Teaming is a core component in practically all professional softwareengineering careers, and as such, is a key skill taught in many undergraduate Computer Science programs. However, not all teams manage to work toget...
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ISBN:
(纸本)9781450391948
Teaming is a core component in practically all professional softwareengineering careers, and as such, is a key skill taught in many undergraduate Computer Science programs. However, not all teams manage to work together effectively, and in education, this can deprive some students of successful teaming experiences. In this work, we seek to gain insights into the characteristics of successful and unsuccessful undergraduate student teams in a softwareengineering course. We conduct semi-structured interviews with18 students who have recently completed a team-based softwareengineering course to understand how they worked together, what challenges they faced, and how they tried to overcome these challenges. Our results show that common problems include communicating, setting and holding to deadlines, and effectively identifying tasks and their relative difficulty. Additionally, we find that self-reflection on what is working and not working or external motivators such as grades help some, but not all, teams overcome these challenges. Finally, we conclude with recommendations for educators on successful behaviours to steer teams towards, and recommendations for researchers on future work to better understand challenges that teams face.
Online runtime verification is a formal dynamic technique that studies how to monitor formal specifications incrementally against an input trace. Often, an observed prefix of a behavior is not enough to emit a definit...
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Online runtime verification is a formal dynamic technique that studies how to monitor formal specifications incrementally against an input trace. Often, an observed prefix of a behavior is not enough to emit a definite verdict and the monitor must wait to receive more information from the execution of the observed system. Monitorability classifies the set of properties depending on the feasibility to obtain a verdict after a finite observation. Havelund and Peled (Proceedings of 18thinternationalconference on runtime verification (RV'18), Berlin, 2018) classified LTL properties according to whether an observation can be extended to a definite answer. In this paper we present a framework that extends the classification of Havelund and Peled to verdict domains that are richer than Booleans, obtaining a monitorability setting under which some of the verdicts (but not others) can be discarded after a sequence of observations. We study the instance of this setting to quantitative temporal logics and we illustrate using examples the different elements of the taxonomy. Finally, we also consider how assumptions on the set of behaviors can affect monitorability.
Artificial Intelligence (AI) systems have gained significant traction in the recent past, creating new challenges in requirements engineering (RE) when building AI software systems. RE for AI practices have not been s...
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ISBN:
(纸本)9789897586477
Artificial Intelligence (AI) systems have gained significant traction in the recent past, creating new challenges in requirements engineering (RE) when building AI software systems. RE for AI practices have not been studied much and have scarce empirical studies. Additionally, many AI software solutions tend to focus on the technical aspects and ignore human-centered values. In this paper, we report on a case study for eliciting and modeling requirements using our framework and a supporting tool for human-centred RE for AI systems. Our case study is a mobile health application for encouraging type-2 diabetic people to reduce their sedentary behavior. We conducted our study withthree experts from the app team - a software engineer, a project manager and a data scientist. We found in our study that most human-centered aspects were not originally considered when developing the first version of the application. We also report on other insights and challenges faced in RE for the health application, e.g., frequently changing requirements.
Withthe rise of healthcare digitization, it has become a critical priority to safeguard patient privacy and ensure data security. Conventional methods of data access control mechanisms have proven to be insufficient ...
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the main protection of transmission lines against electrical faults is the distance relay. According to the feature of this relays, which detect faults by utilizing the impedance of the line, they are susceptible to m...
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To prepare students for the future workforce, it is important to provide them withknowledge and guidance about professional softwareengineering practices. One critical element of workplace practices is learning on t...
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ISBN:
(纸本)9798350378986;9798350378979
To prepare students for the future workforce, it is important to provide them withknowledge and guidance about professional softwareengineering practices. One critical element of workplace practices is learning on the job. there are few studies of how software engineers learn on the job and little focus within the literature on how this understanding can help train students. In this paper, we present a qualitative interview-based field study of workplace learning among professional software engineers. We conducted in-depth interviews with ten software engineers and analyzed the data using thematic analysis based on the learning ecologies framework. In our findings, we identify and discuss professionals' motivation and reasons for learning, the different resources they use to learn, the challenges they face in their learning, and their views on the relationship between formal education and on the job learning. We draw implications of the findings for teaching and learning, and future research.
this article reports papers about technical debt (TD) from the 2021 IEEE/Association for Computing Machinery (ACM) internationalconference on technical debt (TechDebt’21), the 43rd IEEE/ACM internationalconference ...
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this article reports papers about technical debt (TD) from the 2021 IEEE/Association for Computing Machinery (ACM) internationalconference on technical debt (TechDebt’21), the 43rd IEEE/ACM internationalconference on softwareengineering: Journal First Track (ICSE-JF’21), the 43rd IEEE/ACM internationalconference on softwareengineering: softwareengineering in Practice Track (ICSE-SEIP’21), and the 2021 IEEE/ACM 18thinternationalconference on Mining software Repositories (MSR’21). Feedback or suggestions are welcome. In addition, if you try or adopt any of the practices included in the column, please send us and the authors a note about your experiences.
Methods and tools to support quality assessment and code anomaly detection are crucial to enable software evolution and maintenance. In this work, we aim to detect an increase or decrease in code anomalies leveraging ...
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ISBN:
(纸本)9789897586477
Methods and tools to support quality assessment and code anomaly detection are crucial to enable software evolution and maintenance. In this work, we aim to detect an increase or decrease in code anomalies leveraging on the concept of microstructures, which are relationships between entities in the code. We introduce a tools pipeline, called Cadartis, which uses an innovative immune-inspired approach for code anomaly detection, tailored to the organization's needs. this approach has been evaluated on 3882 versions of fifteen open-source projects belonging to three different organizations and the results confirm that the approach can be applied to recognize a decrease or increase of code anomalies (anomalous status). the tools pipeline has been designed to automatically learn patterns of microstructures from previous versions of existing systems belonging to the same organization, to build a personalized quality profiler based on its codebase. this work represents a first step towards new perspectives in the field of software quality assessment and it could be integrated into continuous integration pipelines to profile software quality during the development process.
In the last two decades, research in Self-Adaptive Systems (SAS) has proposed various approaches for inducing a software system withthe ability to change itself at runtime in terms of self-adaptation strategies. For ...
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ISBN:
(纸本)9789897586477
In the last two decades, research in Self-Adaptive Systems (SAS) has proposed various approaches for inducing a software system withthe ability to change itself at runtime in terms of self-adaptation strategies. For the wider adoption of these strategies, there is a need for a framework and tool support to enable their analysis, evaluation, comparison, and eventually their selection in overlapping cases. In this paper, we take a step in this direction by proposing a comprehensive metric suite, i.e., the Adaptive Strategies Metric Suite (ASMS), to measure the design and runtime properties of the adaptive strategies for SAS. ASMS consists of metrics that can be applied through both static and dynamic code analysis. the metrics pertaining to static code analysis have been implemented as a plugin for Understand tool.
there is a growing need for better development methods and tools to keep up withthe increasing complexity of new software systems. New types of user interfaces, the need for intelligent components, sustainability con...
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ISBN:
(数字)9783031617539
ISBN:
(纸本)9783031617522;9783031617539
there is a growing need for better development methods and tools to keep up withthe increasing complexity of new software systems. New types of user interfaces, the need for intelligent components, sustainability concerns,... bring new challenges that we need to handle. In the last years, model-driven engineering has been key to improving the quality and productivity of software development, but models themselves are becoming increasingly complex to specify and manage. In this paper, we present the concept of low-modeling as a solution to enhance current model-driven engineering techniques and get them ready for this new generation of software systems.
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