Personal recommendations in requirements engineering : the OpenReq approach

[Context & motivation] Requirements Engineering (RE) is considered as one of the most critical phases in software development but still many challenges remain open. [Problem] There is a growing trend of applying recommender systems to solve open RE challenges like requirements and stakeholder discovery; however, the existent proposals focus on specific RE tasks and do not give a general coverage for the RE process. [Principal ideas/results] In this research preview, we present the OpenReq approach to the development of intelligent recommendation and decision technologies that support different phases of RE in software projects. Specifically, we present the OpenReq part for personal recommendations for stakeholders. [Contribution] OpenReq aim is to improve and speed up RE processes, especially in large and distributed systemsPeer ReviewedPostprint (author's final draft

On Integrating Student Empirical Software Engineering Studies with Research and Teaching Goals

Background: Many empirical software engineering studies use students as subjects and are conducted as part of university courses. Aim: We aim at reporting our experiences with using guidelines for integrating empirical studies with our research and teaching goals. Method: We document our experience from conducting three studies with graduate students in two software architecture courses. Results: Our results show some problems that we faced when following the guidelines and deviations we made from the original guidelines. Conclusions: Based on our results we propose recommendations for empirical software engineering studies that are integrated in university courses.

Lessons Learned from Development of a Software Tool to Support Academic Advising

We detail some lessons learned while designing and testing a decision-theoretic advising support tool for undergraduates at a large state university. Between 2009 and 2011 we conducted two surveys of over 500 students in multiple majors and colleges. These surveys asked students detailed questions about their preferences concerning course selection, advising, and career paths. We present data from this study which may be helpful for faculty and staff who advise undergraduate students. We find that advising support software tools can augment the student-advisor relationship, particularly in terms of course planning, but cannot and should not replace in-person advising.Comment: 5 Figures, revised version including more figures and cross-referencin

Software Engineers' Information Seeking Behavior in Change Impact Analysis - An Interview Study

Software engineers working in large projects must navigate complex information landscapes. Change Impact Analysis (CIA) is a task that relies on engineers' successful information seeking in databases storing, e.g., source code, requirements, design descriptions, and test case specifications. Several previous approaches to support information seeking are task-specific, thus understanding engineers' seeking behavior in specific tasks is fundamental. We present an industrial case study on how engineers seek information in CIA, with a particular focus on traceability and development artifacts that are not source code. We show that engineers have different information seeking behavior, and that some do not consider traceability particularly useful when conducting CIA. Furthermore, we observe a tendency for engineers to prefer less rigid types of support rather than formal approaches, i.e., engineers value support that allows flexibility in how to practically conduct CIA. Finally, due to diverse information seeking behavior, we argue that future CIA support should embrace individual preferences to identify change impact by empowering several seeking alternatives, including searching, browsing, and tracing.Comment: Accepted for publication in the proceedings of the 25th International Conference on Program Comprehensio

Generic system architecture for context-aware, distributed recommendation

In the existing literature on recommender systems, it is difficult to find an architecture for large-scale implementation. Often, the architectures proposed in papers are specific to an algorithm implementation or a domain. Thus, there is no clear architectural starting point for a new recommender system. This paper presents an architecture blueprint for a context-aware recommender system that provides scalability, availability, and security for its users. The architecture also contributes the dynamic ability to switch between single-device (offline), client-server (online), and fully distributed implementations. From this blueprint, a new recommender system could be built with minimal design and implementation effort regardless of the application.Electrical and Computer Engineerin