Pilar Rodriguez

Woubshet Behutiye, Pertti Seppanen, Pilar Rodriguez et al.

Context: Quality requirements (QRs) have a significant role in the success of software projects. In agile software development (ASD), where working software is valued over comprehensive documentation, QRs are often under-specified or not documented. Consequently, they may be handled improperly and result in degraded software quality and increased maintenance costs. Investigating the documentation of QRs in ASD, would provide evidence on existing practices, tools and aspects considered in ASD that other practitioners might utilize to improve documentation and management of QRs in ASD. Although there are some studies examining documentation in ASD, those that specifically investigate the documentation of QRs in depth are lacking. Method: we conducted a multiple case study by interviewing 15 practitioners of four ASD cases, to provide empirical evidence on documentation of QRs in ASD. We also run workshops with two of the cases, to identify important aspects that ASD practitioners consider when documenting QRs in requirements management repositories. Result and conclusions: ASD companies approach documentation of QRs to fit the needs of their context. They used tools, backlogs,iterative prototypes,... Please refer to the PDF document for the remaining part of the abstract and the rest of the paper

Prabhat Ram, Pilar Rodriguez, Markku Oivo

Existing scientific literature highlights the importance of metrics in Agile Software Development (ASD). Still, empirical investigation into metrics in ASD is scarce, particularly in identifying the rationale and the operational challenges associated with metrics. Under the Q-Rapids project (Horizon 2020), we conducted a multiple case study at four Agile companies, using the Goal Question Metric (GQM) approach, to investigate the rationale explaining the choice of process metrics in ASD, and challenges faced in operationalizing them. Results reflect that companies are interested in assessing process aspects like velocity, testing performance, and estimation accuracy, and they prefer custom metrics for these assessments. Companies use metrics as a means to access and even capitalize on the data, erstwhile inaccessible due to technical or process constraints. However, development context of a company can hinder metrics operationalization, manifesting primarily as unavailability of the data required to measure metrics...(check the paper for full Abstract)

Rahul Mohanani, Iflaah Salman, Burak Turhan et al.

One source of software project challenges and failures is the systematic errors introduced by human cognitive biases. Although extensively explored in cognitive psychology, investigations concerning cognitive biases have only recently gained popularity in software engineering (SE) research. This paper therefore systematically maps, aggregates and synthesizes the literature on cognitive biases in software engineering to generate a comprehensive body of knowledge, understand state of the art research and provide guidelines for future research and practise. Focusing on bias antecedents, effects and mitigation techniques, we identified 65 articles, which investigate 37 cognitive biases, published between 1990 and 2016. Despite strong and increasing interest, the results reveal a scarcity of research on mitigation techniques and poor theoretical foundations in understanding and interpreting cognitive biases. Although bias-related research has generated many new insights in the software engineering community, specific bias mitigation techniques are still needed for software professionals to overcome the deleterious effects of cognitive biases on their work.