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2,751 papers
SEMAT Accelerator is a web-positioning tool for a software project, which implements the Essence kernel and its elements, and enables teaching, adopting, and researching Essence in controlled experiments and case studies.
Statistical data shows that the use of PSP did not improve size and time estima- tion skills but that the productivity did not decrease and the resulting product quality was improved.
The main results indicate that self-organization as supported by certain Agile and Lean practices helps teams in achieving higher performance.
This paper investigates how usage of features relate to their perceived value and shed light into the factors affecting this relationship and shows that feature usage metric has a significant potential to estimate value of features.
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A conceptual framework of cloud computing benefits is proposed, based on various benefit taxonomies presented in the Information System literature, and accounts for the different business areas and organizational levels where each of the benefits manifests.
A modelling notation, so called Feature Usage Diagram, and an approach to identify and visualize the required information for decision makers when reducing features, which has potential to support developers when making decisions for feature reduction.
This paper proposes a novel approach called the unproject leadership model, which translates and maps the specific complexity concepts to the software development domain, consolidating them with the contributions already achieved by the lean and agile literature.
Early results indicate that change agents valued the process user satisfaction the most and the process improvement fit the least, confirming the need of having various stakeholders and dimensions acknowledged in a framework that is used to measure the overall success of an SPI initiative.
This study presents the results of a systematic mapping study on software size estimation metrics and methods. The methods are investigated based on the entity type(s) measured by the method, size attribute type, size measure(s), and theoretical/empirical validation status of the method, and restriction with respect to...
A set of themes that can potentially explain self-organization from the learning viewpoint are identified, which include self-decided learning goals and personalized learning outcomes, peer teaching through active collaboration, diversity is the key and the personal attitude towards the learning matters.
This paper aims to understand how software developers experience the continuous adaptation of performance in a modern, highly volatile environment using Lean and Agile software development methodology and generates a grounded theory, Performance Alignment Work, showing howSoftware developers experience performance.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
By rethinking how large cloud computing systems operate, Associate Professor Christina Delimitrou seeks to make data centers more energy efficient.
An ongoing survey tracks the latest AI accelerator systems to keep hardware relevant for Lincoln Laboratory staff and sponsors.
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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