The Experts below are selected from a list of 36291 Experts worldwide ranked by ideXlab platform

Martin P. Robillard - One of the best experts on this subject based on the ideXlab platform.

  • ICSE - Temporal analysis of API usage concepts
    2012 34th International Conference on Software Engineering (ICSE), 2012
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. The functionality offered by an API is not always accessed uniformly throughout the lifetime of a Client Program. We propose Temporal API Usage Pattern Mining to detect API usage patterns in terms of their time of introduction into Client Programs. We detect concepts as distinct groups of API functionality from the change history of a Client Program. We locate those concepts in the Client change history and detect temporal usage patterns, where a pattern contains a set of concepts that were added into the Client Program in a specific temporal order. We investigated the properties of temporal API usage patterns through a multiple-case study of three APIs and their use in up to 19 Client software projects. Our technique was able to detect a number of valuable patterns in two out of three of the APIs investigated. Further investigation showed some patterns to be relatively consistent between Clients, produced by multiple developers, and not trivially derivable from Program structure or API documentation.

  • ASE - Analyzing temporal API usage patterns
    2011 26th IEEE ACM International Conference on Automated Software Engineering (ASE 2011), 2011
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. As developers write Client Programs, their understanding and usage of APIs change over time. Can we learn from long-term changes in how developers work with APIs in the lifetime of a Client Program? We propose Temporal API Usage Mining to detect significant changes in API usage. We describe a framework to extract detailed models representing addition and removal of calls to API methods over the change history of a Client Program. We apply machine learning technique to these models to semi-automatically infer temporal API usage patterns, i.e., coherent addition of API calls at different phases in the life-cycle of the Client Program.

  • Recommending Adaptive Changes for Framework Evolution
    ACM Transactions on Software Engineering and Methodology, 2011
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    In the course of a framework’s evolution, changes ranging from a simple refactoring to a complete rearchitecture can break Client Programs. Finding suitable replacements for framework elements that were accessed by a Client Program and deleted as part of the framework’s evolution can be a challenging task. We present a recommendation system, SemDiff, that suggests adaptations to Client Programs by analyzing how a framework was adapted to its own changes. In a study of the evolution of one open source framework and three Client Programs, our approach recommended relevant adaptive changes with a high level of precision. In a second study of the evolution of two frameworks, we found that related change detection approaches were better at discovering systematic changes and that SemDiff was complementary to these approaches by detecting non-trivial changes such as when a functionality is imported from an external library.

  • ICSE - SemDiff: Analysis and recommendation support for API evolution
    2009 IEEE 31st International Conference on Software Engineering, 2009
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    As a framework evolves, changes in its Application Programming Interface (API) can break Client Programs that extend the framework. Repairing a Client Program can be a challenging task because developers need to understand the context surrounding the API change. This paper describes SemDiff, a tool that recommends replacements for framework methods that were accessed by a Client Program and deleted during the evolution of the framework. SemDiff recommends replacements for non-trivial changes undiscovered by other change-detection techniques and also enables developers to look at the context of the changes that led to the deletion of a framework method.

  • ICSE - Recommending adaptive changes for framework evolution
    Proceedings of the 13th international conference on Software engineering - ICSE '08, 2008
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    In the course of a framework's evolution, changes ranging from a simple refactoring to a complete rearchitecture can break Client Programs. Finding suitable replacements for framework elements that were accessed by a Client Program and deleted as part of the framework's evolution can be a challenging task. We present a recommendation system, SemDiff, that suggests adaptations to Client Programs by analyzing how a framework adapts to its own changes. In a study of the evolution of the Eclipse JDT framework and three Client Programs, our approach recommended relevant adaptive changes with a high level of precision, and detected non-trivial changes typically undiscovered by current refactoring detection techniques.

Gias Uddin - One of the best experts on this subject based on the ideXlab platform.

