ABSTRACT This paper presents our research experiences studying process knowledge with qualitative and quantitative methods. Informed by related arguments, we present two hypotheses that are tested using a between subjects experimental design. The first hypothesis concerns the accuracy of software process elicitation, which we characterize as the human perception of error between description and performance of a process. The second hypothesis explores the detection of subtle differences in process articulation using latent semantic analysis, a computational technique for measuring patterns in written discourse. The results of our analyses are compared along with discussion of theoretical implications. We define a new type of process property, Coherence, which represents a measure of relatedness in process knowledge. Results also indicate that Coherence may be increased with the use of a conceptual model. Future research is guided by experimental and industrial application. Copyright © 2012 John Wiley & Sons, Ltd.

Process models are often the basis for demonstrating compliance and recommending improvement in software engineering organizations. A descriptive model is a type of process model describing the human activities in software development that actually occur. The purpose of a descriptive model is to provide a baseline for further process improvement and analysis. Ideally, a descriptive model provides an explicit representation. However, if the descriptive model does not represent how a process is actually performed, subsequent recommendations for improvement may be based upon information that is depicted in the model but that does not actually take place. Similarly, a descriptive model may omit important information that is centrally relevant for an organization's process improvement goals. The accuracy of software process elicitation is an important measure and is the degree a descriptive model reflects an actual process in the real world. This study, informed by a synthesis of arguments from related literature, characterizes the accuracy of software process elicitation as the perception of error for a descriptive model. We collected data from 48 users in professional training settings using a between subjects design. The results suggest that users in the treatment group perceived significantly higher error.

With the retail electronic commerce being a major global shopping phenomenon, retailers need to develop additional tools to improve their sales. One such tool is a recommender system through which the shopping page recommends products to the shoppers using their past Web shopping and product search behaviour. While recommender systems are common, few studies exist regarding their usability and user preferences. In this study, a structured survey concerning what recommender systems should contain and how this content should be presented was administered on 131 college-aged online shoppers. Results indicate participants prefer specific recommender content. Price, image and names of products are identified as essential information, while product promotions, customer ratings and feedback are identified as secondary types of information. Shoppers preferred short and relevant recommender information, with a maximum of three recommendations on one page. Future studies may explore differences in preference of recommender systems based on different product types.

This paper presents the results of exploratory research that investigated how people describe software processes in natural language. We conducted a small field study with four participants working at an IT help desk. We elicited and documented a trouble ticketing process using a template under conditions similar to that of many process improvement initiatives. This study included two treatments. In the first treatment, the process engineer elicited information and documented the process. In the second treatment, the participants used the template to document the process on their own. The resulting data, including the process representations, observation field notes, and interview transcripts, were analyzed using a grounded theory approach. The results suggest that there are distinct ways in which process users describe process. We construct a theory that posits that descriptions of process are dependent upon perspectives shaped by the elicitation and process context. Future research will focus on the evaluation of this theory relative to other elicitation approaches and contexts.

Despite their popularity, usability studies concerning Tablet PCs are lacking. This study aimed at determining user satisfaction and preference aspects of Tablet PCs in comparison to laptop PCs and pen-and-paper environments. Several common computer tasks were examined in an experimental environment on 34 college student participants. User satisfaction and preferences were measured by comprehensive questionnaires. An analysis of variance was used for the empirical comparisons. Participants did not have any difficulty in reading, direct manipulation, and form filling tasks. There was a perception of a high number of errors by the participants for the writing task in Tablet PCs. Overall, participants found the general computing capabilities and portability of Tablet PCs impressive. However, the majority did not prefer Tablet PCs to laptop PCs to meet their everyday computing needs. Results can help designers improve the overall usability of the Tablet PC and help its development as a major computing medium.

