Tools for Building Application Generators

Cleaveland, J. Craig; Kintala, Chandra M. R.

doi:10.1002/j.1538-7305.1988.tb00637.x

Cited by 16 publications

(2 citation statements)

References 8 publications

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“…Many popular programming languages (such as C) are not context free, so Yacc provides "semantic actions" that can be used to access symbol tables, etc. More modern tools, such as the Pan system [Ballance et al 1990], Metatool [Cleaveland and Kintala 1988], Eli [Gray et al 1992], CENTAUR [Borras et al 1988], Gandalf [Habermann and Notkin 1986], and the Cornell Synthesizer Generator [Reps and Teitelbaum 1984], provide an integrated environment to implement syntax/semantic processing.…”

Section: Genoamentioning

confidence: 99%

GENOA—a customizable, front-end-retargetable source code analysis framework

Dévanbu

1999

ACM Trans. Softw. Eng. Methodol.

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Code analysis tools provide support for such software engineering tasks as program understanding, software metrics, testing, and reengineering. In this article we describe GENOA, the framework underlying application generators such as Aria and GENϩϩ which have been used to generate a wide range of practical code analysis tools. This experience illustrates front-end retargetability of GENOA; we describe the features of the GENOA framework that allow it to be used with different front ends. While permitting arbitrary parse tree computations, the GENOA specification language has special, compact iteration operators that are tuned for expressing simple, polynomial-time analysis programs; in fact, there is a useful sublanguage of the GENOA language that can express precisely all (and only) polynomial-time (PTIME) analysis programs on parse trees. Thus, we argue that the GENOA language is a simple and convenient vehicle for implementing a range of analysis tools. We also argue that the "front-end reuse" approach of GENOA offers an important advantage for tools aimed at large software projects: the reuse of complex, expensive build procedures to run generated tools over large source bases. In this article, we describe the GENOA framework and our experiences with it.

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Section: Genoamentioning

confidence: 99%

GENOA—a customizable, front-end-retargetable source code analysis framework

Dévanbu

1999

ACM Trans. Softw. Eng. Methodol.

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“…An alternative to using lex and yacc for creating application generators is AT&Ts Meta'Iool' specification-driven toolbuilder" (SDTB), formerly known as STAGE. 4 An SDTB generates application generators (we often refer to it as an application-generator generator) and greatly reduces the effort needed to create them. Figure 1 shows the structure ofthe softwaredevelopmentenvironment when using the MetaTool specification-driven toolbuilder.…”

Section: Application Generatorsmentioning

confidence: 99%

Makcal: An Application Generator for Advice

Toth

1991

At&T Technical Journal

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With the increased sophistication of analog‐circuit simulation tools comes a heavier reliance on the interfaces to these tools. Today, designers can control simulation tools through programs—a technique referred to as procedural simulation—and derive performance measures (e.g., common‐mode rejection ratio, bandwidth, etc.) easily from more‐basic circuit‐simulation variables (i.e., voltages and currents). This technique has proved to be a valuable feature of AT&T's analog‐circuit simulator, ADVICE. To enable designers to exploit procedural simulation more fully, a program called makca1 was created. Makca1 writes a procedural‐simulation program that a designer can use to control ADVICE. Makca1 includes the capability to select and present performance measures in a variety of graphic and textual formats. Because makca1 streamlines the programming process, designers can concentrate more fully on designing, which reduces the product's time to market.

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Specification‐Driven Tools and Techniques

Cleaveland¹

2002

Encyclopedia of Software Engineering

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Specification‐driven tools (SDTs) translate specifications to products such as programs, documentation, tables, and test scripts. SDTs represent a large class of techniques that have independently evolved under a variety of names including application generators, program generators, 4GLs (fourth generation languages), automatic programming, lower CASE tools, and application‐oriented languages. SDTs increase productivity and quality and are most successful in programming areas that are well understood and repetitive such as databases, user interfaces, and translators. SDTs are an effective way to reuse software code and design. Unlike code reuse libraries, SDTs generate customized software that is not modified by the user. A typical SDT for building parsers from grammar descriptions is shown. The productivity and quality of SDTs is achieved by two major factors: narrow domains and understandable specification languages. A “domain” is the area of applicability. General‐purpose programming languages are useful for very large problem domains. The second major factor for increased productivity and quality of SDTs is the specification language. It must be significantly easier to understand than the generated code. It should be much shorter, should not contain unnecessary implementation details, and it should be understandable to nonprogrammers—ideally, the customer. However, specification languages are not necessarily simple. Example problem domains and tools for building SDTs are described.

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Tools for Building Application Generators

Cited by 16 publications

References 8 publications

GENOA—a customizable, front-end-retargetable source code analysis framework

GENOA—a customizable, front-end-retargetable source code analysis framework

Makcal: An Application Generator for Advice

Specification‐Driven Tools and Techniques

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