Stella Pachidi

Understanding users' behavior with software operation data mining

Software usage concerns knowledge about how end-users use the software in the field, and how the software itself responds to their actions. In this paper, we present the Usage Mining Method to guide the analysis of data collected during software operation, in order to extract knowledge about how a software product is used by the end-users. Our method suggests three analysis tasks which employ data mining techniques for extracting usage knowledge from software operation data: users profiling, clickstream analysis and classification analysis. The Usage Mining Method was evaluated through a prototype that was executed in the case of Exact Online, the main online financial management application in the Netherlands. The evaluation confirmed the supportive role of the Usage Mining Method in software product management and development processes, as well as the applicability of the suggested data mining algorithms to carry out the usage analysis tasks.

Functional architecture modeling for the software product industry

Although a lot of research has been carried out on the technical architecture of software systems, the domain of Functional Architecture in the software product industry lacks a formalization of the related concepts and practices. Functional Architecture Modeling is essential for identifying the functionalities of the software product and translating them into modules, which interact with each other or with third party products. Furthermore, the Functional Architecture serves as a base for mapping the functional requirements and planning the product releases. In this paper, we present the Functional Architecture Diagrams, a powerful modeling tool for the Functional Architecture of software products, which comprises: a modular decomposition of the product functionality; a simple notation for easy comprehension by non-specialists; and applicability in any line of business, offering a uniform method for modeling the functionalities of software products.

Working and organizing in the age of the learning algorithm

Abstract Learning algorithms, technologies that generate responses, classifications, or dynamic predictions that resemble those of a knowledge worker, raise important research questions for organizational scholars related to work and organizing. We suggest that such algorithms are distinguished by four consequential aspects: black-boxed performance, comprehensive digitization, anticipatory quantification, and hidden politics. These aspects are likely to alter work and organizing in qualitatively different ways beyond simply signaling an acceleration of long-term technology trends. Our analysis indicates that learning algorithms will transform expertise in organizations, reshape work and occupational boundaries, and offer novel forms of coordination and control. Thus, learning algorithms can be considered performative due to the extent to which their use can shape and alter work and organizational realities. Their rapid deployment requires scholarly attention to societal issues such as the extent to which the algorithm is authorized to make decisions, the need to incorporate morality in the technology, and their digital iron-cage potential.

The Performance Mining Method: Extracting Performance Knowledge from Software Operation Data

Software Performance is a critical aspect for all software products. In terms of Software Operation Knowledge, it concerns knowledge about the software products performance when it is used by the end-users. In this paper the authors suggest data mining techniques that can be used to analyze software operation data in order to extract knowledge about the performance of a software product when it operates in the field. Focusing on Software-as-a-Service applications, the authors present the Performance Mining Method to guide the process of performance monitoring in terms of device demands and responsiveness and analysis finding the causes of the identified performance anomalies. The method has been evaluated through a prototype which was implemented for an online financial management application in the Netherlands.