Concepts and Methodologies for Knowledge-Based Program Understanding--The ALPUS's Approach--

Haruki UENO

Concepts and Methodologies for Knowledge-Based Program Understanding--The ALPUS's Approach--

Haruki UENO

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The background concepts and methodologies of the knowledge-based program understander ALPUS is discussed. ALPUS understands user's buggy Pascal programs using four kinds of programming knowledge: the knowledge on algorithms, programming techniques, the Pascal language, and logical bugs. The knowledge on algorithms, the key knowledge, is represented in a form of hierarchical data structure called Hierarchical Procedure Graph (HPG). In HPG each node represents a chunk of operations called process," which is consisted of sub-processes. The other knowledge is maintained as independent knowledge bases and linked to associated processes of the HPG. The knowledge about bugs acquired by cognitive experiment is grouped into three categories: bugs on algorithms, programming techniques, and the Pascal language, and connected to associated elements of programming knowledge respectively. ALPUS tries to understand user's buggy programs, detects logical bugs, infers user's intentions, and gives advices for fixing bugs. Program understanding is achieved by three steps: normalization, variable identification, and process and technique identification. Normalization results in improving flexibility of understanding. Variable, process and technique identifications are achieved by knowledge-based pattern matching. Intentions are inferred by means of information attached to buggy patterns. The result of comprehension is reported to a user (i.e., student). Experimental results using Quicksort programs written by students show that the HPG formalism is quite powerful in understanding algorithm-oriented programs. The ALPUS's way of program comprehension is useful in the situation of programming education in an intermediate class of an engineering school. The ALPUS system is a subsystem of the intelligent programming environment INTELLITUTOR for learning programming, which was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.

Publication: IEICE TRANSACTIONS on Information Vol.E78-D No.9 pp.1108-1117

Publication Date: 1995/09/25

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Type of Manuscript: Special Section PAPER (Special Issue on Knowledge Based Software Engineering)

Category: Methodologies

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Haruki UENO, "Concepts and Methodologies for Knowledge-Based Program Understanding--The ALPUS's Approach--" in IEICE TRANSACTIONS on Information, vol. E78-D, no. 9, pp. 1108-1117, September 1995, doi: .
Abstract: The background concepts and methodologies of the knowledge-based program understander ALPUS is discussed. ALPUS understands user's buggy Pascal programs using four kinds of programming knowledge: the knowledge on algorithms, programming techniques, the Pascal language, and logical bugs. The knowledge on algorithms, the key knowledge, is represented in a form of hierarchical data structure called Hierarchical Procedure Graph (HPG). In HPG each node represents a chunk of operations called process," which is consisted of sub-processes. The other knowledge is maintained as independent knowledge bases and linked to associated processes of the HPG. The knowledge about bugs acquired by cognitive experiment is grouped into three categories: bugs on algorithms, programming techniques, and the Pascal language, and connected to associated elements of programming knowledge respectively. ALPUS tries to understand user's buggy programs, detects logical bugs, infers user's intentions, and gives advices for fixing bugs. Program understanding is achieved by three steps: normalization, variable identification, and process and technique identification. Normalization results in improving flexibility of understanding. Variable, process and technique identifications are achieved by knowledge-based pattern matching. Intentions are inferred by means of information attached to buggy patterns. The result of comprehension is reported to a user (i.e., student). Experimental results using Quicksort programs written by students show that the HPG formalism is quite powerful in understanding algorithm-oriented programs. The ALPUS's way of program comprehension is useful in the situation of programming education in an intermediate class of an engineering school. The ALPUS system is a subsystem of the intelligent programming environment INTELLITUTOR for learning programming, which was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.
URL: https://global.ieice.org/en_transactions/information/10.1587/e78-d_9_1108/_p

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@ARTICLE{e78-d_9_1108,
author={Haruki UENO, },
journal={IEICE TRANSACTIONS on Information},
title={Concepts and Methodologies for Knowledge-Based Program Understanding--The ALPUS's Approach--},
year={1995},
volume={E78-D},
number={9},
pages={1108-1117},
abstract={The background concepts and methodologies of the knowledge-based program understander ALPUS is discussed. ALPUS understands user's buggy Pascal programs using four kinds of programming knowledge: the knowledge on algorithms, programming techniques, the Pascal language, and logical bugs. The knowledge on algorithms, the key knowledge, is represented in a form of hierarchical data structure called Hierarchical Procedure Graph (HPG). In HPG each node represents a chunk of operations called process," which is consisted of sub-processes. The other knowledge is maintained as independent knowledge bases and linked to associated processes of the HPG. The knowledge about bugs acquired by cognitive experiment is grouped into three categories: bugs on algorithms, programming techniques, and the Pascal language, and connected to associated elements of programming knowledge respectively. ALPUS tries to understand user's buggy programs, detects logical bugs, infers user's intentions, and gives advices for fixing bugs. Program understanding is achieved by three steps: normalization, variable identification, and process and technique identification. Normalization results in improving flexibility of understanding. Variable, process and technique identifications are achieved by knowledge-based pattern matching. Intentions are inferred by means of information attached to buggy patterns. The result of comprehension is reported to a user (i.e., student). Experimental results using Quicksort programs written by students show that the HPG formalism is quite powerful in understanding algorithm-oriented programs. The ALPUS's way of program comprehension is useful in the situation of programming education in an intermediate class of an engineering school. The ALPUS system is a subsystem of the intelligent programming environment INTELLITUTOR for learning programming, which was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.},
keywords={},
doi={},
ISSN={},
month={September},}

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TY - JOUR
TI - Concepts and Methodologies for Knowledge-Based Program Understanding--The ALPUS's Approach--
T2 - IEICE TRANSACTIONS on Information
SP - 1108
EP - 1117
AU - Haruki UENO
PY - 1995
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E78-D
IS - 9
JA - IEICE TRANSACTIONS on Information
Y1 - September 1995
AB - The background concepts and methodologies of the knowledge-based program understander ALPUS is discussed. ALPUS understands user's buggy Pascal programs using four kinds of programming knowledge: the knowledge on algorithms, programming techniques, the Pascal language, and logical bugs. The knowledge on algorithms, the key knowledge, is represented in a form of hierarchical data structure called Hierarchical Procedure Graph (HPG). In HPG each node represents a chunk of operations called process," which is consisted of sub-processes. The other knowledge is maintained as independent knowledge bases and linked to associated processes of the HPG. The knowledge about bugs acquired by cognitive experiment is grouped into three categories: bugs on algorithms, programming techniques, and the Pascal language, and connected to associated elements of programming knowledge respectively. ALPUS tries to understand user's buggy programs, detects logical bugs, infers user's intentions, and gives advices for fixing bugs. Program understanding is achieved by three steps: normalization, variable identification, and process and technique identification. Normalization results in improving flexibility of understanding. Variable, process and technique identifications are achieved by knowledge-based pattern matching. Intentions are inferred by means of information attached to buggy patterns. The result of comprehension is reported to a user (i.e., student). Experimental results using Quicksort programs written by students show that the HPG formalism is quite powerful in understanding algorithm-oriented programs. The ALPUS's way of program comprehension is useful in the situation of programming education in an intermediate class of an engineering school. The ALPUS system is a subsystem of the intelligent programming environment INTELLITUTOR for learning programming, which was implemented in the frame-based knowledge engineering environment ZERO on a UNIX workstation.
ER -