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Object-oriented design

About: Object-oriented design is a research topic. Over the lifetime, 5136 publications have been published within this topic receiving 144108 citations.


Papers
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Book ChapterDOI
25 Sep 1995
TL;DR: In the course of this discussion which recurs to commonly accepted frameworks in measure theory, both, well-known attributes and new proposals are treated.
Abstract: The role of internal product attributes for software measures is analyzed. Attributes are classified as “fundamental”, “auxiliary” and “useless” with respect to their relevance for controlling software quality. The impact of inappropriate attributes on the usefulness of resulting metrics is discussed with emphasis on the object-oriented paradigm. We demonstrate that some of the obvious shortcomings of proposed metrics are caused by inconsiderate attribute selections. In the course of this discussion which recurs to commonly accepted frameworks in measure theory, both, well-known attributes and new proposals are treated.

44 citations

Patent
Alex Colburn1, Steven M. Drucker1, Kirk J. Marple1, Donald P. Mitchell1, Manny Vellon1 
24 Feb 1998
TL;DR: A software object security mechanism addresses system security risks that arise due to interactions between software objects as mentioned in this paper, where conditions are imposed on the accessing of targets by accessing object instances according to attributes of the accessing object and the target object that is being accessed.
Abstract: A software object security mechanism addresses system security risks that arise due to interactions between software objects. Conditions are imposed on the accessing of targets by accessing object instances according to attributes of the accessing object and the target object that is being accessed. One security feature is that an owner identifier is incorporated into objects. The owner identifier includes identification of the user, person, or entity (e.g., corporation) who or that creates the object, or identification of a computer system used by the user, person, or entity to create the object definition. The owner identifier provides a basis for distinguishing the creator of an object from the user of that object. Another security feature is a set of access authorizations that allow different access rights to be made available to different object creators. In one implementation the access authorizations are All, Owner, and Exemplar. Another security feature is that exemplar identifiers are encoded into properties and methods in which the properties and methods are defined. Since exemplars may be authored by anyone and may be changed at run time, these security features insure that inheritance from exemplars of questionable lineage is safe. These security features prevent an exemplar in the hierarchy for an object or object instance from damaging the instance data.

44 citations

Journal ArticleDOI
TL;DR: This is the first work to jointly explore the view-based and model-based relevance among the 3D objects in a graph-based framework and demonstrates the effectiveness on retrieval accuracy of the proposed 3D object retrieval method.
Abstract: 3D object retrieval has attracted extensive research efforts and become an important task in recent years. It is noted that how to measure the relevance between 3D objects is still a difficult issue. Most of the existing methods employ just the model-based or view-based approaches, which may lead to incomplete information for 3D object representation. In this paper, we propose to jointly learn the view-model relevance among 3D objects for retrieval, in which the 3D objects are formulated in different graph structures. With the view information, the multiple views of 3D objects are employed to formulate the 3D object relationship in an object hypergraph structure. With the model data, the model-based features are extracted to construct an object graph to describe the relationship among the 3D objects. The learning on the two graphs is conducted to estimate the relevance among the 3D objects, in which the view/model graph weights can be also optimized in the learning process. This is the first work to jointly explore the view-based and model-based relevance among the 3D objects in a graph-based framework. The proposed method has been evaluated in three data sets. The experimental results and comparison with the state-of-the-art methods demonstrate the effectiveness on retrieval accuracy of the proposed 3D object retrieval method.

44 citations

Journal ArticleDOI
TL;DR: An efficient approach capable of learning and recognizing object categories in an interactive and open-ended manner, which is able to interact with human users, learning new object categories continuously over time is presented.
Abstract: 3D object detection and recognition is increasingly used for manipulation and navigation tasks in service robots. It involves segmenting the objects present in a scene, estimating a feature descriptor for the object view and, finally, recognizing the object view by comparing it to the known object categories. This paper presents an efficient approach capable of learning and recognizing object categories in an interactive and open-ended manner. In this paper, “open-ended” implies that the set of object categories to be learned is not known in advance. The training instances are extracted from on-line experiences of a robot, and thus become gradually available over time, rather than at the beginning of the learning process. This paper focuses on two state-of-the-art questions: (1) How to automatically detect, conceptualize and recognize objects in 3D scenes in an open-ended manner? (2) How to acquire and use high-level knowledge obtained from the interaction with human users, namely when they provide category labels, in order to improve the system performance? This approach starts with a pre-processing step to remove irrelevant data and prepare a suitable point cloud for the subsequent processing. Clustering is then applied to detect object candidates, and object views are described based on a 3D shape descriptor called spin-image. Finally, a nearest-neighbor classification rule is used to predict the categories of the detected objects. A leave-one-out cross validation algorithm is used to compute precision and recall, in a classical off-line evaluation setting, for different system parameters. Also, an on-line evaluation protocol is used to assess the performance of the system in an open-ended setting. Results show that the proposed system is able to interact with human users, learning new object categories continuously over time.

44 citations

Patent
01 Aug 2001
TL;DR: In this article, a system for integrating object changes occurring to an object in a first-object storage system with a second object storage system is presented. But the system operates by first receiving from a first object storage systems a notification of an event relating to an objects in the first-Object storage system, and then sets up a representation of the object in the second-Object Storage System in response to the notification and determines object changes made to the object made by using the representation in the Second-Object System (SOS).
Abstract: A system for integrating object changes occurring to an object in a first object storage system with a second object storage system The system operates by first receiving from a first object storage systems a notification of an event relating to an object in the first object storage system The system sets up a representation of the object in a second object storage system in response to the notification and determines object changes made to the object in the first object storage system by using the representation in the second object storage system Finally, the system determines object changes with the representation in the second storage system

43 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231
20226
20215
20209
201915
201828