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Fourth-generation programming language
Fourth-generation programming language
Fourth-generation programming language
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A fourth-generation programming language (4GL) is a high-level computer programming language that belongs to a class of languages envisioned as an advancement upon third-generation programming languages (3GL). Each of the programming language generations aims to provide a higher level of abstraction of the internal computer hardware details, making the language more programmer-friendly, powerful, and versatile. While the definition of 4GL has changed over time, it can be typified by operating more with large collections of information at once rather than focusing on just bits and bytes. Languages claimed to be 4GL may include support for database management, report generation, mathematical optimization, graphical user interface (GUI) development, or web development. Some researchers state that 4GLs are a subset of domain-specific languages.[1][2]

The concept of 4GL was developed from the 1970s through the 1990s, overlapping most of the development of 3GL, with 4GLs identified as "non-procedural" or "program-generating" languages, contrasted with 3GLs being algorithmic or procedural languages. While 3GLs like C, C++, C#, Java, and JavaScript remain popular for a wide variety of uses, 4GLs as originally defined found uses focused on databases, reports, and websites.[3] Some advanced 3GLs like Python, Ruby, and Perl combine some 4GL abilities within a general-purpose 3GL environment,[4] and libraries with 4GL-like features have been developed as add-ons for most popular 3GLs, producing languages that are a mix of 3GL and 4GL, blurring the distinction.[5]

In the 1980s and 1990s, there were efforts to develop fifth-generation programming languages (5GL).

History

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Though used earlier in papers and discussions, the term 4GL was first used formally by James Martin in his 1981 book Application Development Without Programmers[6] to refer to non-procedural, high-level specification languages. In some primitive way, early 4GLs were included in the Informatics MARK-IV (1967) product and Sperry's MAPPER (1969 internal use, 1979 release).

The motivations for the '4GL' inception and continued interest are several. The term can apply to a large set of software products. It can also apply to an approach that looks for greater semantic properties and implementation power. Just as the 3GL offered greater power to the programmer, so too did the 4GL open up the development environment to a wider population.

The early input scheme for the 4GL supported entry of data within the 72-character limit of the punched card (8 bytes used for sequencing) where a card's tag would identify the type or function. With judicious use of a few cards, the 4GL deck could offer a wide variety of processing and reporting capability whereas the equivalent functionality coded in a 3GL could subsume, perhaps, a whole box or more of cards.[7]

The 72-character format continued for a while as hardware progressed to larger memory and terminal interfaces. Even with its limitations, this approach supported highly sophisticated applications.

As interfaces improved and allowed longer statement lengths and grammar-driven input handling, greater power ensued. An example of this is illustrated by Nicholas Rawlings in his comments for the Computer History Museum about NCSS.[8] He reports that James Martin asked Rawlings for a NOMAD solution to a standard problem Martin called the Engineer's Problem: "give 6% raises to engineers whose job ratings had an average of 7 or better." Martin provided a "dozen pages of COBOL, and then just a page or two of Mark IV, from Informatics." Rawlings offered a single statement, performing a set-at-a-time operation.

The development of the 4GL was influenced by several factors, with the hardware and operating system constraints having a large weight. When the 4GL was first introduced, a disparate mix of hardware and operating systems mandated custom application development support that was specific to the system in order to ensure sales. One example is the MAPPER system developed by Sperry. Though it has roots back to the beginning, the system has proven successful in many applications and has been ported to modern platforms. The latest variant is embedded in the BIS[9] offering of Unisys. MARK-IV is now known as VISION:BUILDER and is offered by Computer Associates.

The Santa Fe railroad used MAPPER to develop a system in a project that was an early example of 4GL, rapid prototyping, and programming by users.[10] The idea was that it was easier to teach railroad experts to use MAPPER than to teach programmers the "intricacies of railroad operations".[11]

One of the early (and portable) languages that had 4GL properties was RAMIS developed by Gerald C. Cohen at Mathematica, a mathematical software company. Cohen left Mathematica and founded Information Builders to create a similar reporting-oriented 4GL, called FOCUS.

Later 4GL types are tied to a database system and are far different from the earlier types in their use of techniques and resources that have resulted from the general improvement of computing with time.

An interesting twist to the 4GL scene is realization that graphical interfaces and the related reasoning done by the user form a 'language' that is poorly understood.

