The Experts below are selected from a list of 1164 Experts worldwide ranked by ideXlab platform
Igor Nikiforov - One of the best experts on this subject based on the ideXlab platform.
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Using the Doc2Vec Algorithm to Detect Semantically Similar Jira Issues in the Process of Resolving Customer Requests
Intelligent Distributed Computing XIII, 2020Co-Authors: Artem Kovalev, Nikita Voinov, Igor NikiforovAbstract:The paper is devoted to research in the field of software maintenance automation. An approach to solving customer requests based on the use of the Doc2Vec algorithm is proposed. It consists of finding semantically related resolved requests, as well as identifying qualified software engineers in the Jira Bug Tracking System. The developed software tool implements the proposed approach and provides reports which help software engineers in solving unresolved customer requests. The experiment compares the automated approach to resolving customer requests with the manual one. The results show advantages of using the software tool in the maintenance process.
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IDC - Using the Doc2Vec Algorithm to Detect Semantically Similar Jira Issues in the Process of Resolving Customer Requests.
Intelligent Distributed Computing XIII, 2019Co-Authors: Artem Kovalev, Nikita Voinov, Igor NikiforovAbstract:The paper is devoted to research in the field of software maintenance automation. An approach to solving customer requests based on the use of the Doc2Vec algorithm is proposed. It consists of finding semantically related resolved requests, as well as identifying qualified software engineers in the Jira Bug Tracking System. The developed software tool implements the proposed approach and provides reports which help software engineers in solving unresolved customer requests. The experiment compares the automated approach to resolving customer requests with the manual one. The results show advantages of using the software tool in the maintenance process.
Julian M Bass - One of the best experts on this subject based on the ideXlab platform.
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implementing the required degree of multitenancy isolation a case study of cloud hosted Bug Tracking System
IEEE International Conference on Services Computing, 2016Co-Authors: Laud Charles Ochei, Andrei Petrovski, Julian M BassAbstract:Implementing the required degree of isolation between tenants is one of the significant challenges for deploying a multitenant application on the cloud. In this paper, we applied COMITRE (COmponent-based approach to Multitenancy Isolation Through request RE-routing) to empirically evaluate the degree of isolation between tenants enabled by three multitenancy patterns (i.e., shared component, tenant-isolated component, and dedicated component) for a cloud-hosted Bug Tracking System using Bugzilla. The study revealed among other things that a component deployed based on dedicated component offers the highest degree of isolation (especially for database transactions where support for locking is enabled). Tenant isolation based on performance (e.g., response time) favoured shared component (compared to resource consumption (e.g., CPU and memory) which favoured dedicated component). We also discuss key challenges and recommendations for implementing multitenancy for application components in cloud-hosted Bug Tracking Systems with guarantees for isolation between multiple tenants.
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SCC - Implementing the Required Degree of Multitenancy Isolation: A Case Study of Cloud-Hosted Bug Tracking System
2016 IEEE International Conference on Services Computing (SCC), 2016Co-Authors: Laud Charles Ochei, Andrei Petrovski, Julian M BassAbstract:Implementing the required degree of isolation between tenants is one of the significant challenges for deploying a multitenant application on the cloud. In this paper, we applied COMITRE (COmponent-based approach to Multitenancy Isolation Through request RE-routing) to empirically evaluate the degree of isolation between tenants enabled by three multitenancy patterns (i.e., shared component, tenant-isolated component, and dedicated component) for a cloud-hosted Bug Tracking System using Bugzilla. The study revealed among other things that a component deployed based on dedicated component offers the highest degree of isolation (especially for database transactions where support for locking is enabled). Tenant isolation based on performance (e.g., response time) favoured shared component (compared to resource consumption (e.g., CPU and memory) which favoured dedicated component). We also discuss key challenges and recommendations for implementing multitenancy for application components in cloud-hosted Bug Tracking Systems with guarantees for isolation between multiple tenants.
Kristis Makris - One of the best experts on this subject based on the ideXlab platform.
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scmBug policy based integration of software configuration management with Bug Tracking
USENIX Annual Technical Conference, 2005Co-Authors: Kristis MakrisAbstract:Software configuration management(SCM) and Bug-Tracking are key components of a successful software engineering project. Existing Systems integrating the two have failed to meet the needs of the ASU scalable computing lab, powered by open-source software. An improved solution to the integration problem, designed to accomodate both free and commercial Systems alike, is presented. ScmBug offers a policy-based mechanism of capturing and handling integration of SCM events, such as committing software change-sets and labeling software releases, with a Bug-Tracking System. Synchronous verification checks and the flexibilty to match multiple development models separate this approach from related work. We address design limitations of existing integration efforts, suggest improvements in SCM and Bug-Tracking Systems required to achieve a scalable solution, and document our early integration experiences.
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USENIX Annual Technical Conference, FREENIX Track - ScmBug: policy-based integration of software configuration management with Bug-Tracking
2005Co-Authors: Kristis Makris, Kyung Dong RyuAbstract:Software configuration management(SCM) and Bug-Tracking are key components of a successful software engineering project. Existing Systems integrating the two have failed to meet the needs of the ASU scalable computing lab, powered by open-source software. An improved solution to the integration problem, designed to accomodate both free and commercial Systems alike, is presented. ScmBug offers a policy-based mechanism of capturing and handling integration of SCM events, such as committing software change-sets and labeling software releases, with a Bug-Tracking System. Synchronous verification checks and the flexibilty to match multiple development models separate this approach from related work. We address design limitations of existing integration efforts, suggest improvements in SCM and Bug-Tracking Systems required to achieve a scalable solution, and document our early integration experiences.
Pavneet Singh Kochhar - One of the best experts on this subject based on the ideXlab platform.
