16,838 research outputs found

    Empirical Analysis of Factors Affecting Confirmation Bias Levels of Software Engineers

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    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

    An analysis of the effects of company culture, education and experience on confirmation bias levels of software developers and testers

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    In this paper, we present a preliminary analysis of factors such as company culture, education and experience, on confirmation bias levels of software developers and testers. Confirmation bias is defined as the tendency of people to verify their hypotheses rather than refuting them and thus it has an effect on all software testing

    Modeling Human Aspects to Enhance Software Quality Management

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    The aim of the research is to explore the impact of cognitive biases and social networks in testing and developing software. The research will aim to address two critical areas: i) to predict defective parts of the software, ii) to determine the right person to test the defective parts of the software. Every phase in software development requires analytical problem solving skills. Moreover, using everyday life heuristics instead of laws of logic and mathematics may affect quality of the software product in an undesirable manner. The proposed research aims to understand how mind works in solving problems. People also work in teams in software development that their social interactions in solving a problem may affect the quality of the product. The proposed research also aims to model the social network structure of testers and developers to understand their impact on software quality and defect prediction performance

    Arguments from Expert Opinion and Persistent Bias

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    Accounts of arguments from expert opinion take it for granted that expert judgments are reliable, and so an argument that proceeds from premises about what an expert judges to a conclusion that the expert is probably right is a strong argument. In my (2013), I considered a potential justification for this assumption, namely, that expert judgments are more likely to be true than novice judgments, and discussed empirical evidence suggesting that expert judgments are not more reliable than novice judgments or even chance. In this paper, I consider another potential justification for this assumption, namely, that expert judgments are not influenced by the kinds of cognitive biases novice judgments are influenced by, and discuss empirical evidence suggesting that experts are vulnerable to pretty much the same kinds of cognitive biases as novices. If this is correct, then the basic assumption at the core of accounts of arguments from expert opinion remains unjustified

    Towards a Metric Suite Proposal to Quantify Confirmation Biases of Developers

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    The goal of software metrics is the identification and measurement of the essential parameters that affect software development. Metrics can be used to improve software quality and productivity. Existing metrics in the literature are mostly product or process related. However, thought processes of people have a significant impact on software quality as software is designed, implemented and tested by people. Therefore, in defining new metrics, we need to take into account human cognitive aspects. Our research aims to address this need through the proposal of a new metric scheme to quantify a specific human cognitive aspect, namely "confirmation bias". In our previous research, in order to quantify confirmation bias, we defined a methodology to measure confirmation biases of people. In this research, we propose a metric suite that would be used by practitioners during daily decision making. Our proposed metric set consists of six metrics with a theoretical basis in cognitive psychology and measurement theory. Empirical sample of these metrics are collected from two software companies that are specialized in two different domains in order to demonstrate their feasibility. We suggest ways in which practitioners may use these metrics to improve software development process

    Omission of quality software development practices : a systematic literature review

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    Software deficiencies are minimized by utilizing recommended software development and quality assurance practices. However, these recommended practices (i.e., quality practices) become ineffective if software professionals purposefully ignore them. Conducting a systematic literature review (n = 4,838), we discovered that only a small number of previous studies, within software engineering and information systems literature, have investigated the omission of quality practices. These studies explain the omission of quality practices mainly as a result of organizational decisions and trade-offs made under resource constraints or market pressure. However, our study indicates that different aspects of this phenomenon deserve further research. In particular, future research must investigate the conditions triggering the omission of quality practices and the processes through which this phenomenon occurs. Especially, since software development is a human-centric phenomenon, the psychological and behavioral aspects of this process deserve in-depth empirical investigation. In addition, futures research must clarify the social, organizational, and economical consequences of ignoring quality practices. Gaining in-depth theoretically sound and empirically grounded understandings about different aspects of this phenomenon enables research and practice to suggest interventions to overcome this issue.fi=vertaisarvioitu|en=peerReviewed

    Hypersonic Wind Tunnel Calibration Using the Modern Design of Experiments

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    A calibration of a hypersonic wind tunnel has been conducted using formal experiment design techniques and response surface modeling. Data from a compact, highly efficient experiment was used to create a regression model of the pitot pressure as a function of the facility operating conditions as well as the longitudinal location within the test section. The new calibration utilized far fewer design points than prior experiments, but covered a wider range of the facility s operating envelope while revealing interactions between factors not captured in previous calibrations. A series of points chosen randomly within the design space was used to verify the accuracy of the response model. The development of the experiment design is discussed along with tactics used in the execution of the experiment to defend against systematic variation in the results. Trends in the data are illustrated, and comparisons are made to earlier findings

    Technical Debt: An empirical investigation of its harmfulness and on management strategies in industry

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    Background: In order to survive in today\u27s fast-growing and ever fast-changing business environment, software companies need to continuously deliver customer value, both from a short- and long-term perspective. However, the consequences of potential long-term and far-reaching negative effects of shortcuts and quick fixes made during the software development lifecycle, described as Technical Debt (TD), can impede the software development process.Objective: The overarching goal of this Ph.D. thesis is twofold. The first goal is to empirically study and understand in what way and to what extent, TD influences today’s software development work, specifically with the intention to provide more quantitative insight into the field. Second, to understand which different initiatives can reduce the negative effects of TD and also which factors are important to consider when implementing such initiatives.Method: To achieve the objectives, a combination of both quantitative and qualitative research methodologies are used, including interviews, surveys, a systematic literature review, a longitudinal study, analysis of documents, correlation analysis, and statistical tests. In seven of the eleven studies included in this Ph.D. thesis, a combination of multiple research methods are used to achieve high validity.Results: We present results showing that software suffering from TD will cause various negative effects on both the software and the developing process. These negative effects are illustrated from a technical, financial, and a developer’s working situational perspective. These studies also identify several initiatives that can be undertaken in order to reduce the negative effects of TD.Conclusion: The results show that software developers report that they waste 23% of their working time due to experiencing TD and that TD required them to perform additional time-consuming work activities. This study also shows that, compared to all types of TD, architectural TD has the greatest negative impact on daily software development work and that TD has negative effects on several different software quality attributes. Further, the results show that TD reduces developer morale. Moreover, the findings show that intentionally introducing TD in startup companies can allow the startups to cut development time, enabling faster feedback and increased revenue, preserve resources, and decrease risk and thereby contribute to beneficial\ua0effects. This study also identifies several initiatives that can be undertaken in order to reduce the negative effects of TD, such as the introduction of a tracking process where the TD items are introduced in an official backlog. The finding also indicates that there is an unfulfilled potential regarding how managers can influence the manner in which software practitioners address TD
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