  • ICSE - Temporal analysis of API usage concepts
    2012 34th International Conference on Software Engineering (ICSE), 2012
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. The functionality offered by an API is not always accessed uniformly throughout the lifetime of a Client Program. We propose Temporal API Usage Pattern Mining to detect API usage patterns in terms of their time of introduction into Client Programs. We detect concepts as distinct groups of API functionality from the change history of a Client Program. We locate those concepts in the Client change history and detect temporal usage patterns, where a pattern contains a set of concepts that were added into the Client Program in a specific temporal order. We investigated the properties of temporal API usage patterns through a multiple-case study of three APIs and their use in up to 19 Client software projects. Our technique was able to detect a number of valuable patterns in two out of three of the APIs investigated. Further investigation showed some patterns to be relatively consistent between Clients, produced by multiple developers, and not trivially derivable from Program structure or API documentation.

  • ASE - Analyzing temporal API usage patterns
    2011 26th IEEE ACM International Conference on Automated Software Engineering (ASE 2011), 2011
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. As developers write Client Programs, their understanding and usage of APIs change over time. Can we learn from long-term changes in how developers work with APIs in the lifetime of a Client Program? We propose Temporal API Usage Mining to detect significant changes in API usage. We describe a framework to extract detailed models representing addition and removal of calls to API methods over the change history of a Client Program. We apply machine learning technique to these models to semi-automatically infer temporal API usage patterns, i.e., coherent addition of API calls at different phases in the life-cycle of the Client Program.

Xiangguang Chen - One of the best experts on this subject based on the ideXlab platform.

  • Research and application of online measurement system of tire tread profile in automobile tire production
    Seventh International Conference on Electronics and Information Engineering, 2017
    Co-Authors: Pengyao Wang, Xiangguang Chen, Kai Yang, Xuejiao Liu
    Abstract:

    To improve the measuring efficiency of width and thickness of tire tread in the process of automobile tire production, the actual condition for the tire production process is analyzed, and a fast online measurement system based on moving tire tread of tire specifications is established in this paper. The coordinate data of tire tread profile is acquired by 3D laser sensor, and we use C# language for Programming which is an object-oriented Programming language to complete the development of Client Program. The system with laser sensor can provide real-time display of tire tread profile and the data to require in the process of tire production. Experimental results demonstrate that the measuring precision of the system is ≤ 1mm, it can meet the measurement requirements of the production process, and the system has the characteristics of convenient installation and testing, system stable operation.

  • Research and Application of PIMS in Automobile Tire Tread Production
    Proceedings of the 5th International Conference on Information Engineering for Mechanics and Materials, 2015
    Co-Authors: Na Liu, Kai Yang, Xiangguang Chen
    Abstract:

    In order to improve the information management level in the process of automobile tire tread production, the actual condition for the tire production process is analyzed in this paper. The information management system of the extruding line in the process of automobile tire tread manufacturing is designed based on combination of B/S and C/S models. The system uses a large-scale distributed database SQL Server 2008 R2 as the underlying database, the C/S section uses visual studio 2012 as a development tool, .NET Framework 4.5 for development environment, C# language for Programming which is an object-oriented Programming language to complete the development of the Client Program. The B/S section uses the Apache server as a web server, the popular web authoring tool Dreamweaver as a development tool, and PHP language as the Programming language to complete the Program. The application results in real field show that the information management system proposed in this paper based on the combination of C/S and B/S models can meet the needs of automobile tire production process, and the process information management system has good application value.

Barthélémy Dagenais - One of the best experts on this subject based on the ideXlab platform.

  • ICSE - Temporal analysis of API usage concepts
    2012 34th International Conference on Software Engineering (ICSE), 2012
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. The functionality offered by an API is not always accessed uniformly throughout the lifetime of a Client Program. We propose Temporal API Usage Pattern Mining to detect API usage patterns in terms of their time of introduction into Client Programs. We detect concepts as distinct groups of API functionality from the change history of a Client Program. We locate those concepts in the Client change history and detect temporal usage patterns, where a pattern contains a set of concepts that were added into the Client Program in a specific temporal order. We investigated the properties of temporal API usage patterns through a multiple-case study of three APIs and their use in up to 19 Client software projects. Our technique was able to detect a number of valuable patterns in two out of three of the APIs investigated. Further investigation showed some patterns to be relatively consistent between Clients, produced by multiple developers, and not trivially derivable from Program structure or API documentation.