Types

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A number of different types of 4GLs exist:

  • Table-driven (codeless) programming, usually running with a runtime framework and libraries. Instead of using code, the developer defines their logic by selecting an operation in a pre-defined list of memory or data table manipulation commands. In other words, instead of coding, the developer uses table-driven algorithm programming (see also control tables that can be used for this purpose). These types of tools can be used for business application development usually consisting in a package allowing for both business data manipulation and reporting, therefore they come with GUI screens and report editors. They usually offer integration with one or more lower level dynamic-link library (DLL), generated from a typical 3GL for when the need arises for more hardware/OS specific operations.
  • Report generator programming languages take a description of the data format and the report to generate and from that they either generate the required report directly or they generate a program to generate the report (see also RPG).
  • Similarly, screen generators (also called forms generators) manage online interactions with the application system users or generate programs to do so.
  • More ambitious 4GLs (sometimes termed fourth generation environments) attempt to automatically generate whole systems from the outputs of computer-aided software engineering (CASE) tools, specifications of screens and reports, and possibly also the specification of some additional processing logic.
  • Data management 4GLs such as SAS, SPSS, and Stata provide sophisticated coding commands for data manipulation, file reshaping, case selection, and data documentation in the preparation of data for statistical analysis and reporting.
  • So-called "XTalk" languages, developed initially with Apple's Hypercard in 1987. Hypercard was the progenitor of more modern and powerful programs such as SuperCard, Toolbook and LiveCode.

Some 4GLs have integrated tools that allow for the easy specification of all the required information:

Low code environments

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In the twenty-first century, 4GL systems have emerged as "low code" environments or platforms for the problem of rapid application development in short periods of time. Vendors often provide sample systems such as CRM, contract management, bug tracking from which development can occur with little programming.[12]

Examples

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General use / versatile

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Database query languages

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Report generators

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Extract data from files or database to create reports in a wide range of formats is done by the report generator tools.

Data manipulation, analysis, and reporting languages

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Software creators

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Mathematical optimization

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Database-driven GUI application development

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Low-code / No-code development platforms

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Source:[13][14]

Screen painters and generators

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Web development languages

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Music Programming language

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See also

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References

[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Fourth-generation programming language

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A fourth-generation programming language (4GL) is generally considered a class of high-level, often non-procedural languages designed to bridge the gap between human-readable instructions and machine execution, enabling users—particularly non-programmers—to specify desired outcomes (such as data queries or report generation) without detailing the underlying procedures, thereby enhancing development efficiency and . These languages emerged as an evolutionary step beyond third-generation languages (3GLs) like and , focusing on domain-specific applications such as database management and , where they can achieve productivity gains of 3:1 to 10:1 compared to traditional coding. The history of 4GLs traces back to the late and early , building on advancements in and structured query systems, with key standardization efforts like SQL developed by in the and later adopted by ANSI in 1986 and ISO. By the mid-, organizations like the National Institute of Standards and Technology (NIST) were actively researching and documenting 4GL capabilities through workshops and publications, recognizing their potential to democratize for end-users in commercial environments. This period marked a shift toward tools that integrated user interfaces, , and system functions, reducing the need for extensive procedural code and influencing the rise of . Key characteristics of 4GLs include their non-procedural nature, which allows English-like commands, icons, and graphical interfaces to perform complex tasks in a single instruction—such as querying records or generating reports—often replacing dozens of lines in lower-level languages. They are typically domain-specific, excelling in areas like database querying, screen formatting, and file handling, while supporting integration with 3GL code for finer control; however, they may consume more and offer limited low-level hardware access. These features make 4GLs particularly valuable for prototyping and business applications, though successful implementation often requires training, vendor support, and structured methodologies to address integration challenges. Notable examples of 4GLs include SQL for database queries, FOCUS for report generation, for business applications, and RAMIS for data analysis, with modern variants like Informix 4GL and extending their use into specialized fields such as mathematical computing and . The adoption of 4GLs has significantly impacted by shifting focus from syntax-heavy coding to conceptual problem-solving, reducing demands in organizations and enabling broader participation in development processes.

Fundamentals

Definition and Scope

A fourth-generation programming language (4GL) is a high-level computer programming language or environment designed with a specific purpose in mind, typically focusing on domains such as database management and report generation, where users specify desired outcomes rather than detailed implementation steps. These languages are characterized by their non-procedural nature, employing a limited set of powerful, declarative commands that abstract away low-level details, thereby reducing the complexity and volume of code required compared to procedural approaches. This design often incorporates syntax resembling natural language to enhance readability and ease of use, allowing for more intuitive expression of business logic. The scope of 4GLs is primarily limited to application-oriented programming, targeting practical tasks in business environments like data processing and analysis, in contrast to the broader, general-purpose capabilities of third-generation languages (3GLs) that emphasize algorithmic control flow. While 4GLs can integrate procedural elements when needed, their core strength lies in enabling rapid development of domain-specific solutions without requiring extensive programming expertise, thus broadening accessibility beyond professional developers. This focus on productivity distinguishes 4GLs as tools for streamlining repetitive, data-centric operations in organizational settings. The term "fourth-generation" emerged in the 1970s to denote this evolution following (first generation), assembly languages (second generation), and procedural high-level languages like and (third generation), marking a shift toward user-centric, problem-solving paradigms. A key objective of 4GLs is to empower end-users, such as business analysts, to create and modify applications independently, minimizing reliance on specialized IT personnel and accelerating the delivery of functional software. This generational progression reflects broader trends in computing toward higher levels, though definitions of 4GLs have varied in the literature due to overlapping features with .

