Tackling gendered aspects of acculturation through Turkish migrant women’s experiences in Europe

Gendered patterns and experiences in migration and acculturation research have recently started to gain recognition with the developments of intersectional and transnational/diaspora theories. Following advancements in the literature, the aim of the current study is to tackle gendered experiences of acculturation through readapting different social domains of RAEM (Relative Acculturation Extended Model) in making sense of the data from qualitative interviews with 24 Turkish migrant women across different European contexts. Findings suggest alternative lines in conceptualizing culture and thus, acculturation, in the case of Turkish migrant women, in addition to conceptualizing potential gendered peculiarities that may surface at the intersection of different positionalities across different social domains. Different consequences of how social domains intertwine in shaping women’s acculturation strategies and the mismatch between their ideal and real strategies are discussed, with potential future leads and implications.info:eu-repo/semantics/publishedVersio

Ground truth deficiencies in software engineering: when codifying the past can be counterproductive

Many software engineering tools build and evaluate their models based on historical data to support development and process decisions. These models help us answer numerous interesting questions, but have their own caveats. In a real-life setting, the objective function of human decision-makers for a given task might be influenced by a whole host of factors that stem from their cognitive biases, subverting the ideal objective function required for an optimally functioning system. Relying on this data as ground truth may give rise to systems that end up automating software engineering decisions by mimicking past sub-optimal behaviour. We illustrate this phenomenon and suggest mitigation strategies to raise awareness

Identifying Potential Risks and Benefits of Using Cloud in Distributed Software Development

Cloud-based infrastructure has been increasingly adopted by the industry in distributed software development (DSD) environments. Its proponents claim that its several benefits include reduced cost, increased speed and greater productivity in software development. Empirical evaluations, however, are in the nascent stage of examining both the benefits and the risks of cloud-based in-frastructure. The objective of this paper is to identify potential benefits and risks of using cloud in a DSD project conducted by teams based in Helsinki and Ma-drid. A cross-case qualitative analysis is performed based on focus groups con-ducted at the Helsinki and Madrid sites. Participants’ observations are used to supplement the analysis. The results of the analysis indicated that the main ben-efits of using cloud are rapid development, continuous integration, cost savings, code sharing, and faster ramp-up. The key risks determined by the project are dependencies, unavailability of access to the cloud, code commitment and inte-gration, technical debt, and additional support costs. The results revealed that if such environments are not planned and set up carefully, the benefits of using cloud in DSD projects might be overshadowed by the risks associated with it.Peer reviewe

An industry experiment on the effects of test-driven development on external quality and productivity

Existing empirical studies on test-driven development (TDD) report different conclusions about its effects on quality and productivity. Very few of those studies are experiments conducted with software professionals in industry. We aim to analyse the effects of TDD on the external quality of the work done and the productivity of developers in an industrial setting. We conducted an experiment with 24 professionals from three different sites of a software organization. We chose a repeated-measures design, and asked subjects to implement TDD and incremental test last development (ITLD) in two simple tasks and a realistic application close to real-life complexity. To analyse our findings, we applied a repeated-measures general linear model procedure and a linear mixed effects procedure. We did not observe a statistical difference between the quality of the work done by subjects in both treatments. We observed that the subjects are more productive when they implement TDD on a simple task compared to ITLD, but the productivity drops significantly when applying TDD to a complex brownfield task. So, the task complexity significantly obscured the effect of TDD. Further evidence is necessary to conclude whether TDD is better or worse than ITLD in terms of external quality and productivity in an industrial setting. We found that experimental factors such as selection of tasks could dominate the findings in TDD studies.This research has been partly funded by Spanish Ministry of Science and Innovation projects TIN2011-23216, the Distinguished Professor Program of Tekes, and the Academy of Finland (Grant Decision No. 260871)

Cloud computing in industrial SMEs: Identification of the barriers to its adoption and effects of its application

