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The Global ETD Search service is a free service for researchers
to find electronic theses and dissertations. This service is
provided by the
Networked Digital Library of Theses and Dissertations.
Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
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Showing 1 to 7 of 7 (0.073 seconds)| 1 |
Návrh metodiky řízení a správy incidentů a problémů a jejího využití ve vybrané organizaci / Design of methodology of administration and management of issues and its application in chosen organisationHolub, Adam January 2016 (has links)
This thesis is focused on design methodology of administration and management of issues, using issue-tracking system. The objective is to create such methodology and deploy it to specific organization. During methodology creation, there were used best practices, acquired from source thesis and authors experiences. In theoretical part of thesis are described approaches, witch is this thesis based on. Then thesis describes what issue-tracking system is and lists mostly used issue-tracking systems. In practical part, the methodology itself is created. At first, target group is described. Then, types of issuse and roles used in issue-tracking system are described. Then is described, how to create lifecycle of issue and how to handle with its attributes. Last part is focused on data reporting from issue-tracking system. Last chapter of practical part describes how to implement methodology to issue-tracking system JIRA.
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[en] ISSUENET: A FRAMEWORK FOR COLLABORATIVE TASK ASSESSMENT / [pt] ISSUENET: UM FRAMEWORK PARA AVALIAÇÃO COLABORATIVA DE TAREFASTATIANA ESCOVEDO 19 February 2008 (has links)
[pt] Atualmente, o mercado de trabalho é caracterizado por
globalização, forte
competição, rápidas mudanças, crescente fluxo e
obsolescência de informações e
exigentes padrões de qualidade e de produtividade. Para
acompanhar estas
transformações, portanto, a escola também precisa evoluir
do modelo clássico para a
Aprendizagem Colaborativa, a fim de formar indivíduos
capazes de se comunicar,
trabalhar em grupo na resolução de problemas complexos e
interdisciplinares, coordenar
o trabalho individual e do grupo, e tomar as melhores
decisões. Esta pesquisa investiga
especificamente a avaliação colaborativa em grupos de
trabalho e de aprendizagem, e
propõe o IssueNet, um Framework de colaboração para
acompanhamento e avaliação
colaborativa de tarefas. Para validar a contribuição do
Framework na avaliação
colaborativa, e investigar que outras influências a sua
utilização exerce em grupos de
trabalho ou de aprendizagem, foram realizados dois estudos
de caso com duas instâncias
distintas do IssueNet. Após a análise dos estudos de caso e
dos depoimentos dos
participantes, concluiu-se que o Framework atendeu às
expectativas de possibilitar a
avaliação colaborativa em grupos de trabalho ou
aprendizagem. / [en] Currently, the business market is characterized by
globalization, strong
competition, fast changes, increasing flow and obsolescence
of information and
demanding quality standards and productivity. To follow
these transformations, the
school also needs to evolve from the classical model to
Collaborative Learning, in order
to form individuals capable to communicating, working in
group for the resolution of
complex and interdisciplinary problems, coordinating the
individual work and that of
the group, and taking the best decisions. This research
specifically investigates the
collaborative evaluation in learning and working groups,
and proposes IssueNet, a
collaboration Framework for the management and
collaborative evaluation of tasks. To
validate the contributions brought about by the Framework,
and to investigate what
other influences it may have on learning or working groups,
two case-studies using two
distinct IssueNet instances have been carried through.
After the analysis of the casestudies
and of the based on the comments of the participants, we
have concluded that
the Framework satisfies our expectations by making it
possible the collaborative
evaluation in learning or working groups.
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Robust Issue Tracking Application (RITA) : Developing an issue tracker using modern web technologiesÅhman, Stefan January 2017 (has links)
Issue tracking is one of the vital parts in maintaining computer systems. It is utilized in anything from small independent companies to large enterprises. The tracking does not just provide developers and other personnel with crucial information regarding their systems current state, but additionally stores useful documentation if any error reoccurs in the future. However, if the tracking issue would be deficient in some way, the complete process of developing or maintaining a system could affected negatively in great extent. This thesis work has looked into a scenario where the tool has been to slow, overly complicated and obsolete. It has made a large negative impact on the work force that uses the tool and made tracking issue to a discouragement. The thesis work has thence investigated features of the existing tool, suggested a better solution to use based upon these findings, followed by the development of a web application. When the application was finished, its usability was tested by the intended staff and performance tests were conducted. The test results showed that the application had been implemented successfully in many aspects. Unfortunately, due to deficient technical choices, the project did struggle with implementing all features as expected. The thesis work did consequently learn the hard way the importance of a choosing development techniques very thoroughly.