Comparison with Other Generations

The progression of programming language generations reflects increasing levels of from hardware, aiming to enhance developer and accessibility. First-generation languages (1GLs) consist of in binary form (0s and 1s), directly executable by the computer's processor without translation, but they demand precise knowledge of hardware architecture and result in verbose, error-prone code. Second-generation languages (2GLs), or assembly languages, introduce mnemonic symbols and symbolic addresses to represent instructions, offering a slight improvement in readability while still being low-level and machine-specific; they require an assembler to translate into 1GL. Third-generation languages (3GLs), such as , , and , mark a shift to high-level, procedural paradigms with English-like syntax and structured , allowing one statement to generate multiple instructions via compilers or interpreters, thus promoting portability across hardware. Fourth-generation languages (4GLs) build on this by adopting declarative and non-procedural approaches, where developers specify desired outcomes ("what" to achieve) rather than step-by-step procedures ("how" to implement them), often through domain-oriented commands that automate underlying logic. This enables significantly higher , with productivity gains estimated at 3 to 10 times over 3GLs for equivalent tasks, primarily by reducing code volume— for instance, generating reports or querying data that might require hundreds of 3GL lines can be accomplished in tens of 4GL statements. Unlike the general-purpose nature of 3GLs, which support broad algorithmic control, 4GLs are typically domain-specific, tailored for areas like database management or report generation, facilitating and but potentially sacrificing fine-grained control over system details. 4GLs emerged in the as a direct response to 3GL limitations in handling data-intensive applications during the minicomputer era, demanding faster development for database and reporting tasks that 3GLs rendered inefficient due to their procedural overhead.

Historical Development

Origins in the

The emergence of fourth-generation programming languages (4GLs) in the was closely linked to the maturation of database management systems (DBMS), which provided the foundational infrastructure for higher-level data manipulation. A key advancement was Edgar F. Codd's 1970 paper introducing the , followed by IBM's System R project (1974–1979), which prototyped relational database technology and developed the Structured Query Language (SQL) for declarative data access. The CODASYL Data Base Task Group (DBTG) released its influential 1971 report, standardizing concepts for network-style DBMS and defining data description and manipulation languages that emphasized navigational access and set-oriented operations, paving the way for more abstracted programming interfaces. Similarly, IBM's Information Management System (IMS), initially developed in the late 1960s for hierarchical data storage, evolved in the to support advanced query and reporting tools, enabling developers to focus on business logic rather than low-level record handling. These DBMS advancements addressed the growing demands of business data processing, where third-generation languages like COBOL proved cumbersome for rapid application development. Economic pressures and technological shifts further accelerated 4GL development during the decade. Businesses sought cost efficiencies through improved and resource optimization, which heightened the need for tools that could streamline operations without extensive programming expertise. Concurrently, the proliferation of minicomputers—such as Digital Equipment Corporation's PDP-11 series—democratized by making it accessible to mid-sized enterprises beyond large mainframes, fostering demand for user-friendly languages tailored to specific domains like reporting and querying. This era's focus on productivity led to non-procedural paradigms, where programmers specified what data was needed rather than how to retrieve it, contrasting with the step-by-step instructions of prior generations. Early 4GLs materialized as commercial products for mainframes and minicomputers, emphasizing domain-specific features for business applications. Mathematica's RAMIS, developed starting in and released commercially in the early , was among the first, offering integrated database management, report generation, and ad hoc querying to empower non-technical users in . National CSS's NOMAD, introduced in 1975, followed as a relational-oriented 4GL, providing English-like commands for database interactions on systems. A seminal innovation was researcher Moshé M. Zloof's Query-By-Example (QBE) in 1975, a visual, skeleton-table interface for relational queries that allowed users to fill in example data patterns, significantly reducing the procedural complexity of database access. Academic and efforts contributed conceptual groundwork for these domain-specific designs, though commercial 4GLs prioritized practical business utility.

