The book is an introduction to the idea of design patterns in software engineering, and a catalog of twenty-three common patterns. The nice thing is, most experienced OOP designers will find out they've known about patterns all along. It's just that they've never considered them as such, or tried to centralize the idea behind a given pattern so that it will be easily reusable.

Design Patterns: Elements of Reusable Object-Oriented Software

The purpose of this article is to review basic empirical results from the psychological literature in a way that provides a useful foundation for research on consumer knowledge. A conceptual organization for this diverse literature is provided by two fundamental distinctions. First, consumer expertise is distinguished from product-related experience. Second, five distinct aspects, or dimensions, of expertise are identified: cognitive effort, cognitive structure, analysis, elaboration, and memory. Improvements in the first two dimensions are shown to have general beneficial effects on the latter three. Analysis, elaboration, and memory are shown to have more specific interrelationships. The empirical findings related to each dimension are reviewed and, on the basis of those findings, specific research hypotheses about the effects of expertise on consumer behavior are suggested.

Dimensions of Consumer Expertise

The problems of designing large software systems were studied through interviewing personnel from 17 large projects. A layered behavioral model is used to analyze how three of these problems—the thin spread of application domain knowledge, fluctuating and conflicting requirements, and communication bottlenecks and breakdowns—affected software productivity and quality through their impact on cognitive, social, and organizational processes.

http://www.cs.rug.nl/search/uploads/Teaching/RE2009Fall/paper/1988_Curtis_ACMC_A%20Field%20Study%20of%20the%20Software%20Design%20Process%20for%20Large%20Systems.pdf

A field study of the software design process for large systems

Motivated by the properties of spreading activation and conceptual distance, the authors propose a metric, called distance, on the power set of nodes in a semantic net. Distance is the average minimum path length over all pairwise combinations of nodes between two subsets of nodes. Distance can be successfully used to assess the conceptual distance between sets of concepts when used on a semantic net of hierarchical relations. When other kinds of relationships, like 'cause', are used, distance must be amended but then can again be effective. The judgements of distance significantly correlate with the distance judgements that people make and help to determine whether one semantic net is better or worse than another. The authors focus on the mathematical characteristics of distance that presents novel cases and interpretations. Experiments in which distance is applied to pairs of concepts and to sets of concepts in a hierarchical knowledge base show the power of hierarchical relations in representing information about the conceptual distance between concepts. >

Development and application of a metric on semantic nets

▪ Abstract Expert and exceptional performance are shown to be mediated by cognitive and perceptual-motor skills and by domain-specific physiological and anatomical adaptations. The highest levels of human performance in different domains can only be attained after around ten years of extended, daily amounts of deliberate practice activities. Laboratory analyses of expert performance in many domains such as chess, medicine, auditing, computer programming, bridge, physics, sports, typing, juggling, dance, and music reveal maximal adaptations of experts to domain-specific constraints. For example, acquired anticipatory skills circumvent general limits on reaction time, and distinctive memory skills allow a domain-specific expansion of working memory capacity to support planning, reasoning, and evaluation. Many of the mechanisms of superior expert performance serve the dual purpose of mediating experts' current performance and of allowing continued improvement of this performance in response to informative fe...

Expert and exceptional performance: evidence of maximal adaptation to task constraints.

A detailed look at the representations constructed by novice and expert computer programmers is presented. The issue is addressed by looking at the interaction between the representation naturally formed by programmers at each level of expertise and .an experimentally induced abstract or concrete "mental set." The data suggest that, in the absence of an experimentally provided set, experts form abstract representations (denned here as what a program does), whereas novices form concrete representations (defined here as how a program functions). The data also suggest that appropriate sets can aid each group to form the representation not natural to them; however, these representations are not as stable as the preferred ones. The generality of the findings and the utility of the experts' representation of a task is discussed both in relation to computer programming and to problem solving in other domains. In the semantically rich domains of skilled problem solving (Bhaskar & Simon, 1977), the difference between experts and nonexperts is both qualitative and quantitative. Not only do experts perform better than novices on quantitative measures of skill but experimental manipulations also uncover qualitative differ- ences in the representations and strategies used by experts. Repeatedly, we find that the work- ing representations of experts are abstract conceptualizations of the original problem statement, whereas those of novices are less abstract and focus more on surface features of the problem. For example, in a recent ex- periment, Adelson (1981c) found that expert programmers used abstract, conceptually based representations when attempting to re- call programming material, whereas novices used syntactically based representations. Using a multitrial free-recall procedure, Adelson asked novice and expert programmers to recall a set of 16 lines of programming code that had been presented in random order. Although the subjects had not been told that the 16 lines

When Novices Surpass Experts: The Difficulty of a Task May Increase With Expertise

The question of how novice and expert computer programmers represent and use programming concepts is addressed here. Lines of programming code forming three complete programs were presented one at a time and in random order in a multitrial free recall procedure. Qualitative and quantitative measures revealed clear but different subjective organization in the two groups. The novices used a syntax-based organization, whereas the experts used a more abstract hierarchical organization based on principles of program function.

/pdf/problem-solving-and-the-development-of-abstract-categories-4cywc9hj6m.pdf

Problem solving and the development of abstract categories in programming languages

A designer's expertise rests on the knowledge and skills which develop with experience in a domain. As a result, when a designer is designing an object in an unfamiliar domain he will not have the same knowledge and skills available to him as when he is designing an object in a familiar domain. In this paper we look at the software designer's underlying constellation of knowledge and skills, and at the way in which this constellation is dependent upon experience in a domain. What skills drop out, what skills, or interactions of skills come forward as experience with the domain changes? To answer the above question, we studied expert designers in experimentally created design contexts with which they were differentially familiar. In this paper we describe the knowledge and skills we found were central to each of the above contexts and discuss the functional utility of each. In addition to discussing the knowledge and skills we observed in expert designers, we will also compare novice and expert behavior.

The Role of Domain Expenence in Software Design

Knowledge and processes in the comprehension of computer programs.

In this article we present a preliminary cognitive model of the process of software design. Our goal was to develop a model of expert problem-solving skills for a task in which domain knowledge played an extensive role. In our model the process of design is captured via goals-and-operators interacting with a knowledge base. We have defined the goals and operators as ones which are general to design, rather than specific to the current task. In addition, we have structured the atomic level operators so that they are able to access domain specific knowledge acquired through experience. This structure enables both general processes and domain specific knowledge to play critical roles in producing any particular design artifact. From our protocol analysis we have built a model which unites several recurring behaviors into an interpretable whole. the behaviors we account for include the building of mental models, mental simulation, and balanced development.

Beth Adelson

Papers

When Novices Surpass Experts: The Difficulty of a Task May Increase With Expertise

Problem solving and the development of abstract categories in programming languages

The Role of Domain Expenence in Software Design

Knowledge and processes in the comprehension of computer programs.

A model of software design