In this paper we review the literature relating to the psychological/educational study of programming. We identify general trends comparing novice and expert programmers, programming knowledge and strategies, program generation and comprehension, and objectoriented versus procedural programming. (We do not cover research relating specifically to other programming styles.) The main focus of the review is on novice programming and topics relating to novice teaching and learning. Various problems experienced by novices are identified, including issues relating to basic program design, to algorithmic complexity in certain language features, to the ‘‘fragility’ ’ of novice knowledge, and so on. We summarise this material and suggest some practical implications for teachers. We suggest that a key issue that emerges is the distinction between effective and ineffective novices. What characterises effective novices? Is it possible to identify the specific deficits of ineffective novices and help them to become effective learners of programming? 1.

A study by a ITiCSE 2001 working group ("the McCracken Group") established that many students do not know how to program at the conclusion of their introductory courses. A popular explanation for this incapacity is that the students lack the ability to problem-solve. That is, they lack the ability to take a problem description, decompose it into sub-problems and implement them, then assemble the pieces into a complete solution. An alternative explanation is that many students have a fragile grasp of both basic programming principles and the ability to systematically carry out routine programming tasks, such as tracing (or “desk checking”) through code. This ITiCSE 2004 working group studied the alternative explanation, by testing

Software development and maintenance tasks rely on and can benefit from an increased level of program understanding. Object-oriented programming languages provide features which facilitate software maintenance, yet the same features often make object-oriented programs more difficult to understand. We support the use of program visualization techniques to foster object-oriented program comprehension. This paper identifies ways that visualization can increase program understanding, and presents a means for characterizing both static and dynamic aspects of an object-oriented program. We then describe the implementation of a prototypical tool for visualizing the execution of C++ programs. Based on this work, we define a framework for the visualization of object-oriented software which requires little or no programmer intervention and provides a mechanism which allows users to focus quickly on particular aspects of the program. Keywords: program visualization, program comprehension. 1 In...

We present results of observing professional maintenance engineers working with industrial code at actual maintenance tasks. Protocol analysis is used to explore how code understanding might differ for small versus large scale code. The experiment confirms that cognition processes work at all levels of abstraction simultaneously as programmers build a mental model of the code. Cognition processes emerged at three levels of aggregation representing lower and higher level strategies of understanding. They show differences in what triggers them and how they achieve their goals. Results are useful for defining core competencies which maintenance engineers need for their work and for documentation and development standards. 1 Introduction During maintenance and software evolution, software engineers must understand code they haven't written for a variety of tasks. Existing cognition models [1, 4, 5, 6, 7, 10] emphasize cognition by what the program does (a functional approach) and how th...

Maintenance frequently consumes more resources than new software development. A major portion of the maintenance effort is spent on the reverse engineering activity of understanding existing software. If we can learn more about how programmers understand code successfully, we can build better tools to support the understanding process. This contributes to higher quality and improved efficiency of maintenance tasks. We present an integrated code comprehension model and our experiences with it in an industrial setting. We use audio-taped, think-aloud reports to investigate how well our integrated code comprehension model works during industrial maintenance activities ranging from code fixes to enhancements, code leverage, and reuse. We analyze the tapes for information needs during maintenance activities and derive tool capabilities accordingly. 1 Introduction Maintenance typically requires more resources than new software development. A significant portion of the maintenance effort in...

maintenance of large-scale software

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Classically, humans have been perceived as a source of faults in systems. Modern ergonomic views are promoting a somewhat different idea according to which humans are a factor of safety in unexpected situations. The safety of a system cannot be achieved without taking into account these two sides of cognition which compose what is called cognitive flexibility. In this paper, we will consider the cases of a nuclear accident and a plane crash-landing where human cognitive flexibility has impacted on the final safety of the system. We aim to discuss the violations that humans have performed in these cases with the assumption that they do not always deteriorate system safety. The discussion gravitates around a core argument according to which violations per se do not inform on the safety impairments in a system. Some other dimensions have to be taken into account. Among these, we are of the opinion that the accuracy of the operators’ mental model plays a key role, allowing some violations to improve system safety in emergency situations.

Use Case Modeling is a technique for handling the functional requirements in a software development project. The Use Case Model can serve as a means of communication between the different stakeholders in a project. It is used in planning the project and is updated and used during the project. In order to reduce the possibilities for misunderstandings and differences in understanding, it would be useful to be able to evaluate to what extent the different stakeholders have understood the model and also to detect differences in interpretation. Low comprehension or differences in interpretation may indicate a need for more effort on specifying the requirements. If this is not feasible, it may be necessary to assume a higher risk when planning and estimating the project. We propose using knowledge on how humans understand text from cognitive psychology in the design of an experiment with a twofold goal: Investigate methods for measuring comprehension of Use Case Models and analyze the differences in understanding. Keywords: Understanding, Requirements engineering, Use Case Models, Schema Theory 1.

This study reports results from an empirical study of 54 software maintainers in the software maintenance department of a Norwegian company. The study addresses the relationship between amount of experience and maintenance skills. The findings were, amongst others: (1) While there may have been a reduction in the frequency of major unexpected problems from tasks solved by very inexperienced to medium experienced maintainers, additional years of general software maintenance experience did not lead to further reduction. More application specific experience, however, further reduced the frequency of major unexpected problems. (2) The most experienced maintainers did not predict maintenance problems better than maintainers with little or medium experience. (3) A simple one-variable model outperformed the maintainers' predictions of maintenance problems, i.e., the average prediction performance of the maintainers seems poor. Index terms: Software maintenance, predictions, learning from experience, human judgement. 1