Evolution Through the 1980s and 1990s

During the , fourth-generation programming languages (4GLs) saw significant milestones through their integration with emerging management systems (RDBMS). The of SQL by the in 1986 provided a foundational that enhanced 4GL capabilities for data manipulation across various platforms. Oracle advanced this integration with the introduction of in 1979, a 4GL tool designed for rapid development of database-driven applications, which generated over 35% of the company's product revenue by the decade's end. Concurrently, the rise of personal computing fueled the popularity of PC-based 4GLs, such as , which became a dominant tool for database management and application building on microcomputers, and FOCUS, a reporting-oriented 4GL that expanded from mainframe environments to PC adaptations. The transition from mainframe-centric computing to client-server architectures in the late 1980s and early broadened the applicability of 4GLs, enabling distributed and multi-tier application development. This shift allowed 4GLs to support networked environments, where tools like those from and facilitated easier connectivity between client applications and remote servers. In the , 4GLs evolved with greater emphasis on (GUI) integration, exemplified by Microsoft's , a hybrid language combining procedural elements with declarative, (RAD) features for Windows-based GUIs. While pure 4GLs began to wane in favor of more versatile third-generation languages (3GLs) that offered better performance and flexibility for complex, object-oriented systems, their influence persisted in shaping RAD tools and low-code methodologies. By the late , 4GLs maintained a significant presence in enterprise development, particularly for database and reporting tasks, with widespread adoption in sectors reliant on legacy systems. A pivotal event boosting 4GL usage was the Year 2000 (Y2K) preparations, which highlighted vulnerabilities in legacy applications written in 4GLs and similar languages; tools like CA-Impact/2000 were developed to scan and remediate code in 4GL environments, ensuring compliance across COBOL-integrated systems. This effort underscored the entrenched role of 4GLs in enterprise infrastructure, where they comprised a notable share of development efforts amid the push for millennium readiness.

Core Characteristics

Non-Procedural and Domain-Specific Design

Fourth-generation programming languages (4GLs) are characterized by their non-procedural , which allows developers to specify the desired outcomes of a program without detailing the step-by-step algorithms required to achieve them. In this approach, the language's or interpreter assumes responsibility for translating high-level declarations into efficient , often leveraging built-in optimizers to handle implementation details such as data access paths or . This contrasts with third-generation languages (3GLs), where programmers must explicitly manage procedural logic, such as loops and conditionals, to manipulate data. A core aspect of 4GL design is its domain-specific orientation, tailoring syntax and semantics to particular application areas like database management or report generation, rather than providing general-purpose constructs. For instance, in domains, 4GLs enable concise specifications focused on query results, such as selecting records based on criteria, without requiring manual navigation through data structures. This specificity reduces the on users by embedding directly into the language, minimizing errors associated with low-level operations. The declarative style of 4GLs often incorporates English-like commands to enhance and , such as "PRINT CUSTOMER-NAME WHERE ZIP-CODE > 02134," which abstracts away the underlying file handling and algorithmic sequencing. Built-in optimizers further support this by automatically generating efficient execution plans, for example, in query where the selects optimal join orders or indexing strategies. These layers build progressively from foundational tools like SQL's SELECT statements to more comprehensive 4GL specifications for full applications, shielding users from hardware-specific details. However, this design introduces trade-offs, including potential due to proprietary syntax and limited portability across systems, as well as performance overhead in scenarios requiring complex computations beyond the targeted domain. While 4GLs excel in for domain-oriented tasks, their reliance on specialized interpreters can limit flexibility in highly algorithmic or real-time environments.

Productivity and Accessibility Features

Fourth-generation programming languages (4GLs) significantly enhance developer productivity by minimizing the volume of code required and accelerating the development process compared to third-generation languages (3GLs). Case studies demonstrate that 4GL tools like III enable the creation of applications with substantially smaller sizes than equivalent programs in , while also reducing overall development time. For instance, in one analysis, III outperformed in speed of implementation for data-oriented tasks, allowing prototypes to be built in a fraction of the time—often days rather than weeks—that would be needed with procedural 3GL approaches. These gains stem from 4GLs' non-procedural nature, which focuses on what the program should achieve rather than how, thereby streamlining and phases. indicates that 4GLs improve efficiency particularly for less experienced programmers, who achieve higher output rates when using 4GLs over 3GLs due to simpler syntax and built-in abstractions for common operations like querying and reporting. Overall, empirical studies confirm that 4GL adoption can yield productivity improvements of 3 to 5 times in targeted application domains, such as database management, by reducing the effort needed for routine coding tasks. Accessibility is a core strength of 4GLs, as they incorporate intuitive interfaces that empower non-expert users, including business analysts and domain specialists, to build functional applications without extensive programming . Early 4GL tools featured form-based editors and menu-driven environments, such as screen painting in , which allowed users to visually design interfaces and logic flows, drastically lowering the entry barrier compared to the verbose coding required in 3GLs. This design facilitated the emergence of end-user or "citizen" development within enterprises, where non-IT staff could and deploy custom solutions for departmental needs, thereby reducing dependency on developers and minimizing overhead. According to industry analyses, such features contributed to quicker by enabling rapid iteration and broader participation in software creation. Despite these advantages, 4GLs have limitations in flexibility, particularly for handling intricate algorithms or performance-critical components, where their higher-level abstractions can lead to inefficiencies or insufficient control. In such cases, developers often must integrate 3GL modules to embed low-level logic, as 4GLs are generally less powerful for complex computations and may generate resource-intensive code. Performance benchmarks from comparative studies highlight that while 4GLs excel in development speed, they can underperform 3GLs in execution efficiency, necessitating hybrid approaches for robust enterprise systems.