  • ASE - Analyzing temporal API usage patterns
    2011 26th IEEE ACM International Conference on Automated Software Engineering (ASE 2011), 2011
    Co-Authors: Gias Uddin, Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    Software reuse through Application Programming Interfaces (APIs) is an integral part of software development. As developers write Client Programs, their understanding and usage of APIs change over time. Can we learn from long-term changes in how developers work with APIs in the lifetime of a Client Program? We propose Temporal API Usage Mining to detect significant changes in API usage. We describe a framework to extract detailed models representing addition and removal of calls to API methods over the change history of a Client Program. We apply machine learning technique to these models to semi-automatically infer temporal API usage patterns, i.e., coherent addition of API calls at different phases in the life-cycle of the Client Program.

  • Recommending Adaptive Changes for Framework Evolution
    ACM Transactions on Software Engineering and Methodology, 2011
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    In the course of a framework’s evolution, changes ranging from a simple refactoring to a complete rearchitecture can break Client Programs. Finding suitable replacements for framework elements that were accessed by a Client Program and deleted as part of the framework’s evolution can be a challenging task. We present a recommendation system, SemDiff, that suggests adaptations to Client Programs by analyzing how a framework was adapted to its own changes. In a study of the evolution of one open source framework and three Client Programs, our approach recommended relevant adaptive changes with a high level of precision. In a second study of the evolution of two frameworks, we found that related change detection approaches were better at discovering systematic changes and that SemDiff was complementary to these approaches by detecting non-trivial changes such as when a functionality is imported from an external library.

  • ICSE - SemDiff: Analysis and recommendation support for API evolution
    2009 IEEE 31st International Conference on Software Engineering, 2009
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    As a framework evolves, changes in its Application Programming Interface (API) can break Client Programs that extend the framework. Repairing a Client Program can be a challenging task because developers need to understand the context surrounding the API change. This paper describes SemDiff, a tool that recommends replacements for framework methods that were accessed by a Client Program and deleted during the evolution of the framework. SemDiff recommends replacements for non-trivial changes undiscovered by other change-detection techniques and also enables developers to look at the context of the changes that led to the deletion of a framework method.

  • ICSE - Recommending adaptive changes for framework evolution
    Proceedings of the 13th international conference on Software engineering - ICSE '08, 2008
    Co-Authors: Barthélémy Dagenais, Martin P. Robillard
    Abstract:

    In the course of a framework's evolution, changes ranging from a simple refactoring to a complete rearchitecture can break Client Programs. Finding suitable replacements for framework elements that were accessed by a Client Program and deleted as part of the framework's evolution can be a challenging task. We present a recommendation system, SemDiff, that suggests adaptations to Client Programs by analyzing how a framework adapts to its own changes. In a study of the evolution of the Eclipse JDT framework and three Client Programs, our approach recommended relevant adaptive changes with a high level of precision, and detected non-trivial changes typically undiscovered by current refactoring detection techniques.

Gregory L Fenves - One of the best experts on this subject based on the ideXlab platform.

  • software framework for distributed experimental computational simulation of structural systems
    Earthquake Engineering & Structural Dynamics, 2006
    Co-Authors: Yoshikazu Takahashi, Gregory L Fenves
    Abstract:

    SUMMARY Supported by the recent advancement of experimental test methods, numerical simulation, and high-speed communication networks, it is possible to distribute geographically the testing of structural systems using hybrid experimental-computational simulation. One of the barriers for this advanced testing is the lack ofexible software for hybrid simulation using heterogeneous experimental equipment. To address this need, an object-oriented software framework is designed, developed, implemented, and demonstrated for distributed experimental-computational simulation of structural systems. The software computes the imposed displacements for a range of test methods and co-ordinates the control of local and distributed congurations of experimental equipment. The object-oriented design of the software promotes the sharing of modules for experimental equipment, test set-ups, simulation models, and test methods. The communication model for distributed hybrid testing is similar to that used for parallel computing to solve structural simulation problems. As a demonstration, a distributed pseudodynamic test was conducted using a Client-server approach, in which the server Program controlled the test equipment in Japan and the Client Program performed the computational simulation in the United States. The distributed hybrid simulation showed that the software framework isexible and reliable. Copyright ? 2005 John Wiley & Sons, Ltd.