Ethically Aligned Design: An empirical evaluation of the RESOLVEDD-strategy in Software and Systems development context

Use of artificial intelligence (AI) in human contexts calls for ethical considerations for the design and development of AI-based systems. However, little knowledge currently exists on how to provide useful and tangible tools that could help software developers and designers implement ethical considerations into practice. In this paper, we empirically evaluate a method that enables ethically aligned design in a decision-making process. Though this method, titled the RESOLVEDD-strategy, originates from the field of business ethics, it is being applied in other fields as well. We tested the RESOLVEDD-strategy in a multiple case study of five student projects where the use of ethical tools was given as one of the design requirements. A key finding from the study indicates that simply the presence of an ethical tool has an effect on ethical consideration, creating more responsibility even in instances where the use of the tool is not intrinsically motivated.Comment: This is the author's version of the work. The copyright holder's version can be found at https://doi.org/10.1109/SEAA.2019.0001

How Advanced Change Patterns Impact the Process of Process Modeling

Process model quality has been an area of considerable research efforts. In this context, correctness-by-construction as enabled by change patterns provides promising perspectives. While the process of process modeling (PPM) based on change primitives has been thoroughly investigated, only little is known about the PPM based on change patterns. In particular, it is unclear what set of change patterns should be provided and how the available change pattern set impacts the PPM. To obtain a better understanding of the latter as well as the (subjective) perceptions of process modelers, the arising challenges, and the pros and cons of different change pattern sets we conduct a controlled experiment. Our results indicate that process modelers face similar challenges irrespective of the used change pattern set (core pattern set versus extended pattern set, which adds two advanced change patterns to the core patterns set). An extended change pattern set, however, is perceived as more difficult to use, yielding a higher mental effort. Moreover, our results indicate that more advanced patterns were only used to a limited extent and frequently applied incorrectly, thus, lowering the potential benefits of an extended pattern set

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.

On The Impact of Passive Voice Requirements on Domain Modelling

Context: The requirements specification is a central arte- fact in the software engineering (SE) process, and its quality (might) influence downstream activities like implementation or testing. One quality defect that is often mentioned in standards is the use of passive voice. However, the con- sequences of this defect are still unclear. Goal: We need to understand whether the use of passive voice in requirements has an influence on other activities in SE. In this work we focus on domain modelling. Method: We designed an experiment, in which we ask students to draw a domain model from a given set of requirements written in active or passive voice. We compared the completeness of the resulting domain model by counting the number of missing actors, domain objects and their associations with respect to a specified solution. Results: While we could not see a difference in the number of missing actors and objects, participants which received passive sentences missed almost twice the associations. Conclusion: Our experiment indicates that, against common knowledge, actors and objects in a requirement can often be understood from the context. However, the study also shows that passive sentences complicate understanding how certain domain concepts are interconnected

Translating Business Process Models to Class Diagrams

Choreography of business processes can track messages between different services. At the time of writing, there are no guidelines t o d raw a U ML C lass D iagram f rom t he Business Process Choreography. This paper reports an experiment using a set of guidelines. Objective: Evaluate the subjects’ performance and perceptions when applying the BPc2Class-guidelines and BPc2Class-discovery process. Method: To measure the performance and user perception of both ways of mapping the processes, a comparative experiment was conducted with 38 subjects. The subjects, being master students, solved a process case in the first session and a guidelines case in the second session. A survey was filled in by the subjects to measure the user perception variables. Results: The results indicated that the guidelines showed significantly better results in five out of the six measured variables. Conclusion: Based on the findings and limitations of this research the use of guidelines looks promising, but future research is necessary to further generalize the conclusion

Myth Buster: Do Engineers Trust Parametric Models Over Their Own Intuition?

This paper explores the abilities of engineers to estimate everyday tasks and their reliance on their own intuition when performing cost estimates. The approach to answering these questions is similar to that of the popular television show MythBusters which aims to separate truth from urban legend using controlled experiments. In MythBusters, methods for testing myths and urban legends are usually planned and executed in a manner to produce the most visually dramatic results possible, which generally involves explosions, fires, or vehicle crashes. While the question of parametric models versus intuition is not as exciting, we provide an interesting result that demonstrates the difference between what is real and what is fiction in the world of cost estimation. Two heuristics, representativeness and anchoring, are explored in two experiments involving psychology students, engineering students, and engineering practitioners. The first experiment, designed to determine if there is a difference in estimating ability in everyday quantities, demonstrates that the three groups estimate with relatively equal accuracy. The results shed light on the distribution of estimates and the process of subjective judgment. The second experiment, designed to explore abilities for estimating the cost of software-intensive systems given incomplete information, shows that predictions by engineering students and practitioners are within 3-12% of each other. Results also show that engineers rely more on their intuition than on parametric models to make decisions. The value of this work is in helping better understand how software engineers make decisions based on limited information. Implications for the development of software cost estimation models are discussed in light of the findings from the two experiments

Happy software developers solve problems better: psychological measurements in empirical software engineering

For more than 30 years, it has been claimed that a way to improve software developers' productivity and software quality is to focus on people and to provide incentives to make developers satisfied and happy. This claim has rarely been verified in software engineering research, which faces an additional challenge in comparison to more traditional engineering fields: software development is an intellectual activity and is dominated by often-neglected human aspects. Among the skills required for software development, developers must possess high analytical problem-solving skills and creativity for the software construction process. According to psychology research, affects-emotions and moods-deeply influence the cognitive processing abilities and performance of workers, including creativity and analytical problem solving. Nonetheless, little research has investigated the correlation between the affective states, creativity, and analytical problem-solving performance of programmers. This article echoes the call to employ psychological measurements in software engineering research. We report a study with 42 participants to investigate the relationship between the affective states, creativity, and analytical problem-solving skills of software developers. The results offer support for the claim that happy developers are indeed better problem solvers in terms of their analytical abilities. The following contributions are made by this study: (1) providing a better understanding of the impact of affective states on the creativity and analytical problem-solving capacities of developers, (2) introducing and validating psychological measurements, theories, and concepts of affective states, creativity, and analytical-problem-solving skills in empirical software engineering, and (3) raising the need for studying the human factors of software engineering by employing a multidisciplinary viewpoint.Comment: 33 pages, 11 figures, published at Peer