ISSN:0737-0024    

DOI:10.1207/s15327051hci0102_1

出版商:Lawrence Erlbaum Associates, Inc.    

年代:1985

数据来源: Taylor

摘要:

Four experiments study the errors students make using LISP functions. The first two experiments show that frequency of errors is increased by increasing the complexity of irrelevant aspects of the problem. The experiments also show that the distribution of errors is largely random and that subjects' errors seem to result from slips rather than from misconceptions. Experiment 3 shows that subjects' errors tend to involve loss of parentheses in answers when the resulting errors are well-formed LISP expressions. Experiment 4 asks subjects, who knew no LISP, to judge the reasonableness of the answers to various LISP function calls. Subjects could detect many errors on the basis of general criteria of what a reasonable answer should look like. On the basis of these four experiments, we conclude that errors occur when there is a loss of information in the working memory representation of the problem and when the resulting answer still looks reasonable.

ISSN:0737-0024    

DOI:10.1207/s15327051hci0102_2

出版商:Lawrence Erlbaum Associates, Inc.    

年代:1985

数据来源: Taylor

摘要:

We present a process model to explain bugs produced by novices early in a programming course. The model was motivated by interviews with novice programmers solving simple programming problems. Our key idea is that many programming bugs can be explained by novices inappropriately using their knowledge of step-by-step procedural specifications in natural language. We view programming bugs as patches generated in response to an impasse reached by the novice while developing a program. We call such patching strategies bug generators. Several of our bug generators describe how natural language preprogramming knowledge is used by novices to create patches. Other kinds of bug generators are also discussed. We describe a representation both for novice natural language preprogramming knowledge and novice fragmentary programming knowledge. Using these representations and the bug generators, we evaluate the model by analyzing four interviews with novice programmers.

ISSN:0737-0024    

DOI:10.1207/s15327051hci0102_3

出版商:Lawrence Erlbaum Associates, Inc.    

年代:1985

数据来源: Taylor

摘要:

In this paper, we present a descriptive theory of buggy novice programs and a bug categorization scheme that is based on this theory. Central to this theory is the cognitively plausible knowledge - goals and plans - that underlies programming. The bug categorization scheme makes explicit problem-dependent goal and plan knowledge at many different levels of detail. We provide several examples of how the scheme permits us to focus on bugs in a way that facilitates generating plausible accounts of why the bugs may have arisen. In particular, our approach has led us to one explanation of why some novice programs are buggier than others. A basic part of this explanation is the notion of merged goals and merged plans in which a single integrated plan is used to achieve multiple goals.

ISSN:0737-0024    

DOI:10.1207/s15327051hci0102_4

出版商:Lawrence Erlbaum Associates, Inc.    

年代:1985

数据来源: Taylor