Novice users frequently make errors when learning a new computer task and spend a large portion of their time trying to recover from errors. Three methods for helping novice users respond to errors have been presented in the literature: error management training, exploratory training, and conceptual models. In error management training, errors are presented as opportunities for learning, and users are instructed in strategies for coping with errors. In exploration, users are given an overview of their environment and are taught how to navigate through their task environment. Conceptual models are graphical or mathematical representations of a system that correspond closely to the real-world system. This experiment tested the effectiveness of these different approaches on training novice users to use the Internet. In this experiment, users received 3 hr of training on the World Wide Web and then were asked to perform a set of information retrieval tasks. Performance was measured in two ways: task performance and performance time. Participants who received exploratory training had significantly higher task performance. Participants who received exploration and conceptual models, both individually and together, were able to complete the tasks in less time. Error management had no significant effect on the performance of participants. In the task application of Web browsing, exploration seems to be the most appropriate training method for novice users.

This article presents a neural network approach for user modeling. A set of neural networks is utilized to represent and infer users' task-related characteristics. These networks function as associative memories that can capture the causal relations among users' characteristics for the system adaptation. It is suggested that this approach can be expected to overcome some inherent problems of the conventional stereotyping approaches in terms of pattern recognition and classification of user characteristics.

An analysis is presented of early design and code change data from the software cost reduction (SCR) project, a well-reported effort conducted at the US Naval Research Laboratory from 1978 to 1988. The analyses are mostly time-based studies of the change data and relationships between the data and SCR personnel activity data. Some analyses of the change data show patterns consistent with a major goal of the SCR project: the design and development of easy-to-change software. Specifically, most changes took a day or less to uncover and resolve; the majority of changes updated at most one module. Moreover, these percentages remained fairly stable. No positive relationship appeared between error-correction effort and the number of days that an error remained in the SCR design documentation. Other analyses suggest that consistency may have been temporary. For example, the analyses suggest a stepwise growth in average change effort, and an increasing percentage of changes resulted in module interface updates. Certain specific ratios between SCR change data and personnel activity data may be possible indicators of design incompleteness.>

A conceptual research framework is presented for studying and designing adaptive human-computer interfaces that modify themselves dynamically with respect to the current user and the current context. This framework is based on the software engineering principle for constructing an abstract specification that incorporates all the necessary information about the entity. The goal of this approach is to implement an abstract interface that is composed of an abstract user, an abstract system, and an abstract application. The paper concerns the design of the abstract user. The abstract user is seen as an interaction between a static production model of the goals necessary to accomplish a specific task and a dynamic production model of a user's goal hierarchy for accomplishing that task. This framework suggests that the task model necessarily follows from the specifics of the task domain. Further, the user's goal model must be constructed by monitoring the user's actions, deducing the goals, and comparing the user's goal hierarchy with the set of goals that the task model requires.>

The authors present a survey of recent research in adaptive interface computer software as well as a discussion of factors that require consideration in designing this software. An adaptive interface needs to include a knowledge base that encompasses four domains. These four domains are knowledge of the current user, knowledge of the interaction scheme, knowledge of the problem task, and knowledge of the underlying system. The authors review and discuss these knowledge bases along with the positive and negative aspects of adaptive interfaces.>

Abstract Human memory organization has been shown to be important in the processing of natural language. Evidence is provided in this investigation which suggests that human memory organization is also important in processing programming languages. Subjects were divided into experimental groups which studied programs with or without documentation, and with or without hierarchically indented statements. Subjects studied and recalled five Fortran programs. The pattern of recalled statements at logic segment boundaries was compared to the recalled pattern within segments. In addition, the recalled boundary patterns of the experimental groups were compared to each other. The results indicate that algorithmic logic segments form a cognitive organizational structure in human memory for computer programs. Statement indentation and internal program documentation did not apparently enhance the organizational process or the recall of programming statements.

Recent investigations into the psychological factors underlying computer programming have focused on the effects of internal documentation and statement indentation on programmer performance [1, 5, 7]. Using memory recall approaches several studies have concentrated on the relationship between logic segments of a program's algorithm and the memory organization of the programmer.