Major Categories

Database Query and Manipulation Languages

Database query and manipulation languages represent a core category of fourth-generation programming languages (4GLs), designed to facilitate direct interaction with relational databases through high-level, declarative syntax that abstracts away low-level procedural details. These languages prioritize ease of use for , modification, and management, allowing users to specify what data is needed rather than how to compute it, which aligns with the non-procedural ethos of 4GLs. A prototypical example is SQL (Structured Query Language), which enables non-programmers to manipulate relational data without writing procedural code, marking it as a foundational 4GL for database operations. SQL was standardized by the (ANSI) in 1986 as ANSI X3.135, providing a vendor-neutral framework for database interactions that has since become ubiquitous. Key features include declarative queries such as SELECT statements for retrieving , JOIN operations to combine tables, and aggregation functions like SUM, , and AVG to summarize results, all of which operate on relational models without requiring explicit loops or conditionals. These elements integrate seamlessly with database management systems (DBMS) like and , where SQL serves as the primary interface for querying and updating stores. For instance, Informix-4GL embeds SQL statements directly into application code, allowing developers to execute queries within a higher-level scripting environment for efficient handling. In practice, languages like Oracle's PL/SQL extend SQL's capabilities through stored procedures, enabling modular data manipulation routines stored within the database itself, such as CREATE PROCEDURE blocks that encapsulate complex queries and updates. Historically, these 4GL tools have been widely adopted in sectors like banking and finance for ad-hoc reporting, where users generate on-demand queries to analyze transaction data or customer records without custom programming. This productivity stems from 4GLs' focus on domain-specific abstraction, reducing development time for database-centric tasks compared to third-generation languages.

Report Generation and Data Analysis Tools

Report generation tools in fourth-generation programming languages (4GLs) are designed to automate the creation of formatted outputs from data sources, often building on database query foundations to extract and present information in structured reports. These tools emphasize non-procedural specifications, allowing users to define report layouts, sorting, grouping, and conditional formatting without detailing low-level steps. Developed primarily for mainframe environments in the 1970s and 1980s, they significantly reduced the manual coding required for periodic business reports, enabling faster development cycles in enterprise computing. One prominent example is FOCUS, a 4GL developed by Information Builders in 1975, which supports report generation through its dialogue-oriented language for defining data extraction, aggregation, and output formatting on mainframes. FOCUS includes features for sorting data by multiple keys, grouping records for subtotals, and applying conditional logic to format elements like headers and footers based on data values. It was widely adopted for business reporting, allowing end-users to produce tabular outputs from with minimal procedural code. Similarly, Easytrieve, originally created by Pansophic Systems in the and later acquired by , functions as a report generator for mainframes, providing 4GL capabilities for and output customization. Its report procedures support sorting and grouping via control fields, conditional formatting through IF-THEN logic, and automatic for multi-page reports. Easytrieve's design streamlined the generation of inventory summaries or , cutting development time compared to third-generation languages like . The RAMIS Report Writer, introduced in the by Mathematica as part of the RAMIS 4GL system, exemplified early report generation by enabling users to specify report structures declaratively, including sorting, grouping by categories, and conditional suppression of lines. Licensed to National CSS, it facilitated ad-hoc reporting in environments and influenced later tools in applications before the rise of OLAP systems in the 1990s. For data analysis, 4GL report tools incorporate built-in statistical functions such as sums, averages, counts, and percentages to summarize datasets without external processing. Base SAS, developed starting in 1976 and recognized as a 4GL, exemplifies this by offering procedures for data transformation and analysis, including aggregation statistics and integration with early formats via file exports. These capabilities supported in sectors like and healthcare during the , reducing reliance on custom programming for routine metrics. Overall, these tools played a pivotal role in enterprise computing by automating report production, with studies showing productivity gains of up to 10 times over procedural languages for standard tasks.

