InfoQ Homepage Applied Research Content on InfoQ
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/articles/adapt-surprises-software-reliant-businesses/en/smallimage/Preparing-to-Be-Unprepared-logo-small-1723034897494.jpg)
Prepare to Be Unprepared: Investing in Capacity to Adapt to Surprises in Software-Reliant Businesses
Incidents are often perceived as extraordinary aberrations, unconnected to "normal" work. For over twenty years, the field of Resilience Engineering has aimed at flipping this approach around — by understanding what makes incidents so rare (relative to when and how they do not happen) and so minor (relative to how much worse they can be) and deliberately enhancing what makes that possible.
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/articles/testing-machine-learning-simulators/en/smallimage/testing-machine-learning-small-logo-1709558228387.jpg)
Testing Machine Learning: Insight and Experience from Using Simulators to Test Trained Functionality
When testing machine learning systems, we must apply existing test processes and methods differently. Machine Learning applications consist of a few lines of code, with complex networks of weighted data points that form the implementation. The data used in training is where the functionality is ultimately defined, and that is where you will find your issues and bugs.
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/articles/improve-predictability-measure-stability/en/smallimage/how-agile-teams-can-improve-predictability-by-measuring-stability-small-1693917878580.jpg)
How Agile Teams Can Improve Predictability by Measuring Stability
In this article, we will present our approach for analysing agile systems as networks of queues and how we have used it to analyse 926 projects in the Public Jira Dataset. We explain how you can measure the Stability Metric (SM) for your queues. Finally, we will present our planned next phase of research.
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/articles/process-data-find-more-bugs/en/smallimage/logo-1674649351750.jpg)
How to Use Your Existing Software Development Process Data to Find More Bugs in Less Time
This article presents better solutions that employ data from the system under test and the tests themselves to optimize testing efforts. This allows teams to find more bugs (by making sure that bug-dense areas are tested) in less time (by reducing the executions of tests that are very unlikely to detect bugs).
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How to Measure the Energy Consumption of Bugs
Software engineers should accept their responsibility for taking energy consumption and carbon dioxide emissions into account when developing software; they have a big responsibility towards nature, our environment and sustainability. This article sheds light on how software engineers can this perspective into account, zooming in on energetic shortcomings or bottlenecks of bugs.
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/articles/co-creation-patterns-software-development/en/smallimage/logo-1667590759022.jpg)
From Async Code Reviews to Co-Creation Patterns
This article dives into the throughput and quality of the async code review process, which are very important dimensions to optimize for in product development teams. It also explains why co-creation patterns – Pair and Mob programming – as an alternative way of working are able to optimize for both of those dimensions, instead of needing to trade off between them.
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/articles/green-iot-energy-sustainability/en/smallimage/green-IoT-for-energy-efficiency-and-environmental-sustainability-small-1666432828743.jpg)
Green IoT for Energy Efficiency and Environmental Sustainability
The growth of IoT has resulted in improving connectivity amongst devices worldwide. Green IoT represents the energy efficient procedures adopted by IoT devices to achieve a sustainable and safer world. In order to green the IoT, it will be necessary to use less energy, look for new resources, reduce the negative effects of the IoT on human health, and cause less environmental disruption.
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/articles/business-impact-code-quality/en/smallimage/logo-1665740739711.jpg)
Code Red: the Business Impact of Code Quality
Everyone in the software industry “knows” that code quality is important, yet we never had any data or numbers to prove it. In this article, we explore the impact by diving into recent research on code quality. With twice the development speed, 15 times fewer bugs, and a significant reduction of uncertainty in completion times, the business advantage of code quality is unmistakably clear.
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/articles/psychological-safety-tech-teams/en/smallimage/psychological-safety-tech-teams-image-small-1649851511472.jpg)
How Psychological Safety at Work Creates Effective Software Tech Teams That Learn and Grow
This article provides the foundations of psychological safety and shows how it has been applied for team effectiveness. It explores how psychological safety supports learning and improvement and how we can foster a psychologically safe culture in tech teams.
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Getting Rid of Wastes and Impediments in Software Development Using Data Science
This article presents how to use data science to detect wastes and impediments, and concepts and related information that help teams to figure out the root cause of impediments they struggle to get rid of. The knowledge discovered during research includes an expanded waste classification, and the use of trends to uncover undesired situations like hidden delayed backlog items and defects trends.
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/articles/spaces-shape-collaboration-anthropology/en/smallimage/how-space-shapes-collaboration-small-image-1640183715486.jpg)
How Space Shapes Collaboration: Using Anthropology to Break Silos
Software companies strive to keep innovating and changing the rules of the market. These companies are made of people who, unlike smartphones, personal computers or smart watches, have not evolved as much in recent years. This article proposes an analysis of workspaces from anthropology to solve one of the most common problems: the appearance of silos instead of a culture of collaboration.
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Validation of Autonomous Systems
This article introduces validation and certification as well as the general approval of autonomous systems and their components, such as those used in automation technology and robotics. It gives an overview of methods for verification and validation of autonomous systems, sketches current tools and show the evolution towards AI-based techniques for influence analysis of continuous changes.