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A GitHub-Based Voice Assistant for Software Developers and TeamsSereesathien, Siriwan 01 June 2021 (has links) (PDF)
Software developers and teams typically rely on source code and tasks management tools for their projects. They tend to depend on different platforms such as GitHub, Azure DevOps, Bitbucket, and GitLab for task-tracking, feature-tracking, and bug-tracking to develop and maintain their software repositories. Individually, developers may lose concentration when having to navigate through numerous screens consisting of various platforms to perform daily tasks. Additionally, while in meetings (non-virtual), teams are often separate from their machines and often would have to rely on pure recollection of the tasks and issues related to their work. This can delay the decision-making process and take away valuable focus hours of developers. Although there is usually one person with their laptop to guide the meeting and has access to the source code management tools, this can take a lot of time as they are not familiar with all the developers’ independent works. Therefore, a new tool needs to be introduced to help accelerate individual and team meetings’ productivity. In this paper, we continued the work on Robin, a voice-assistant built to answer questions regarding GitHub issues and source code management. Robin has the ability to answer questions in addition to completing actions on the behalf of the developer. This thesis presents Robin's abilities, architecture, and implementation while also examining its usability through a user study. Our study suggests that some people love the idea of having a conversational agent for software development. However, a lot more research and iterations must be done to fully make Robin give the user experience we imagined. In this thesis, we were able to set the foundation of this idea and the lessons that we learned.
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Design of information tree for support related queries: Axis Communications AB : An exploratory research study in debug suggestions with machine learning at Axis Communications, Lund / Utformning av informationsträd för supportrelaterade frågor: Axis Communications AB : En utforskande forskningsstudie i felsökningsförslag med maskininlärning vid Axis Communications, LundRangavajjula, Santosh Bharadwaj January 2017 (has links)
Context: In today's world, we have access to so much data than at any time in the past with more and more data coming from smartphones, sensors networks, and business processes. But, most of this data is meaningless, if it's not properly formatted and utilized. Traditionally, in service support teams, issues raised by customers are processed locally, made reports and sent over in the support line for resolution. The resolution of the issue then depends on the expertise of the technicians or developers and their experience in handling similar issues which limits the size, speed, and scale of the problems that can be resolved. One solution to this problem is to make relevant information tailored to the issue under investigation to be easily available. Objectives: The focus of the thesis is to improve turn around time of customer queries using recommendations and evaluate by defining metrics in comparison to existing workflow. As Artificial Intelligence applications can have a broad spectrum, we confine the scope with a relevance in software service and Issue Tracking Systems. Software support is a complicated process as it involves various stakeholders with conflicting interests. During the course of this literary work, we are primarily interested in evaluating different AI solutions specifically in the customer support space customize and compare them. Methods: The following thesis work has been carried out by making controlled experiments using different datasets and Machine learning models. Results: We classified Axis data and Bugzilla (eclipse) using Decision Trees, K Nearest Neighbors, Neural Networks, Naive Bayes and evaluated them using precision, recall rate, and F-score. K Nearest Neighbors was having precision 0.11, recall rate 0.11, Decision Trees had precision 0.11, recall rate 0.11, Neural Networks had precision 0.13, recall rate 0.11 and Naive Bayes had precision 0.05, recall rate 0.11. The result shows too many false positives and true negatives for being able to recommend. Conclusions: In this Thesis work, we have gone through 33 research articles and synthesized them. Existing systems in place and the current state of the art is described. A debug suggestion tool was developed in python with SKlearn. Experiments with different Machine Learning models are run on the tool and highest 0.13 (precision), 0.10 (f-score), 0.11 (recall) are observed with MLP Classification Neural Network.
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Implementace Application Lifecycle Mangement systému pro využití v nesoftwarových projektech ve firmě Audatex Systems s.r.o. / Implementing Application Lifecycle Management system for non-software projects usage in Audatex Systems s.r.o.Hlobil, Lukáš January 2012 (has links)
This thesis describes implementation process of issue tracking systém in company Audatex Systems s.r.o. An analysis of company's processes has been performed and ideal state after implementation is proposed. The implemented system is going to be used not only for software defect tracking, but also for company's other needs like project management and internal communication. Output of company's analysis is a list of requirements for said system and a tender is performed -- along with setting up of test environments. Process of implementation and configuration is described along with experience from implementation proces. Each of shotlisted applications is configured for company's specific needs and is evaluated with an evaluation systém, that has been created for this specific tender. Situation after implementation is descibed in conclusion of this thesis. Main benefit of this thesis lies in comparision of applications and presenting their configurations for company's needs. Two free solutions are compared along with a comercial one. In conclusion this thesis answers a question, whether a comercial solution is really needed for this specific case.
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Tuning of machine learning algorithms for automatic bug assignmentArtchounin, Daniel January 2017 (has links)
In software development projects, bug triage consists mainly of assigning bug reports to software developers or teams (depending on the project). The partial or total automation of this task would have a positive economic impact on many software projects. This thesis introduces a systematic four-step method to find some of the best configurations of several machine learning algorithms intending to solve the automatic bug assignment problem. These four steps are respectively used to select a combination of pre-processing techniques, a bug report representation, a potential feature selection technique and to tune several classifiers. The aforementioned method has been applied on three software projects: 66 066 bug reports of a proprietary project, 24 450 bug reports of Eclipse JDT and 30 358 bug reports of Mozilla Firefox. 619 configurations have been applied and compared on each of these three projects. In production, using the approach introduced in this work on the bug reports of the proprietary project would have increased the accuracy by up to 16.64 percentage points.
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