Application and GUI Development Platforms

Fourth-generation programming languages (4GLs) have played a significant role in the development of graphical user interfaces (GUIs) and database-driven applications, particularly through platforms designed for and client-server architectures. Tools like , introduced by Sybase in the late , enabled developers to build interactive client-server applications with visual designers that facilitated the creation of forms and windows without extensive manual coding. Similarly, Progress 4GL, also known as Advanced Business Language (ABL), supported the construction of GUI applications for business environments, integrating database access with user interfaces in a unified development framework. A key feature of these 4GL platforms is the use of screen painters, which allow developers to visually design forms and layouts, generating underlying code automatically for elements like buttons, fields, and menus. For instance, in Progress ABL, the AppBuilder tool provides a graphical interface for defining UI components and linking them to data sources, streamlining the process of creating event-responsive screens. is central to these systems, where application logic responds to user actions such as clicks or ; in , events like button clicks or data changes trigger scripts that handle interactions without requiring procedural sequencing. Data binding further enhances productivity by automatically synchronizing UI elements with database records—for example, 's DataWindow control binds query results to visual controls, enabling seamless updates and validations during runtime. These platforms excelled in rapid GUI prototyping, allowing and deployment of applications in the , a period marked by the transition from character-based to graphical interfaces in . Uniface, a 4GL environment originating in the , supported multi-tier application development with its form designers and component-based architecture, facilitating the distribution of logic across client, server, and data layers for scalable GUIs. In ERP systems, SAP's ABAP incorporated 4GL elements, such as built-in libraries for UI generation and , which powered custom graphical modules for business processes like inventory management. Overall, these tools accelerated the shift to Windows-based graphical applications by automating code generation for deployment in client-server environments, reducing development time from months to weeks in many cases.

Specialized Domain Languages

Specialized domain languages within fourth-generation programming languages (4GLs) are designed for specific technical or creative fields, enabling users to express complex problems in high-level, declarative terms tailored to the domain, thereby abstracting underlying computational algorithms and improving for domain experts. These languages emphasize non-procedural , where the focus is on what the program should achieve rather than how, often through intuitive syntax that mirrors natural problem descriptions in areas like , optimization, , and creative arts. By tuning the language to the nuances of a particular field—such as optimization solvers that hide details like the method behind high-level constraints—specialized 4GLs reduce the need for low-level coding and facilitate and analysis. In mathematical and optimization domains, tools like and LINGO exemplify specialized 4GLs by providing declarative interfaces for numerical computing and . , developed by , functions as a fourth-generation programming language with scripting capabilities that allow users to define matrix operations and optimization problems in a high-level, interactive environment, making it accessible for engineers and scientists without deep programming expertise. For instance, in can be specified through functions like linprog, where users declare an objective function and constraints without implementing the solver algorithm. Similarly, LINGO, from LINDO Systems, is a for optimization that supports declarative formulation of problems, such as linear programs expressed as: minimizecTxsubject toAx≤b,x≥0,\begin{align*} \text{minimize} \quad & \mathbf{c}^T \mathbf{x} \\ \text{subject to} \quad & A \mathbf{x} \leq \mathbf{b}, \\ & \mathbf{x} \geq 0, \end{align*} where c\mathbf{c} is the coefficient vector for the objective, AA the constraint matrix, and b\mathbf{b} the right-hand side, abstracting the simplex method or other solvers into concise, set-based syntax. This domain tuning enables optimization experts to focus on model specification rather than algorithmic implementation. For , early specialized 4GLs like ColdFusion introduced high-level tools for creating dynamic websites, blending markup with scripting to simplify server-side application building. (CFML), its core scripting component, allows developers to embed database queries and logic directly into HTML-like tags, facilitating rapid development of interactive web applications without extensive procedural code. As a fourth-generation , it prioritizes in web contexts by automating common tasks like form handling and . In creative and simulation fields, domain-specific languages like Csound provide high-level abstractions for sound synthesis, enabling composers and sound designers to define synthesis instruments and scores declaratively using unit generators and orchestras, abstracting into high-level score statements for music composition. Similarly, (General Purpose Simulation System) models queuing systems and processes via block diagrams and transaction flows, allowing analysts to specify system behaviors intuitively for without low-level event logic coding; as an early high-level language from the 1960s, it influenced later non-procedural approaches. Additionally, in (CAD), within serves as a domain-specific scripting extension for automating design tasks, such as parametric drawing and entity manipulation, through functions tied to geometric primitives.

