To this end, 66 primary studies were analyzed to provide an overview of what has been discussed in the area by analyzing four research questions. Descriptive validity in qualitative research is the “factual accuracy” of the reported data 60. It is not concerned with any interpretation of the data, only whether it is accurately represented in the account. 61. That is, in contrast to descriptive validity, the interpretation of data is a central concern. As a last threat to theoretical validity, the theoretical constructs we used in our study might not have been defined well enough to ensure similar understanding among all researchers. Furthermore, we described the case study design and process in detail in Section 3, to allow readers to assess the validity in more depth. The reported GSE challenges by the participants of Case 2 are in line with the challenges reported in GSE literature and practice. Furthermore, developers might have forgotten to report some of the challenges that they experienced during the design session. Different developers might perceive different challenges to their GSE experience. To mitigate this issue, we additionally tried to triangulate the reported challenges with those observed during the distributed design sessions. Having the option to clarify would have either solved the issue, or given the team enough information to continue discussions, potentially leading to “true” creative events. Post h as been created with G SA Conte nt Gen erator Dem over sion !
This could have affected our comparison of the design thinking. We collected data on challenges to distributed design thinking by asking the distributed developers to report their perceived challenges during the design sessions. These challenges are subjective. However, we cannot guarantee that other developers would report the same challenges. Some of the studies, however, do not make it clear in their methodology which methods or evaluation criteria are used. Similarly, the lessons learned are organized by distinguishing them with respect to the requirement (RLL), development (DLL), and evaluation (ELL) phases. Agile methodologies, such as the Dynamic Software Development Method stapleton2003dsdm , Extreme Programming beck2000extreme , Crystal cockburn2004crystal , Feature-driven development palmer2001practical , Kanban anderson2010kanban or Scrum schwaber2016scrum , have emerged to deal with the increasing complexity in software engineering and to handle the inevitable changes in requirements throughout their life-cycle jiang2009analysis . Mirkovic and Peterson investigate an adapted CTF method which they propose to enhance cybersecurity education for students. All events that purely relate to the problem space are events in which a participant reads a requirement and realizes that a concept/a requirement is missing in the solution, e.g.,: “Here it says: Students must … This article was done by GSA Conte nt Generator Dem oversion.
So it’s stated that it is related to the intersection, not to the road.” There is no evident correlation between the number of creative events and the proportions of problem and solution space exploration. To reduce threats to interpretive validity, we employed a number of measures. In the following, we will describe potential threats to validity and how we addressed them in our study. This enables researchers to replicate our study. First, we relied on two established theoretical concepts: the design thinking concept 3 and that of convergent/divergent thinking 55. For coding the data, we used written guidelines such as the coding guidelines presented in Appendix A. Multiple researchers then applied these guidelines to the same data, and discussed differences. To obtain the ground truth, we conducted an in-depth manual exploratory analysis of email messages (spanning multiple mailing lists) relating to all PEPs that reached either the accepted (152 PEPs) or rejected (96 PEPs) states. The identification of categories of events done in this work as well as the analysis of topic popularity is a first step towards the accomplishment of the bigger goal of understanding the mechanisms by which software development communities thrive in offline and online settings and share information with one another. In multi-tenant environments, recommendation may be based on the anonymized information collected from other users using a particular tool.
Currently, our recommendation approach is based on the LSTM model due to its superior performance over its contemporaries. Recommendation of action items to best serve the users. We find this interesting, as managing tasks is not essential to contributing code per se but is perceived to be important, hence there might be this gap in expectations between CA designers and users that must be taken into account. This is a threat to theoretical validity, as the design thinking processes captured in our study might not represent the overall design thinking activity. The results of this study expose. To the extent this is feasible in qualitative case studies, this should enable a reproduction of our results under comparable contexts. Based on the results of our SLR, one can get good performance when using machine learning approaches like SVM or gradient boosting. When you optimized your internet pages, log files can show you the particular keywords and phrases employed by the visitors for your website that is their hit are targeted by the specified keyword. After applying all the filters explained above to the six selected repositories, we ended up having 54,127 pull requests that are tagged as bug fixes, in our data set with 83,067 unique files that are edited at least once.
Treated the adoption of GitHub Actions by each project in our data set as an “intervention”. However, there is a minor threat to descriptive validity since we used transcripts for data analysis instead of the video recordings. However, design thinking is a cognitive activity and can happen also implicitly inside the mind of the thinking developer (tacit design thinking). Design thinking is a concrete phenomenon, a natural and ubiquitous human activity during problem-solving processes 62. We assessed explicit design thinking, i.e., design thinking expressed verbally. Regarding the connection between design creativity and design thinking, we observe that the teams that quickly jump between topics and make many assumptions seem to be the teams that exhibit most problem space exploration. Understanding when this frequently valuable type of software development might make sense is also typically easy enough to do. The level of expertise and experience in software architecture design might influence the design thinking. In addition, all distributed developers had a short hands-on experience (i.e., 2222-3333 minutes) to test the environment by collaboratively sketching on the shared canvas of OctoUML. While all teams consisted of members with professional experience, this experience differed. Specifically, the co-located teams had on average 19 years of professional experience, the distributed teams between 3 and 7 years. In the co-located case, CT2 has with 43.8% by far the highest proportion of problem-space exploration, followed by CT1 with only 29.4%. Investigating the creative events, we notice that this team exhibits a clear pattern of making assumptions whenever they come across a new issue or complexity that they cannot solve immediately: “So this can get fairly complex very fast because you have all these intersections.