Florian Reinfrank

Group decision support for requirements negotiation

Requirements engineering is one of the most critical phases in software development. Requirements verbalize decision alternatives that are negotiated by stakeholders. In this paper we present the results of an empirical analysis of the effects of applying group recommendation technologies to requirements negotiation. This analysis has been conducted within the scope of software development projects at our university where development teams were supported with group recommendation technologies when deciding which requirements should be implemented. A major result of the study is that group recommendation technologies can improve the perceived usability (in certain cases) and the perceived quality of decision support. Furthermore, it is not recommended to disclose preferences of individual group members at the beginning of a decision process --- this could lead to an insufficient exchange of decision-relevant information.

Toward the Next Generation of Recommender Systems: Applications and Research Challenges

Recommender systems are assisting users in the process of identifying items that fulfill their wishes and needs. These systems are successfully applied in different e-commerce settings, for example, to the recommendation of news, movies, music, books, and digital cameras. The major goal of this book chapter is to discuss new and upcoming applications of recommendation technologies and to provide an outlook on major characteristics of future technological developments. Based on a literature analysis, we discuss new and upcoming applications in domains such as software engineering, data and knowledge engineering, configurable items, and persuasive technologies. Thereafter we sketch major properties of the next generation of recommendation technologies.

Basic Approaches in Recommendation Systems

Recommendation systems support users in finding items of interest. In this chapter, we introduce the basic approaches of collaborative filtering, content-based filtering, and knowledge-based recommendation. We first discuss principles of the underlying algorithms based on a running example. Thereafter, we provide an overview of hybrid recommendation approaches which combine basic variants. We conclude this chapter with a discussion of newer algorithmic trends, especially critiquing-based and group recommendation.

Automated Analysis in Feature Modelling and Product Configuration

The automated analysis of feature models is one of the thriving topics of research in the software product line and variability management communities that has attracted more attention in the last years. A recent literature review reported that more than 30 analysis operations have been identified and different analysis mechanisms have been proposed. Product configuration is a well established research field with more than 30 years of successful applications in different industrial domains. Our hypothesis, that is not really new, is that these two independent areas of research have interesting synergies that have not been fully explored. To try to explore the potential synergies systematically, in this paper we provide a rapid review to bring together these previously disparate streams of work. We define a set of research questions and give a preliminary answer to some of them. We conclude that there are many research opportunities in the synergy of these independent areas.

An Overview of Recommender Systems in Requirements Engineering

Requirements engineering (RE) is considered as one of the most critical phases in software development. Poorly implemented RE processes are still one of the major risks for project failure. As a consequence, we can observe an increasing demand for intelligent software components that support stakeholders in the completion of RE tasks. In this chapter, we give an overview of the research dedicated to the application of recommendation technologies in RE. On the basis of a literature analysis, we exemplify the application of recommendation technologies in different scenarios. In this context, the approaches of collaborative filtering, content-based filtering, clustering, knowledge-based recommendation, group-based recommendation, and social network analysis are discussed. With the goal to stimulate further related research, we conclude the chapter with a discussion of issues for future work.

Automated repair of scoring rules in constraint-based recommender systems

Constraint-based recommender systems support customers in preference construction processes related to complex products and services. In this context, utility constraints scoring rules play an important role. They determine the order in which items products and services are presented to customers. In many cases utility constraints are faulty, i.e., calculate rankings which are not expected and accepted by marketing and sales experts. The adaptation of these constraints is extremely time-consuming and often an error-prone process. We present an approach to the automated adaptation of utility constraint sets which is based on solutions for nonlinear optimization problems. This approach increases the applicability of constraint-based recommendation technologies by allowing the automated reproduction of example item rankings specified by marketing and sales experts.

ReComment: towards critiquing-based recommendation with speech interaction

In contrast to search-based approaches, critiquing-based recommender systems provide a navigation-based interface where users are enabled to critique displayed recommendations as a means of preference elicitation. In this paper we present Recomment, our approach to natural language based unit critiquing. We discuss the developed prototype and present the corresponding user interface. In order to show the applicability of our concepts, we present the results of a user study. This study shows that speech interfaces have the potential to improve the perceived ease of use as well as the overall quality of recommendations.

User Interfaces for Configuration Environments

Configuration technologies are successfully applied in different domains such as telecommunication, financial services, and automotive. User interfaces of configuration environments play a key role with regard to two major aspects. First, users of a configurator application need interfaces that allow for efficient and intuitive configuration processes. Second, knowledge engineers and domain experts (developers of configurator applications) need interfaces that provide intelligent support of development and maintenance operations. In this chapter we discuss aspects that should be taken into account when developing user interfaces for configurator end users and application developers.

WE-DECIDE: a decision support environment for groups of users

Group recommendation technologies are becoming increasingly popular for supporting group decision processes in various domains such as interactive television, music, and tourist destinations. Existing group recommendation environments are focusing on specific domains and do not include the possibility of supporting different kinds of decision scenarios. The We-Decide group decision support environment advances the state of the art by supporting different decision scenarios in a domain-independent fashion. In this paper we give an overview of the We-Decide environment and report the results of a first user study which focused on system usability and potentials for further applications.

Conflict Detection and Diagnosis in Configuration

The widespread industrial application of configuration technologies triggers an increasing demand for intelligent techniques that efficiently support anomaly management operations for configuration knowledge bases. Examples of such operations are the testing and debugging of faulty knowledge bases (see Chapter 11) and the detection of redundancies in configuration knowledge bases (see Chapter 12). The goal of this chapter is to discuss techniques and algorithms that form the technological basis for the aforementioned anomaly management operations.