Regression testing is a means to assure that a change in the software, or its execution environment, does not introduce new defects. It involves the expensive undertaking of rerunning test cases. Several techniques have been proposed to reduce the number of test cases to execute in regression testing, however, there is no research on how to assess industrial relevance and applicability of such techniques. We conducted a systematic literature review with the following two goals: firstly, to enable researchers to design and present regression testing research with a focus on industrial relevance and applicability and secondly, to facilitate the industrial adoption of such research by addressing the attributes of concern from the practitioners' perspective. Using a reference-based search approach, we identified 1068 papers on regression testing. We then reduced the scope to only include papers with explicit discussions about relevance and applicability (i.e. mainly studies involving industrial stakeholders). Uniquely in this literature review, practitioners were consulted at several steps to increase the likelihood of achieving our aim of identifying factors important for relevance and applicability. We have summarised the results of these consultations and an analysis of the literature in three taxonomies, which capture aspects of industrial-relevance regarding the regression testing techniques. Based on these taxonomies, we mapped 38 papers reporting the evaluation of 26 regression testing techniques in industrial settings.

Software engineers handle a lot of information in their daily work. We explore how software engineers interact with information management systems/tools, and to what extent these systems expose users to increased cognitive load. We reviewed the literature of cognitive aspects, relevant for software engineering, and performed an exploratory case study on how software engineers perceive information systems. Data was collected through five semistructured interviews. We present empirical evidence of the presence of cognitive load drivers, as a consequence of tool use in large scale software engineering.

For climate and sustainability reasons, there is an interest and incentive to produce plastic and rubber products with increased content of a bio-based component, preferably existing as an industrial by-product, for example, wood powder/sawdust. There are many studies on the making of wood-plastic composites, but hitherto very few consider vacuum forming as a processing technique, especially considering a biofiller. Here, the properties of a vacuum formed composite with thermally modified wood powder (with reduced water uptake) and a very ductile polyolefin, was reported. Surprisingly, even at a 15 wt% filler content, the composite remained ductile (extensibility of ca. 30%). The water uptake increased with increasing content of wood powder, but was never more than 5%. The water sorption kinetics indicated that the wood powder did not form a percolated continuous path through the material for easy access to the water, which led to a low water diffusivity (ca. 2 Â 10 À10 cm 2 s À1 ). The calorimetric data showed that the biofiller, overall, did not affect the melting and crystallization behavior of the polymer matrix, nor the observed glass transition temperature. To conclude, vacuum forming was shown to be a viable technique for composites with a very ductile/elastic matrix and stiff fillers.