Modern Extensions

Low-Code and No-Code Environments

Low-code and no-code environments extend the core principles of fourth-generation programming languages (4GLs) into contemporary by emphasizing visual modeling, from low-level code, and rapid application creation with minimal or no hand-coding. These platforms build on 4GL's non-procedural, domain-oriented approach, enabling users to define application logic through graphical interfaces rather than writing extensive scripts. For instance, and Mendix utilize visual design tools to model data flows, business rules, and interfaces, allowing developers to generate deployable applications from high-level specifications, much like traditional 4GLs such as SQL or report generators but with broader applicability to web and mobile apps. Key features of these environments include drag-and-drop interfaces for constructing workflows and user interfaces, AI-assisted generation for automating code snippets and optimizations, and native integration with management systems (DBMS) like AWS RDS or Azure SQL for seamless data persistence and querying. Drag-and-drop capabilities reduce development time by enabling intuitive assembly of components, while AI tools, such as those in Mendix's AI-assisted modeling, suggest optimizations based on best practices. Integration with cloud DBMS ensures and supports 4GL-like data manipulation without deep infrastructure knowledge, facilitating hybrid deployments across on-premises and environments. Prominent examples include , which specializes in low-code process automation with strong BPMN support for enterprise workflows, and Bubble, a no-code platform that empowers non-technical users to build full-stack web applications via visual editors. The growth of these platforms underscores their impact, with the low-code development technologies market reaching approximately $45.5 billion in 2025. This expansion reflects 4GL's enduring legacy in promoting citizen development, where non-IT professionals contribute to app creation; as of 2025, approximately 80% of businesses report using low-code tools, though exact percentages for new applications vary by region and sector, and earlier forecasts predicted that 70% of new applications developed by organizations would utilize low-code or no-code technologies by 2025, up from less than 25% in 2020. In 2025, fourth-generation programming languages (4GLs) maintain significant relevance in enterprise environments, particularly for maintaining legacy systems that underpin critical operations in sectors like and . For instance, tools such as FOCUS and continue to support in mainframe-based applications, often integrated with in hybrid setups to extend the life of decades-old infrastructure without full rewrites. According to a 2025 analysis, such legacy 4GL systems consume up to 80% of IT budgets in some organizations due to ongoing needs, highlighting their entrenched role despite modernization efforts. Simultaneously, 4GL concepts have resurged through low-code platforms in workflows, enabling faster prototyping and automation in data analytics and internal tooling, as seen in integrations with pipelines and declarative tools like Terraform. A key trend amplifying 4GL's influence is the integration of (AI) for automated code generation and optimization, bridging traditional 4GL abstractions with generative models. Platforms like draw on 4GL-like productivity by translating prompts into domain-specific code, reducing development time by up to 55% for routine tasks. Gartner forecasts that by 2026, 75% of new business applications will leverage low-code technologies, with AI-powered variants contributing to low-code platforms powering 80% of mission-critical applications by 2029. This synergy addresses 4GL's historical limitations in scalability, though challenges persist, such as enhanced security requirements in no-code platforms to mitigate vulnerabilities in AI-assisted outputs. Looking ahead, 4GLs are poised to influence future paradigms through voice and interfaces, often framed as 5GL advancements that prioritize intent-based programming over procedural syntax. In , emerging tools allow developers to describe applications in , generating code via large language models, which could democratize software creation beyond expert users and build directly on 4GL's focus. IDC's MarketScape report underscores this trajectory, positioning low-code platforms with AI and agentic capabilities as foundational for . However, realization depends on overcoming AI's current gaps in production reliability, ensuring human oversight remains integral.

