Essays about: "Felrapporter"

Showing result 1 - 5 of 9 essays containing the word Felrapporter.

  1. 1. Duplicate detection of multimodal and domain-specific trouble reports when having few samples : An evaluation of models using natural language processing, machine learning, and Siamese networks pre-trained on automatically labeled data

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Viktor Karlstrand; [2022]
    Keywords : Duplicate detection; Bug reports; Trouble reports; Natural language processing; Information retrieval; Machine learning; Siamese neural network; Transformers; Automated data labeling; Shapley values; Dubblettdetektering; Felrapporter; Buggrapporter; Naturlig språkbehandling; Informationssökning; Maskininlärning; Siamesiska neurala nätverk; Transformatorer; Automatiserad datamärkning; Shapley-värden;

    Abstract : Trouble and bug reports are essential in software maintenance and for identifying faults—a challenging and time-consuming task. In cases when the fault and reports are similar or identical to previous and already resolved ones, the effort can be reduced significantly making the prospect of automatically detecting duplicates very compelling. READ MORE

  3. 2. Integrating Telecommunications-Specific Language Models into a Trouble Report Retrieval Approach

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Nathan Bosch; [2022]
    Keywords : information retrieval; neural ranking; trouble reports; log analysis; natural language processing; informationssökning; neural rangordning; felrapporter; logganalys; naturlig språkbehandling;

    Abstract : In the development of large telecommunications systems, it is imperative to identify, report, analyze and, thereafter, resolve both software and hardware faults. This resolution process often relies on written trouble reports (TRs), that contain information about the observed fault and, after analysis, information about why the fault occurred and the decision to resolve the fault. READ MORE

  4. 3. Natural Language Processing Model for Log Analysis to Retrieve Solutions For Troubleshooting Processes

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Núria Marzo i Grimalt; [2021]
    Keywords : Trouble Report; Recommender System; BERT; Information Retrieval; Natural Language Processing; Multi-Stage Ranking; Felrapporter; Rekommendatorsystem; BERT; Informationsinhämtning; Naturlig Språkbehandling; Dubbelriktade Ranking;

    Abstract : In the telecommunications industry, one of the most time-consuming tasks is troubleshooting and the resolution of Trouble Report (TR) tickets. This task involves the understanding of textual data which can be challenging due to its domain- and company-specific features. READ MORE

  5. 4. Grouping Similar Bug Reports from Crash Dumps with Unsupervised Learning

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Sara Vestergren; [2021]
    Keywords : Unsupervised Learning; Bug Report; Duplicate Detection; Clustering; Software Crash; Oövervakad Inlärning; Felrapport; Dublett-detektering; Klustring; Mjukvarukrasch;

    Abstract : Quality software usually means high reliability, which in turn has two main components; the software should provide correctness, which means it should perform the specified task, and robustness in the sense that it should be able to manage unexpected situations. In other words, reliable systems are systems without bugs. READ MORE

  6. 5. Developing a Simplified and Consistent Defect Taxonomy for Smaller Enterprises

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Johanna Iivanainen; [2021]
    Keywords : Defect Taxonomy; Defect Classification; Small- and Medium-sized Enterprises; Software Defects; Manual Defect Classification.; Defekttaxonomi; Defektklassifikation; Små och medelstora företag; Mjukvarufel; Manuell defektklassificering.;

    Abstract : Developing software that meets the customers’ requirements, expectations, and quality standards is a challenging task for all software organizations. As modern software becomes more and more complex, so do the defects of the software. READ MORE