On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review <s> Data extraction and synthesis <s> Objectives: To demonstrate the benefits of applying meta ethnography to the synthesis of qualitative research, by means of a worked example. Methods: Four papers about lay meanings of medicines were arbitrarily chosen. Noblit and Hare's seven-step process for conducting a meta ethnography was employed: getting started; deciding what is relevant to the initial interest; reading the studies; determining how the studies are related; translating the studies into one another; synthesising translations; and expressing the synthesis. Results: Six key concepts were identified: adherence/compliance; self-regulation; aversion; alternative coping strategies; sanctions; and selective disclosure. Four second-order interpretations (derived from the chosen papers) were identified, on the basis of which four third-order interpretations (based on the key concepts and second-order interpretations) were constructed. These were all linked together in a line of argument that accounts for patients' medicine-taking behaviour and communication with health professionals in different settings. Third-order interpretations were developed which were not only consistent with the original results but also extended beyond them. Conclusions: It is possible to use meta ethnography to synthesise the results of qualitative research. The worked example has produced middle-range theories in the form of hypotheses that could be tested by other researchers. <s> BIB001 </s> On Using Network Science in Mining Developers Collaboration in Software Engineering: A Systematic Literature Review <s> Data extraction and synthesis <s> Context: The increase in the number of qualitative and mixed-methods research published in software engineering has created an opportunity for further knowledge generation through the synthesis of studies with similar aims. This is particularly true in the research on human aspects because the phenomena of interest are often better understood using qualitative research. However, the use of qualitative synthesis methods is not widespread and worked examples of their consistent application in software engineering are needed. Objective: To explore the use of meta-ethnography in the synthesis of empirical studies in software engineering through an example using studies about the relations between personality and software team processes. Methods: We applied the seven phases of meta-ethnography on a set of articles selected from a previously developed systematic review, to assess the appropriateness of meta-ethnography in this domain with respect to ease of use, and usefulness and reliability of results. Results: Common concepts were identified through reading and interpreting the studies. Then, second order translations were built and used to synthesize a model of the relationships between personality and software team processes. Conclusions: Meta-ethnography is adequate in the synthesis of empirical studies even in the context of mixed-methods studies. However, we believe that the method should not be used to synthesize studies that are too disparate to avoid the development of gross generalizations, which tend to be fruitless and are contrary to the central tenets of interpretive research. <s> BIB002
Data synthesis for heterogeneous studies is always hard, particularity when the primary studies cover the same aspect with different measurements and present the results in different ways. Also, the primary studies in most cases use a mixed-methods for the analysis that makes a universal comparison impossible. Thus, we followed a meta-ethnography method BIB001 , as advised by Silva et al. in BIB002 , which translates the quantitative findings of the PSs into comparable features that can be used for a proper analysis. Thus, we invested a lot of time during the execution of this SLR in designing a good set of features to be extracted from the primary studies in order to answer the research questions. Table 7 shows the set of features extracted from each primary study. Features in category "A" are documentary features that capture the general goal of each primary study. For space limitation, we will discuss few of them in the following. Feature "A1" in this review has the same value (i.e., Human Aspects that is the main topic of this review). Feature "A2" represents the SE context that the proposed network analysis method serves, for example, how can we do bug assignment by analyzing the developers collaboration network?. Feature "A3" captures the network being used in each PS. Features of category "B" address the network analysis aspects of the PSs, and features of category "C" address the other aspects. Features "B1" to "B6" address questions about the constructed network type. This is an important step towards understating how valid the constructed networks are, which is covered in features "B7" to "B10". Feature "B7" reflects how good an edge is. Real edges are real connections between the nodes. A proxy edge is used when the real edge is hard to obtain. For example, changing a file, a module, or any software artifact may not yield a real relationship. Instead, we call this interaction a proxy. An example of a real edge is the edges constructed in the communication email networks, in which the edge and its direction are explicitly found in reality. Having clear idea about the constructed network, we can check the validity of the used measures and their meaningfulness. Features "B11" to "B13" address the used measures in each PS. Feature "B12" is important and it reflects whether the meaning of the used measures is sufficiently explained or not, and if the explanation exists, whether it is meaningful or not. The feature "B14" tests whether the results in each PS are validated or not. The extraction features in Table 7 are designed to be mapped to the research questions in Section 1.1. Extraction features "B1" to "B10" give us rich information that enable obtaining strong evidence regarding the quality of the constructed networks addressed in RQ1. Features "B11" to "B13" answer RQ2, while the feature "B14" is mapped to RQ3. Features "C1" to "C4" answer RQ4. The answers of the first four research questions enable us to answer RQ5. 