ABSTRACT: Cloud computing is a new technological paradigm that may revolutionize how organizations use IT by facilitating delivery of all technology as a service. In the literature, the Cloud is treated mainly through a technological approach focused on the concept definition, service models, infrastructures for its evelopment and security problems. However, there is an important lack of works which analyze this paradigm adoption in SMEs and its results, with a gap between the technological development and its adoption by organizations. This paper uses a qualitative technique methodology -group meetings with managers- and a quantitative one-survey- and identifies which factors act as barriers to Cloud adoption and which positive effects its application generates in 94 industrial SMEs. The conclusion is that the main barriers are of a cultural type and that the positive effects go well beyond reducing costs

Empirical Analysis of Factors Affecting Confirmation Bias Levels of Software Engineers

Confirmation bias is defined as the tendency of people to seek evidence that verifies a hypothesis rather than seeking evidence to falsify it. Due to the confirmation bias, defects may be introduced in a software product during requirements analysis, design, implementation and/or testing phases. For instance, testers may exhibit confirmatory behavior in the form of a tendency to make the code run rather than employing a strategic approach to make it fail. As a result, most of the defects that have been introduced in the earlier phases of software development may be overlooked leading to an increase in software defect density. In this paper, we quantify confirmation bias levels in terms of a single derived metric. However, the main focus of this paper is the analysis of factors affecting confirmation bias levels of software engineers. Identification of these factors can guide project managers to circumvent negative effects of confirmation bias, as well as providing guidance for the recruitment and effective allocation of software engineers. In this empirical study, we observed low confirmation bias levels among participants with logical reasoning and hypothesis testing skills

A review of rapid serial visual presentation-based brain-computer interfaces

International audienceRapid serial visual presentation (RSVP) combined with the detection of event related brain responses facilitates the selection of relevant information contained in a stream of images presented rapidly to a human. Event related potentials (ERPs) measured non-invasively with electroencephalography (EEG) can be associated with infrequent targets amongst a stream of images. Human-machine symbiosis may be augmented by enabling human interaction with a computer, without overt movement, and/or enable optimization of image/information sorting processes involving humans. Features of the human visual system impact on the success of the RSVP paradigm, but pre-attentive processing supports the identification of target information post presentation of the information by assessing the co-occurrence or time-locked EEG potentials. This paper presents a comprehensive review and evaluation of the limited but significant literature on research in RSVP-based brain-computer interfaces (BCIs). Applications that use RSVP-based BCIs are categorized based on display mode and protocol design, whilst a range of factors influencing ERP evocation and detection are analyzed. Guidelines for using the RSVP-based BCI paradigms are recommended, with a view to further standardizing methods and enhancing the inter-relatability of experimental design to support future research and the use of RSVP-based BCIs in practice

Challenges for automatically extracting molecular interactions from full-text articles

<p>Abstract</p> <p>Background</p> <p>The increasing availability of full-text biomedical articles will allow more biomedical knowledge to be extracted automatically with greater reliability. However, most Information Retrieval (IR) and Extraction (IE) tools currently process only abstracts. The lack of corpora has limited the development of tools that are capable of exploiting the knowledge in full-text articles. As a result, there has been little investigation into the advantages of full-text document structure, and the challenges developers will face in processing full-text articles.</p> <p>Results</p> <p>We manually annotated passages from full-text articles that describe interactions summarised in a Molecular Interaction Map (MIM). Our corpus tracks the process of identifying facts to form the MIM summaries and captures any factual dependencies that must be resolved to extract the fact completely. For example, a fact in the results section may require a synonym defined in the introduction. The passages are also annotated with negated and coreference expressions that must be resolved.</p> <p>We describe the guidelines for identifying relevant passages and possible dependencies. The corpus includes 2162 sentences from 78 full-text articles. Our corpus analysis demonstrates the necessity of full-text processing; identifies the article sections where interactions are most commonly stated; and quantifies the proportion of interaction statements requiring coherent dependencies. Further, it allows us to report on the relative importance of identifying synonyms and resolving negated expressions. We also experiment with an oracle sentence retrieval system using the corpus as a gold-standard evaluation set.</p> <p>Conclusion</p> <p>We introduce the MIM corpus, a unique resource that maps interaction facts in a MIM to annotated passages within full-text articles. It is an invaluable case study providing guidance to developers of biomedical IR and IE systems, and can be used as a gold-standard evaluation set for full-text IR tasks.</p