 United States Census: each punch card was a single record. Compare the journal entry from 1880 and the punch card from 1895. Records were well-established in the first half of the 20th century, when most data processing was done using punched cards. Typically each record of a data file would be recorded in one punched card, with specific columns assigned to specific fields. Generally, a record was the smallest unit that could be read in from external storage (e.g. card reader, tape or disk). The contents of punchcard-style records were originally called "unit records" because since punchcards had pre-determined document lengths.[11] When storage systems became more advanced with the use of hard drives and magnetic tape, variable-length records became the standard. A variable-length record is a record in which the size of the record in bytes is approximately equal to the sum of the sizes of the its fields. This was not possible to do before more advanced storage hardware was invented because all of the punchcards had to conform to pre-determined document lengths that the computer could read, since at the time the cards had to be physically fed into a machine.

Most machine language implementations and early assembly languages did not have special syntax for records, but the concept was available (and extensively used) through the use of index registers, indirect addressing, and self-modifying code. Some early computers, such as the IBM 1620, had hardware support for delimiting records and fields, and special instructions for copying such records.

The concept of records and fields was central in some early file sorting and tabulating utilities, such as IBM's Report Program Generator (RPG).

COBOL was the first widespread programming language to support record types,[12] and its record definition facilities were quite sophisticated at the time. The language allows for the definition of nested records with alphanumeric, integer, and fractional fields of arbitrary size and precision, as well as fields that automatically format any value assigned to them (e.g., insertion of currency signs, decimal points, and digit group separators). Each file is associated with a record variable where data is read into or written from. COBOL also provides a MOVE CORRESPONDING statement that assigns corresponding fields of two records according to their names.

The early languages developed for numeric computing, such as FORTRAN (up to FORTRAN IV) and Algol 60, did not have support for record types; but later versions of those languages, such as FORTRAN 77 and Algol 68 did add them. The original Lisp programming language too was lacking records (except for the built-in cons cell), but its S-expressions provided an adequate surrogate. The Pascal programming language was one of the first languages to fully integrate record types with other basic types into a logically consistent type system. The PL/I programming language provided for COBOL-style records. The C programming language initially provided the record concept as a kind of template (struct) that could be laid on top of a memory area, rather than a true record data type. The latter were provided eventually (by the typedef declaration), but the two concepts are still distinct in the language. Most languages designed after Pascal (such as Ada, Modula, and Java), also supported records.

Although records are not often used in their original context anymore (i.e. being used solely for the purpose of containing data), records influenced newer object oriented programming languages and relational database management systems. Since records provided more modularity in the way data was stored and handled, they are better suited at representing complex, real-world concepts than the primitive data types provided by default in languages. This influenced later languages such as C++, Python, JavaScript, and Objective-C which address the same modularity concerns of programmers.[13] Objects in these languages are essentially records with the addition of methods and inheritance, which allow programmers to manipulate the way data behaves instead of only the contents of a record. Many programmers regard records as obsolete now since object-oriented languages have features that far surpass what records are capable of. On the other hand, many programmers argue that the low overhead and ability to use records in assembly language make records still relevant when programming with low levels of abstraction. to Today, the most popular languages on the TIOBE index, an indicator of the popularity of programming languages, have been influenced in some way by records due to the fact that they are object oriented.[14] Query languages such as SQL and Object Query Language were also influenced by the concept of records. These languages allow the programmer to store sets of data, which are essentially records, in tables.[15] This data can then be retrieved using a primary key. The tables themselves are also records which may have a foreign key: a key that references data in another table.   

• Declaration of a new record type, including the position, type, and (possibly) name of each field;
• Declaration of variables and values as having a given record type;
• Construction of a record value from given field values and (sometimes) with given field names;
• Selection of a field of a record with an explicit name;
• Assignment of a record value to a record variable;
• Comparison of two records for equality;
• Computation of a standard hash value for the record.

The selection of a field from a record value yields a value.

Some languages may provide facilities that enumerate all fields of a record, or at least the fields that are references. This facility is needed to implement certain services such as debuggers, garbage collectors, and serialization. It requires some degree of type polymorphism.

In systems with record subtyping, operations on values of record type may also include:

• Adding a new field to a record, setting the value of the new field.
• Removing a field from a record.

In such settings, a specific record type implies that a specific set of fields are present, but values of that type may contain additional fields. A record with fields x, y, and z would thus belong to the type of records with fields x and y, as would a record with fields x, y, and r. The rationale is that passing an (x,y,z) record to a function that expects an (x,y) record as argument should work, since that function will find all the fields it requires within the record. Many ways of practically implementing records in programming languages would have trouble with allowing such variability, but the matter is a central characteristic of record types in more theoretical contexts.

The representation of records in memory varies depending on the programming languages. Usually the fields are stored in consecutive positions in memory, in the same order as they are declared in the record type. This may result in two or more fields stored into the same word of memory; indeed, this feature is often used in systems programming to access specific bits of a word. On the other hand, most compilers will add padding fields, mostly invisible to the programmer, in order to comply with alignment constraints imposed by the machine—say, that a floating point field must occupy a single word.

Some languages may implement a record as an array of addresses pointing to the fields (and, possibly, to their names and/or types). Objects in object-oriented languages are often implemented in rather complicated ways, especially in languages that allow multiple class inheritance.

A self-defining record is a type of record which contains information to identify the record type and to locate information within the record. It may contain the offsets of elements; the elements can therefore be stored in any order or may be omitted.[16] The information stored in a self-defining record can be interpreted as metadata for the record, which is similar to what one would expect to find in the UNIX metadata regarding a file, containing information such as the record's creation time and the size of the record in bytes. Alternatively, various elements of the record, each including an element identifier, can simply follow one another in any order.

• Block (data storage)
• Composite data type
• Data hierarchy
• Object composition
• Passive data structure
• Union type