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.

Naming the Pain in Requirements Engineering: A Design for a Global Family of Surveys and First Results from Germany

For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, they still do not allow for empirical generalisations. To lay an empirical and externally valid foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. We designed a globally distributed family of surveys in joint collaborations with different researchers and completed the first run in Germany. The instrument is based on a theory in the form of a set of hypotheses inferred from our experiences and available studies. We test each hypothesis in our theory and identify further candidates to extend the theory by correlation and Grounded Theory analysis. In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from Germany with participants from 58 companies. The results reveal, for example, a tendency to improve RE via internally defined qualitative methods rather than relying on normative approaches like CMMI. We also discovered various RE problems that are statistically significant in practice. For instance, we could corroborate communication flaws or moving targets as problems in practice. Our results are not yet fully representative but already give first insights into current practices and problems in RE, and they allow us to draw lessons learnt for future replications. Our results obtained from this first run in Germany make us confident that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice

Six reasons for rejecting an industrial survey paper

Context: Despite their importance in any empirically based research program, industrial surveys are not very common in the software engineering literature. In our experience, a possible reason is their difficulty of publication. Goal: We would like to understand what are the issues that may prevent the publication of papers reporting industrial surveys. Method: In this preliminary work, we analyzed the surveys we conducted and extracted the main lessons learned in terms of issues and problems. Results: Most common critics posed to industrial surveys are: lack of novelty, limitation of the geographic scope and sampling issues. Conclusions: Most objections that led to reject a survey paper actually are not easy to overcome and others are not so serious. These objections could restrain researchers from conducting this type of studies that represent an important methodological asset. For these reasons, we think that reviewers should be less severe to judge survey papers provided that all the limitations of the study are well explained and highlighte

On Modeling and Analyzing Cost Factors in Information Systems Engineering

Introducing enterprise information systems (EIS) is usually associated with high costs. It is therefore crucial to understand those factors that determine or influence these costs. Though software cost estimation has received considerable attention during the last decades, it is difficult to apply existing approaches to EIS. This difficulty particularly stems from the inability of these methods to deal with the dynamic interactions of the many technological, organizational and projectdriven cost factors which specifically arise in the context of EIS. Picking up this problem, we introduce the EcoPOST framework to investigate the complex cost structures of EIS engineering projects through qualitative cost evaluation models. This paper extends previously described concepts and introduces design rules and guidelines for cost evaluation models in order to enhance the development of meaningful and useful EcoPOST cost evaluation models. A case study illustrates the benefits of our approach. Most important, our EcoPOST framework is an important tool supporting EIS engineers in gaining a better understanding of the critical factors determining the costs of EIS engineering projects

Teaching psychology to computing students

The aim of this paper is twofold. The first aim is to discuss some observations gained from teaching Psychology to Computing students, highlighting both the wide range of areas where Psychology is relevant to Computing education and the topics that are relevant at different stages of students’ education. The second aim is to consider findings from research investigating the characteristics of Computing and Psychology students. It is proposed that this information could be considered in the design and use of Psychology materials for Computing students. The format for the paper is as follows. Section one will illustrate the many links between the disciplines of Psychology & Computing; highlighting these links helps to answer the question that many Computing students ask, what can Psychology offer to Computing? Section two will then review some of the ways that I have been involved in teaching Psychology to Computing students, from A/AS level to undergraduate and postgraduate level. Section three will compare the profiles of Computing and Psychology students (e.g. on age, gender and motivation to study), to highlight how an understanding of these factors can be used to adapt Psychology teaching materials for Computing students. The conclusions which cover some practical suggestions are presented in section four

Case Studies in Industry: What We Have Learnt

Case study research has become an important research methodology for exploring phenomena in their natural contexts. Case studies have earned a distinct role in the empirical analysis of software engineering phenomena which are difficult to capture in isolation. Such phenomena often appear in the context of methods and development processes for which it is difficult to run large, controlled experiments as they usually have to reduce the scale in several respects and, hence, are detached from the reality of industrial software development. The other side of the medal is that the realistic socio-economic environments where we conduct case studies -- with real-life cases and realistic conditions -- also pose a plethora of practical challenges to planning and conducting case studies. In this experience report, we discuss such practical challenges and the lessons we learnt in conducting case studies in industry. Our goal is to help especially inexperienced researchers facing their first case studies in industry by increasing their awareness for typical obstacles they might face and practical ways to deal with those obstacles.Comment: Proceedings of the 4th International Workshop on Conducting Empirical Studies in Industry, co-located with ICSE, 201

On Evidence-based Risk Management in Requirements Engineering

Background: The sensitivity of Requirements Engineering (RE) to the context makes it difficult to efficiently control problems therein, thus, hampering an effective risk management devoted to allow for early corrective or even preventive measures. Problem: There is still little empirical knowledge about context-specific RE phenomena which would be necessary for an effective context- sensitive risk management in RE. Goal: We propose and validate an evidence-based approach to assess risks in RE using cross-company data about problems, causes and effects. Research Method: We use survey data from 228 companies and build a probabilistic network that supports the forecast of context-specific RE phenomena. We implement this approach using spreadsheets to support a light-weight risk assessment. Results: Our results from an initial validation in 6 companies strengthen our confidence that the approach increases the awareness for individual risk factors in RE, and the feedback further allows for disseminating our approach into practice.Comment: 20 pages, submitted to 10th Software Quality Days conference, 201