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Institution

Carnegie Mellon University

EducationPittsburgh, Pennsylvania, United States
About: Carnegie Mellon University is a education organization based out in Pittsburgh, Pennsylvania, United States. It is known for research contribution in the topics: Computer science & Robot. The organization has 36317 authors who have published 104359 publications receiving 5975734 citations. The organization is also known as: CMU & Carnegie Mellon.


Papers
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Journal ArticleDOI
TL;DR: The key idea is to define architectural connectors as explicit semantic entities as a collection of protocols that characterize each of the participant roles in an interaction and how these roles interact.
Abstract: As software systems become more complex, the overall system structure—or software architecture—becomes a central design problem. An important step toward an engineering discipline of software is a formal basis for describing and analyzing these designs. In the article we present a formal approach to one aspect of architectural design: the interactions among components. The key idea is to define architectural connectors as explicit semantic entities. These are specified as a collection of protocols that characterize each of the participant roles in an interaction and how these roles interact. We illustrate how this scheme can be used to define a variety of common architectural connectors. We further provide a formal semantics and show how this leads to a system in which architectural compatibility can be checked in a way analogous to type-checking in programming languages.

1,344 citations

Journal ArticleDOI
TL;DR: In this paper, the nature of physical symbol systems is laid out in ways familiar, but not thereby useless, to review the basis of common understanding between the various disciplines.

1,343 citations

Book ChapterDOI
01 Jan 2001
TL;DR: An overview of the Capability Maturity Model for Software (Software CMM) and the concepts of software process maturity and a discussion of likely future directions for CMM-like models are provided.
Abstract: This article provides an overview of the Capability Maturity Model® for Software (Software CMM®) and the concepts of software process maturity. (Capability Maturity Model and CMM are registered in the U.S. Patent and Trademark Office.) It contains a background discussion of why process is crucial to organizational and project success, a description of the development of the CMM, a detailed summary of the model, and a description of the model's use for process improvement and the evaluation of software suppliers; describes the use of the CMM in the context of the SEI's IDEALSM (IDEAL is a service mark of Carnegie Mellon University) approach to process improvement; summarizes some of the strengths and weaknesses of the current model and its use; characterizes the state of the practice and the return on investment for software process improvement; and concludes with a discussion of likely future directions for CMM-like models. Keywords: capability maturity model; trademark; Carnegie Mellon University; principles; total quality management; software; maturity model; uses; key process improvement; case studies

1,342 citations

Journal ArticleDOI
TL;DR: According to the framework, organizational experience interacts with the context to create knowledge and the context is conceived as having both a latent component and an active component through which learning occurs.
Abstract: Organizational learning has been an important topic for the journal Organization Science and for the field. We provide a theoretical framework for analyzing organizational learning. According to the framework, organizational experience interacts with the context to create knowledge. The context is conceived as having both a latent component and an active component through which learning occurs. We also discuss current and emerging research themes related to components of our framework. Promising future research directions are identified. We hope that our perspective will stimulate future work on organizational learning and knowledge.

1,340 citations

Journal ArticleDOI
TL;DR: A semi-parametric mixture model was used with a sample of 1,037 boys assessed repeatedly from 6 to 15 years of age to approximate a continuous distribution of developmental trajectories for three externalizing behaviors.
Abstract: A semi-parametric mixture model was used with a sample of 1,037 boys assessed repeatedly from 6 to 15 years of age to approximate a continuous distribution of developmental trajectories for three externalizing behaviors. Regression models were then used to determine which trajectories best predicted physically violent and nonviolent juvenile delinquency up to 17 years of age. Four developmental trajectories were identified for the physical aggression, opposition, and hyperactivity externalizing behavior dimensions: a chronic problem trajectory, a high level near-desister trajectory, a moderate level desister trajectory, and a no problem trajectory. Boys who followed a given trajectory for one type of externalizing problem behavior did not necessarily follow the same trajectory for the two other types of behavior problem. The different developmental trajectories of problem behavior also led to different types of juvenile delinquency. A chronic oppositional trajectory, with the physical aggression and hyperactivity trajectories being held constant, led to covert delinquency (theft) only, while a chronic physical aggression trajectory, with the oppositional and hyperactivity trajectories being held constant, led to overt delinquency (physical violence) and to the most serious delinquent acts.

1,337 citations


Authors

Showing all 36645 results

NameH-indexPapersCitations
Yi Chen2174342293080
Rakesh K. Jain2001467177727
Robert C. Nichol187851162994
Michael I. Jordan1761016216204
Jasvinder A. Singh1762382223370
J. N. Butler1722525175561
P. Chang1702154151783
Krzysztof Matyjaszewski1691431128585
Yang Yang1642704144071
Geoffrey E. Hinton157414409047
Herbert A. Simon157745194597
Yongsun Kim1562588145619
Terrence J. Sejnowski155845117382
John B. Goodenough1511064113741
Scott Shenker150454118017
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023120
2022499
20214,981
20205,375
20195,420
20184,972