Synthesis of UNIX programs using derivational analogy

Bhansali, Sanjay; Harandi, Mehdi T.

doi:10.1007/bf00993480

Cited by 13 publications

(5 citation statements)

References 13 publications

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“…An analogous design (or source) with similar requirements could be retrieved, then adapted or transformed for the current design with the assistance of domain knowledge in the form of heuristic rules and transformation operators. If a design plan is stored with the source design solution, it provides more information about adaptation and transformation (Bhansali & Harandi, 1992).…”

Section: An Analogy-based Design Modelmentioning

confidence: 99%

Function–behavior–structure paths and their role in analogy-based design

Qian

Gero

1996

AIEDAM

221

119

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In many creative design processes, cross-domain knowledge is required to inspire the new design result. Thus, in knowledge-based design, how we represent the cross-domain knowledge becomes a key issue. In this paper, we present a formalism for design knowledge representation. By analyzing function representation in different design domains, from graphic design and industrial design to architectural and engineering device designs, we find that although the focus of each kind of design is different, the function representation can be generalized into a small number of categories. This formalism can be used in an explorative model of design by analogy, where designs from different design domains are sources to help produce a new design.

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Section: An Analogy-based Design Modelmentioning

confidence: 99%

Function–behavior–structure paths and their role in analogy-based design

Qian

Gero

1996

AIEDAM

221

119

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“…Automating the design of this type of software is an important and challenging research task [13] because of the current overwhelming need for high quality software [7]. While there have been some successful demonstrations of partial automation in this area ( [3], [8], [22], [27], [40]), on the whole progress has been slow and limited. The main focus of the Déjà Vu project has been to investigate the potential for CBR to improve matters, and by way of a demonstration, to build a case-based system for automating the design of steel-mill control software.…”

Section: Déjà Vu and The Plant-control Domainmentioning

confidence: 99%

Hierarchical case-based reasoning integrating case-based and decompositional problem-solving techniques for plant-control software design

Smyth

Keane

Cunningham

2001

IEEE Trans. Knowl. Data Eng.

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Case-based reasoning (CBR) is an AI technique that emphasises the role of past experience during future problem solving. New problems are solved by retrieving and adapting the solutions to similar problems, solutions that have been stored and indexed for future reuse as cases in a case-base. The power of CBR is severely curtailed if problem solving is limited to the retrieval and adaptation of a single case, and for this reason the strategy of reusing multiple cases is immediately appealing. This paper describes the technique of hierarchical case-based reasoning, which allows complex problems to be solved by reusing multiple cases at various levels of abstraction. The technique is described in the context of Déjà Vu, a CBR system aimed at automating plant-control software design.

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“…Veloso and Carbonell (1993) described a derivational approach that learns to improve case indices and speed problem solving. Bhansali and Harandi (1993) used derivational analogy to learn how to synthesize UNIX programs. In both cases, several learning opportunities arose, including how to use justification knowledge to direct the search for selecting goals, operators, and bindings.…”

Section: Learning Adaptation Knowledgementioning

confidence: 99%

Case-based learning: Beyond classification of feature vectors

Aha

Wettschereck

1997

Lecture Notes in Computer Science

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The dominant theme of case-based research at recent ML conferences has been on classifying cases represented by feature vectors. However, other useful tasks can be targeted, and other representations are often preferable. We review the recent literature on case-based learning, focusing on alternative performance tasks and more expressive case representations. We also highlight topics in need of additional research.

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Synthesis of UNIX programs using derivational analogy

Cited by 13 publications

References 13 publications

Function–behavior–structure paths and their role in analogy-based design

Function–behavior–structure paths and their role in analogy-based design

Hierarchical case-based reasoning integrating case-based and decompositional problem-solving techniques for plant-control software design

Case-based learning: Beyond classification of feature vectors

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