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ASE - DupFinder: integrated tool support for duplicate Bug report detection
Proceedings of the 29th ACM IEEE international conference on Automated software engineering - ASE '14, 2014Co-Authors: Ferdian Thung, Pavneet Singh KochharAbstract:To track Bugs that appear in a software, developers often make use of a Bug Tracking System. Users can report Bugs that they encounter in such a System. Bug reporting is inherently an uncoordinated distributed process though and thus when a user submits a new Bug report, there might be cases when another Bug report describing exactly the same problem is already present in the System. Such Bug reports are duplicate of each other and these duplicate Bug reports need to be identified. A number of past studies have proposed a number of automated approaches to detect duplicate Bug reports. However, these approaches are not integrated to existing Bug Tracking Systems. In this paper, we propose a tool named DupFinder, which implements the state-of-the-art unsupervised duplicate Bug report approach by Runeson et al., as a Bugzilla extension. DupFinder does not require any training data and thus can easily be deployed to any project. DupFinder extracts texts from summary and description fields of a new Bug report and recent Bug reports present in a Bug Tracking System, uses vector space model to measure similarity of Bug reports, and provides developers with a list of potential duplicate Bug reports based on the similarity of these reports with the new Bug report. We have released DupFinder as an open source tool in GitHub, which is available at: https://github.com/smagsmu/dupfinder.
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SIGSOFT FSE - BugLocalizer: integrated tool support for Bug localization
Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2014, 2014Co-Authors: Ferdian Thung, Pavneet Singh KochharAbstract:To manage Bugs that appear in a software, developers often make use of a Bug Tracking System such as Bugzilla. Users can report Bugs that they encounter in such a System. Whenever a user reports a new Bug report, developers need to read the summary and description of the Bug report and manually locate the Buggy files based on this information. This manual process is often time consuming and tedious. Thus, a number of past studies have proposed Bug localization techniques to automatically recover potentially Buggy files from Bug reports. Unfortunately, none of these techniques are integrated to Bug Tracking Systems and thus it hinders their adoption by practitioners. To help disseminate research in Bug localization to practitioners, we develop a tool named BugLocalizer, which is implemented as a Bugzilla extension and builds upon a recently proposed Bug localization technique. Our tool extracts texts from summary and description fields of a Bug report and source code files. It then computes similarities of the Bug report with source code files to find the Buggy files. Developers can use our tool online from a Bugzilla web interface by providing a link to a git source code repository and specifying the version of the repository to be analyzed. We have released our tool publicly in GitHub, which is available at: https://github.com/smagsmu/Buglocalizer. We have also provided a demo video, which can be accessed at: http://youtu.be/iWHaLNCUjBY.
Naresh Kumar Nagwani - One of the best experts on this subject based on the ideXlab platform.
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An Open Source Multi Agent System for Data Preprocessing of Online Software Bug Repositories
International Journal of Computer Applications, 2010Co-Authors: Naresh Kumar NagwaniAbstract:Software Bug repositories contain lot of useful information related to software development, software design and software’s common error patterns. Most of the projects use Bug Tracking System to manage the Bugs associated with the software. These Bug Tracking System works as an online Bug repositories, which can be accessed by all of the project members situated at different locations. Researches can also access these online Bug repositories for exploring knowledge from them. In order to extract knowledge from software repositories some preprocessing mechanism is required to extract, parse and save the data locally from these online repository. To address this problem an open source multi agent System is proposed in this paper for the preprocessing of online software defect repositories. The proposed System is also implemented using the open source technologies. Software agents are independent software units and works intelligently and also getting very popular for current and future research, and hence the concepts of agents are included for preprocessing task and multi agent System is implemented. The implementation is done using open source application programming interfaces (API's) and also performance is evaluated for the implementation in terms of Bug data fetch and parse timings.
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weight similarity measurement model based object oriented approach for Bug databases mining to detect similar and duplicate Bugs
International Conference on Autonomic Computing, 2009Co-Authors: Naresh Kumar Nagwani, Pradeep SinghAbstract:In this paper data mining is applied on Bug database to discover the similar and duplicate Bugs. Whenever a new Bug will be entered in the Bug database through Bug Tracking System, it will be matched against the existing Bugs and duplicate and similar Bugs will be mined from the Bug database. Similar kind of Bugs are resolved in almost in same manners. So if a Bug is found somewhere similar to other existing Bug which is already resolved then its resolution will take less time, since some of the Bug analysis part is similar to existing one, hence it will save time. In the existing tradition developers must have to manually identify duplicate Bug reports, but this identification process is time-consuming and exacerbates the already high cost of software maintenance. So if the similar and duplicate Bugs can be found out using some approach it will be a cost and time saving activity. Based on this concept a weight similarity measurement model based object orinted approach is described here in this paper to discover similar and duplicate Bugs in the Bug database.
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An Open Source Framework for Data Pre-processing of Online Software Bug Repositories
Data mining and knowledge engineering, 2009Co-Authors: Naresh Kumar Nagwani, Shrish VermaAbstract:Software Bug repositories are great source of knowledge. It contains lot of useful information related to software development, software design and common error patterns for a software project. Most of the projects uses some Bug Tracking System to manage the Bugs associated with the software. These Bug Tracking System works as an online Bug repositories, which can be accessed by all of the project members situated at different locations. All project members can update and read the software Bug related information from these online Bug repositories. In order to extract knowledge from these online software Bug repositories some mechanism is required to extract, parse and save the data locally for analysis. In this paper a framework is proposed and implemented using open source API’s (Application Programming Interfaces) for the preprocessing of the online software Bug repositories for data mining, also performance is evaluated for the implemented framework in terms of software Bug data fetch and parse timings from online repositories.
