This research was partially sponsored by NCCOSC under Contract No. N66001-94-C-6037, Arpa OrderNo. B326, and partially by NSF under grant number IRI-9319969. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official poli-cies, either expressed or implied, of the U.S. Government.

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Abstract. The goal of our study is to evaluate the effect on program comprehension of three factors that have not previously been studied in a single experiment. These factors are programmer expertise (expert versus novice), programming task (documentation versus reuse), and the development of understanding over time (phase 1 versus phase 2). This study is carried out in the context of the mental model approach to comprehension based on van Dijk and Kintsch’s model [(1983) Strategies of Discourse Comprehension. New York: Academic]. One key aspect of this model is the distinction between two kinds of representation the reader might construct from a text: (1) the textbase, which refers to what is said in the text and how it is said, and (2) the situation model, which represents the situation referred to by the text. We have evaluated the effect of the three factors mentioned above on the development of both the textbase (or program model) and the situation model in object-oriented program comprehension. We found a four-way interaction of expertise, phase, task and type of model. For the documentation group we found that experts and novices differ in the elaboration of their situation model but not their program model. There was no interaction of expertise with phase and type of model in the documentation group. For the reuse group, there was a three-way interaction between phase, expertise and type of model. For the novice reuse group, the effect of the phase was to increase the construction of the situation model but not the program model.

New approaches to teaching introductory computer science are sorely needed. Current instruction in programming has been shown to result in relatively poor understanding of the programming language under study, little development of problem solving skills, and little

In order to implement real-time adaptive augmented cognition, one of the focal points of our present research involves understanding the dimensions of task complexity. Task complexity is a construct that has been used in many fields such as biology, computer science, and psychology. An objective of our current research effort is to be able to instantaneously assess change in the cognitive capabilities of people as they perform increasingly complex tasks. In order to address these broader goals, a better understanding of task complexity is needed. Specific questions we ask include: (1) What are the factors that contribute to task complexity? (2) What are effective ways to assess task complexity? and (3) How can task complexity be reduced in real-time tasks? In order to address these questions, we review literature related to task complexity across several domains such as user models, human computer interaction, human factors and instructional design.

Computer programmers break apart large programs into smaller coherent pieces. Each of these pieces: func-tions, subroutines, modules, or abstract datatypes, is usually a contiguous piece of program text. The experi-ment reported here shows that programmers also rou-tinely break programs into one kind of coherent piece which is not coniguous. When debugging unfamiliar pro-grams programmers use program pieces called slices which are sets of statements related by their flow of data. The statements in a slice are not necessarily textually contiguous, but may be scattered through a program.