References

  1. https://nvlpubs.nist.gov/nistpubs/Legacy/SP/nbsspecialpublication500-143.pdf
  2. https://dl.acm.org/doi/pdf/10.1145/989341.989351
  3. https://www.ibm.com/history/sql
  4. https://thesai.org/Downloads/Volume11No6/Paper_23-4GL_Code_Generation_A_Systematic_Review.pdf
  5. https://cacm.acm.org/practice/the-realities-of-software-technology-payoffs/
  6. https://dl.acm.org/doi/10.1145/66099.66483
  7. https://apps.dtic.mil/sti/tr/pdf/ADA171773.pdf
  8. http://www.decosta.com/Nomad/tales/history.html
  9. https://www.ibm.com/history/system-r
  10. https://cacm.acm.org/opinion/how-charles-bachman-invented-the-dbms-a-foundation-of-our-digital-world/
  11. https://www.ibm.com/docs/en/zos-basic-skills?topic=ims-software
  12. https://apps.dtic.mil/sti/pdfs/ADA171773.pdf
  13. https://www.inf.fu-berlin.de/lehre/SS01/hc/minicomp/
  14. http://archive.computerhistory.org/resources/text/Oral_History/RAMIS_and_NOMAD/RAMIS_and_NOMAD.National_CSS.oral_history.2005.102658182.pdf
  15. https://ieeexplore.ieee.org/document/6774378
  16. https://research.ibm.com/publications/query-by-example
  17. https://dl.acm.org/doi/10.1007/978-3-642-40564-8_2
  18. https://learnsql.com/blog/history-of-sql-standards/
  19. https://cologne-data.de/2019_01_DOAG_RedStack_oracleforms_is_stronger_than_time.pdf
  20. https://www.computer.org/csdl/magazine/so/1988/04/s4008/13rRUx0xPg7
  21. https://apps.dtic.mil/sti/tr/pdf/ADA305960.pdf
  22. https://hitech-us.com/articles/entry/000/evolution-of-programming-languages-understanding-the-past-present-and-future
  23. https://www.techmonitor.ai/hardware/how_cobol_held_off_threat_of_the_fourth_generation_why_the_end_may_now_be_nigh
  24. https://www.cnet.com/tech/tech-industry/ca-updates-y2k-tool/
  25. https://homepage.cs.uri.edu/faculty/wolfe/book/programming/chapsix.html
  26. https://nap.nationalacademies.org/read/5463/chapter/11
  27. https://dl.acm.org/doi/pdf/10.5555/1074100.1074642
  28. https://go.gale.com/ps/i.do?id=GALE%257CA18993834&sid=googleScholar&v=2.1&it=r&linkaccess=abs&issn=00010782&p=AONE&sw=w
  29. https://aisel.aisnet.org/cgi/viewcontent.cgi?article=1945&context=misq
  30. https://www.jstor.org/stable/40397799
  31. https://www.researchgate.net/publication/228388061_Strategic_Software_Development_Productivity_Comparisons_of_General_Development_Programs
  32. https://www.sciencedirect.com/topics/computer-science/generation-language
  33. https://zourpri.files.wordpress.com/2014/01/gartner-glossary-of-ict-acronyms-and-terms.pdf
  34. https://thorteaches.com/glossary/fourth-generation-language-4gl/
  35. https://www.gocodeo.com/post/fourth-generation-programming-languages-4gls-what-developers-need-to-know-in-2025
  36. https://blog.ansi.org/ansi/sql-standard-iso-iec-9075-2023-ansi-x3-135/
  37. https://www.ibm.com/think/topics/structured-query-language
  38. https://www.ibm.com/docs/en/informix-servers/14.10.0?topic=statements-select-statement
  39. https://docs.oracle.com/cd/B28359_01/appdev.111/b28843/tdddg_procedures.htm
  40. https://www.sciencedirect.com/science/article/pii/0950584989900372
  41. https://docs.tibco.com/products/ibi-focus-9-0-5
  42. https://www.pcmag.com/encyclopedia/term/ca-easytrieve
  43. https://www.broadcom.com/products/mainframe/foundational-and-open-mainframe/easytrieve-report-generator
  44. https://techdocs.broadcom.com/us/en/ca-mainframe-software/devops/ca-easytrieve-report-generator/11-6/programming/report-processing/report-procedures.html
  45. https://conservancy.umn.edu/bitstreams/654e5900-8396-46cd-896c-e8001fac4b8f/download
  46. https://www.sas.com/content/dam/SAS/en_us/doc/factsheet/base-sas-101198.pdf
  47. https://documentation.sas.com/doc/en/lrcon/9.4/n0toa1y5c8wkpxn1duru2ltw8i52.htm
  48. https://dl.acm.org/doi/pdf/10.1145/323275.323299
  49. https://www.progress.com/openedge/developer
  50. https://docs.progress.com/bundle/openedge-develop-abl-applications/page/User-interface-events.html
  51. https://pblib.com/knowledge-base/writing-server-scripts-pb-docs-80/
  52. https://www.appeon.com/system/files/product-manual/datawindow_programmers_guide.pdf
  53. https://www.bloorresearch.com/companies/uniface/
  54. https://help.sap.com/docs/SAP_NETWEAVER_AS_ABAP_FOR_SOH_740/7bfe8cdcfbb040dcb6702dada8c3e2f0/230ffbcaeaa1404889322ced79dfc187.html
  55. https://technology.oregonstate.edu/software/matlab
  56. https://www.lindo.com/index.php/products/lingo-and-optimization-modeling
  57. https://csound.com/
  58. https://www.infoworld.com/article/4049946/is-ai-the-4gl-weve-been-waiting-for.html
  59. https://www.gartner.com/reviews/market/enterprise-low-code-application-platform
  60. https://www.jitterbit.com/blog/the-future-of-low-code/
  61. https://www.index.dev/blog/no-code-low-code-statistics
  62. https://www.gartner.com/en/newsroom/press-releases/2021-11-10-gartner-says-cloud-will-be-the-centerpiece-of-new-digital-experiences
  63. https://www.gartner.com/en/documents/3995846
  64. https://www.linkedin.com/posts/douglautzenheiser_how-hard-is-it-to-migrate-from-a-mainframe-activity-7365143773497995265-sGsP
  65. https://www.bairesdev.com/blog/top-programming-languages/
  66. https://www.pragmaticcoders.com/resources/legacy-code-stats
  67. https://www.thoughtworks.com/en-ca/insights/blog/generative-ai/experiment-github-copilot-practical-guide
  68. https://arxiv.org/abs/2406.17910
  69. https://blog.tooljet.ai/gartner-forecast-on-low-code-development-technologies/
  70. https://www.gartner.com/en/newsroom/press-releases/2022-12-13-gartner-forecasts-worldwide-low-code-development-technologies-market-to-grow-20-percent-in-2023
  71. https://sapinsider.org/map/low-code-development-trends-in-2025/
  72. https://www.salesforce.com/news/stories/idc-low-code-no-code-developer-tools-2025/
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