Sökning: "Just-in-Time Software Defect Prediction"

Hittade 3 uppsatser innehållade orden Just-in-Time Software Defect Prediction.

  1. 1. Evaluation of Attention Mechanisms for Just-In-Time Software Defect Prediction

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Abgeiba Yaroslava Isunza Navarro; [2020]
    Nyckelord :Just-in-Time Software Defect Prediction; Attention Mechanism; Convolutional Neural Network; Feature Extraction; Just-in-Time Software Defect Prediction; Attention Mechanism; Convolutional Neural Network; Feature Extraction;

    Sammanfattning : Just-In-Time Software Defect Prediction (JIT-DP) focuses on predicting errors in software at change-level with the objective of helping developers identify defects while the development process is still ongoing, and improving the quality of software applications. This work studies deep learning techniques by applying attention mechanisms that have been successful in, among others, Natural Language Processing (NLP) tasks. LÄS MER

  3. 2. Just-In-Time Software Defect Prediction using version control tool based software metrics and source code embeddings

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Christopher Dahlén; [2019]
    Nyckelord :;

    Sammanfattning : Software development is a multifactorial process. Its complexity has made it challenging to study the circumstances that underlie efficient software development. However, a better understanding of these factors will reduce the long-term costs of software development. LÄS MER

  4. 3. Investigating the Practicality of Just-in-time Defect Prediction with Semi-supervised Learning on Industrial Commit Data

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Arsalan Syed; [2019]
    Nyckelord :;

    Sammanfattning : Some of the challenges faced with Just-in-time defect (JIT) prediction are achieving high performing models and obtaining large quantities of labelled data. There is also a limited number of studies that actually test the effectiveness of software defect prediction models in practice. LÄS MER