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Evaluation of Novel Approaches to Software Engineering 17th International Conference, ENASE 2022, Virtual Event, April 25-26, 2022, Revised Selected Papers için kapak resmi
Başlık:
Evaluation of Novel Approaches to Software Engineering 17th International Conference, ENASE 2022, Virtual Event, April 25-26, 2022, Revised Selected Papers
Yazar:
Kaindl, Hermann. editor.
ISBN:
9783031365973
Basım Bilgisi:
1st ed. 2023.
Fiziksel Tanımlama:
XII, 338 p. 103 illus., 76 illus. in color. online resource.
Seri:
Communications in Computer and Information Science, 1829
İçerik:
Theory and Practice of Systems and Applications Development -- An Approach-based on Allen's Interval Algebra to Provision Resources for Disrupted Business Processes -- BPMN4FRSS: An BPMN Extension To Support Risk-Based Development of Forensic-Ready Software Systems -- Evaluating Probabilistic Topic Models for Bug Triaging Tasks -- Software Project Management Approaches Used in the Context of Agile Development: A Systematic Literature Mapping -- Empirical Validation of Entropy-based Redundancy Metrics as Reliability Indicators using Fault-proneness Attribute and Complexity Metrics -- Dynamic link Network Emulation and Validation of Execution Datasets -- Predicting Bug-fixing Time using the Latent Dirichlet Allocation Model with Covariates -- Challenges and Novel Approaches to Systems and Software Engineering (SSE) -- Pull Requests Integration Process Optimization: An Empirical Study -- Identify Javascript Trends in Crowdsourcing Small Tasks -- Assessing Sustainability Impacts of Systems: SuSAF and the SDGs -- Exploiting Metadata Semantics in Data Lakes using Blueprints -- The Ugly Side of Stack Overow: An In-depth Exploration of the Social Dynamics of New Users' Engagement and Community Perception of Them -- Systems and Software Quality -- Better Understanding Diverse End User Website Usage Challenges with Browser-based Augmented Reality Approaches -- An Exploration of Technical Debt Over the Lifetime of Open-source Software -- A New Metric for Multithreaded Parallel Programs Overhead Time Prediction.
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