Open PROMOL: An Experimental Language for Target Program Modification

Štuikys, Vytautas; Damaševičius, Robertas; Ziberkas, Giedrius

doi:10.1007/978-1-4757-6674-5_20

Cited by 17 publications

(6 citation statements)

References 5 publications

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“…The LO sequence metaprogram is implemented using Open PROMOL metalanguage [21]. A wrapper metaprogram is created, which wraps the earlier developed sorting GLO metaprogram (Figure 2), provides a meta-interface for LO sequence parameters, and organizes LO sequence generation and storage.…”

Section: Figure 1 Feature Diagram Of Sorting Lo Sequence (A Fragment)mentioning

confidence: 99%

Specification and Generation of Learning Object Sequences for E-learning Using Sequence Feature Diagrams and Metaprogramming Techniques

Damaševičius

Štuikys

2009

2009 Ninth IEEE International Conference on Advanced Learning Technologies

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The success of learning objects (LO) is limited by the ability to integrate them into coherent teaching courses in order to enable the educational goaloriented creation of competency. LO sequences must be defined that are adapted to different types of learners, their personal needs and knowledge states to allow for effective personalized learning. In this paper, we propose a method for specification of LO sequences using Sequence Feature Diagrams and describe the generation of LO sequences from Generative LOs using metaprogramming techniques.

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Section: Figure 1 Feature Diagram Of Sorting Lo Sequence (A Fragment)mentioning

confidence: 99%

Specification and Generation of Learning Object Sequences for E-learning Using Sequence Feature Diagrams and Metaprogramming Techniques

Damaševičius

Štuikys

2009

2009 Ninth IEEE International Conference on Advanced Learning Technologies

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“…The majority vote function is used in different applications such as fault tolerant computing and machine learning. One-stage meta-program for implementing the majority vote function using Open PROMOL [35] as meta-language and VHDL as domain language has been presented in [36]. Here we present a multi-stage version of it (Figure 7), one of its meta-program instances (Figure 8) and a fragment of generated VHDL program instance (Figure 9).…”

Section: Majority Vote Functionmentioning

confidence: 99%

Understanding of Heterogeneous Multi-Stage Meta-Programs

Štuikys

Damaševičius

Ziberkas

2012

ITC

Self Cite

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The paper analyzes an approach to understanding heterogeneous meta-programs and multi-stage metaprograms. At the core of the approach is human-centred analysis combined with the Brook's program cognition theory and the concept of reverse engineering. The use of the approach leads to extracting higher-level models (graphs representing meta-parameter -meta-function relationship models, feature diagrams and algorithms) from correct meta-specifications. The models and processes enable not only to better understand the multi-stage heterogeneous meta-programs but also to contribute to their evolution. The paper describes some properties of the multi-stage heterogeneous meta-programs. The approach is supported by the case study and complexity evaluation.

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“…The advantages of the scripting languages should be reached by avoidance of certain weaknesses of the Object-oriented programming, which are, according to Ousterhout [16], rigidity of the object model, high level of typing and the need of the translation/compilation phase during the program development. There are some scripting language characteristics that could be useful for Generative programming: a scripting language abilities in the character strings processing [13] [19], the possibilities of connecting completed components written in the target programming languages [19] and flexibility of the scripting languages syntax which arise from a low typing level [16] [19]. Except of using existing scripting languages, some projects on making specialized scripting languages aimed at Generative programming were conceived, such as Open Promol [19] and CodeWorker [13].…”

Section: Related Workmentioning

confidence: 99%

Introducing Polymorphic Features into a Scripting Model of Generator

Radošević

Magdalenić

2011

CIT

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Generative programming is a discipline of Automatic programming which strives to make application and the generator development process flexible and generated program code optimized. Because of the lack of appropriate graphic and aspect based generator models, we developed the Scripting model of generator, as a static generator model based on higher level scripts. This paper gives a formal definition of the Scripting model and describes how basic object model properties, like encapsulation, inheritance, and now, polymorphism are achieved. This offers some advantages in generative application development, such as more precise application specification, better generator reusability, and simpler generator model and its easier implementation. The introduced polymorphic features are presented in an illustrative example of a Java application generator.

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Open PROMOL: An Experimental Language for Target Program Modification

Cited by 17 publications

References 5 publications

Specification and Generation of Learning Object Sequences for E-learning Using Sequence Feature Diagrams and Metaprogramming Techniques

Specification and Generation of Learning Object Sequences for E-learning Using Sequence Feature Diagrams and Metaprogramming Techniques

Understanding of Heterogeneous Multi-Stage Meta-Programs

Introducing Polymorphic Features into a Scripting Model of Generator

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