Inlämning av Examensarbete / Submission of Thesis

Irene Moriggl MSE-2010-17, pp. 54. COM/School of Computing, 2010.

The work

Författare / Author: Irene Moriggl
irenemoriggl@gmail.com
Titel / Title: Intelligent Code Inspection using Static Code Features - An approach for Java
Abstrakt Abstract:

Effective defect detection is still a hot issue when it comes to software quality assurance. Static source code analysis plays thereby an important role, since it offers the possibility for automated defect detection in early stages of the development. As detecting defects can be seen as a classification problem, machine learning is recently investigated to be used for this purpose. This study presents a new model for automated defect detection by means of machine learn- ers based on static Java code features. The model comprises the extraction of necessary features as well as the application of suitable classifiers to them. It is realized by a prototype for the feature extraction and a study on the prototype’s output in order to identify the most suitable classifiers. Finally, the overall approach is evaluated in a using an open source project. The suitability study and the evaluation show, that several classifiers are suitable for the model and that the Rotation Forest, Multilayer Perceptron and the JRip classifier make the approach most effective. They detect defects with an accuracy higher than 96%. Although the approach comprises only a prototype, it shows the potential to become an effective alternative to nowa- days defect detection methods.

Ämnesord / Subject: Datavetenskap - Computer Science\Software Engineering

Nyckelord / Keywords: Java, Static Source Code Analysis, Machine Learning, Automated Defect Detection

Publication info

Dokument id / Document id:
Program:/ Programme European Master on Software Engineering
Registreringsdatum / Date of registration: 09/22/2010
Uppsatstyp / Type of thesis: Masterarbete/Master's Thesis (120 credits)

Context

Handledare / Supervisor: Dr. Stefan Axelsson
Examinator / Examiner: Dr. Tony Gorschek
Organisation / Organisation: Blekinge Institute of Technology
Institution / School: COM/School of Computing

+46 455 38 50 00

Files & Access

Bifogad uppsats fil(er) / Files attached: bth-irmo-thesis.pdf (1167 kB, öppnas i nytt fönster)