LAURA, a system to debug student programs

Adam, Anne; Laurent, Jean-Pierre

doi:10.1016/0004-3702(80)90023-5

Cited by 70 publications

(39 citation statements)

References 21 publications

(12 reference statements)

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“…Each node has a type which is taken from a vocabulary of node types. 2. Each node has two disjoint tuples of ports, called its inputs and outputs.…”

Section: Flow Graphsmentioning

confidence: 99%

“…This information is useful in presenting the results of recognition and can be a source of guidance for the recognition system, as discussed in Section 4. 2…”

Section: Edge Attributesmentioning

confidence: 99%

“…This is expressed as: the feedback-ce of the innermost recursion containing the test must be C-the failure-ce of the test. 2. The success-ce of the test is one possible way to exit the recursion (but there may be another exit test in whose success-ce the recursion is also exited).…”

Section: Encoding Temporal Abstractions In Grammar Rulesmentioning

confidence: 99%

“…Figure 6-8 shows the results of running the CST example under the following four conditions: a) parse-interleave both constraints, b) match-interleave co-occurrence, parseinterleave port precedence, c) parse-interleave co-occurrence, match-interleave port precedence, and d) match-interleave both. 2 In Figure 6-8, the number of items created by the parser is shown as the number of items of three different types. "Successful" items are complete items which satisfy all their rules' constraints.…”

Section: Access-firtmentioning

confidence: 99%

“…This is done by applying an attribute combination function, which is defined for each attribute, to the attribute values of n 1 and n 2 . The attribute combination functions may be partial functions.…”

mentioning

confidence: 99%

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Automated Program Recognition by Graph Parsing

Wills¹

1992

107

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JAN 22 1993_ 93-01046 93 J21 034- REPORT DOCUMENTATION PAGEForM N=o07-1 01MB NO 0704-0188 Pub•ic reporting burden for this collection of information is estimated to averaqe I hour oer response. including the time for revewing Instructions. searchrg e.-st'ng sata sour'., gathering and maintaining the data needed, and completing and reviewing the collection of information Send comments retarding this burden estimate or any other asoect Of this ol lection of information, including suggestions for reducing this burden, We demonstrate that this graph parsing approach is a feasible and useful way to automate program recognition. In studying this approach, we have experimented with two medium-sized, real-world simulator programs. There are three aspects of our study. First, we evaluate our representation's ability to suppress many common forms of program variation which hinder recognition. Second, we investigate the expressiveness of our graph grammar formalism for capturing programming cliches. Third, we empirically and analytically study the computational cost of our recognition approach with respect to the real-world simulator programs. The recognition of standard computational structures (cliches) in a program can help an experienced programmer understand the program. Based on the known relationships between the cliches, a hierarchical description of the program's design can be recovered. We develop and study a graph parsing approach to automating program recognition in which programs are represented as attributed dataflow graphs and a library of cliches is encoded as an attributed graph grammar. Graph parsing is used to recognize clich6s in the code. We demonstrate that this graph parsing approach is a feasible and useful way to automate program recognition. In studying this approach, we have experimented with two medium-sized, real-world simulator programs. There are three aspects of our study. First, we evaluate our representation's ability to suppress many common forms of program variation which hinder recognition. Second, we investigate the expressiveness of our graph grammar formalism for capturing programming clich6s. Third, we empirically and analytically study the computational cost of our recognition approach with respect to the real-world simulator programs.

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“…Each node has a type which is taken from a vocabulary of node types. 2. Each node has two disjoint tuples of ports, called its inputs and outputs.…”

Section: Flow Graphsmentioning

confidence: 99%

“…This information is useful in presenting the results of recognition and can be a source of guidance for the recognition system, as discussed in Section 4. 2…”

Section: Edge Attributesmentioning

confidence: 99%

Section: Encoding Temporal Abstractions In Grammar Rulesmentioning

confidence: 99%

Section: Access-firtmentioning

confidence: 99%

mentioning

confidence: 99%

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Automated Program Recognition by Graph Parsing

Wills¹

1992

107

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Novice program recognition/diagnosis system based on goal/plan concepts

Kaijiri

1996

Systems & Computers in Japan

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SUMMARYStudies on program understanding/recognition have been conducted from various points of view, including debugging. However, the target, the range and the kind of recognition, differ according to objectives. A new problem description method and a new recognition method whose objective is to help novices learn program design and debugging is proposed here. This method has the following characteristics:It uses the algorithm level problem description. It is called the problem solution tree.The problem solution tree has positional information regarding goals.It uses a variety of matching methods to enable matching with many erroneous student programs.It uses a partial recognition strategy to diagnose programs with which full matching failed.The system recognized that approximately 85 percent of the novice samples are not well formed.

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Fatal error in pass zero: How not to confuse novices

Boulay

Matthew

1984

Readings on Cognitive Ergonomics — Mind and Computers

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LAURA, a system to debug student programs

Cited by 70 publications

References 21 publications

Automated Program Recognition by Graph Parsing

Automated Program Recognition by Graph Parsing

Novice program recognition/diagnosis system based on goal/plan concepts

Fatal error in pass zero: How not to confuse novices

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