Context: Families of experiments (i.e., groups of experiments with the same goal) are on the rise in Software Engineering (SE). Selecting unsuitable aggregation techniques to analyze families may undermine their potential to provide in-depth insights from experiments' results. Objectives: Identifying the techniques used to aggregate experiments' results within families in SE. Raising awareness of the importance of applying suitable aggregation techniques to reach reliable conclusions within families. Method: We conduct a systematic mapping study (SMS) to identify the aggregation techniques used to analyze families of experiments in SE. We outline the advantages and disadvantages of each aggregation technique according to mature experimental disciplines such as medicine and pharmacology. We provide preliminary recommendations to analyze and report families of experiments in view of families' common limitations with regard to joint data analysis. Results: Several aggregation techniques have been used to analyze SE families of experiments, including Narrative synthesis, Aggregated Data (AD), Individual Participant Data (IPD) mega-trial or stratified, and Aggregation of p-values. The rationale used to select aggregation techniques is rarely discussed within families. Families of experiments are commonly analyzed with unsuitable aggregation techniques according to the literature of mature experimental disciplines. Conclusion: Data analysis' reporting practices should be improved to increase the reliability and transparency of joint results. AD and IPD stratified appear to be suitable to analyze SE families of experiments.

Software regression testing techniques verify previous functionalities each time software modifications occur or new characteristics are added. With the aim of gaining a better understanding of this subject, in this work we present a survey of software regression testing techniques applied in the last 15 years; taking into account its application domain, kind of metrics they use, its application strategies and the phase of the software development process where they are applied. From an outcome of 460 papers, a set of 25 papers describing the use of 31 software testing regression techniques were identified. Results of this survey suggest that at the time of applying a regression testing techniques, metrics like cost and fault detection efficiency are the most relevant. Most of the techniques were assessed with instrumented programs (experimental cases) under academic settings. Conversely, we observe a minimum set of software regression techniques applied in industrial settings, mainly, under corrective and maintenance approaches. Finally, we observe a trend using some regression techniques under agile approaches.

Experiment replication is a key component of the scientific paradigm. The purpose of replication is to verify previously observed findings. Although some Software Engineering (SE) experiments have been replicated, yet, there is still disagreement about how replications should be run in our field. With the aim of gaining a better understanding of how replications are carried out, this paper examines different replication types in other scientific disciplines. We believe that by analysing the replication types proposed in other disciplines it is possible to clarify some of the question marks still hanging over experimental SE replication.