Inlämning av Examensarbete / Submission of Thesis

Denis Kacan; Darius Sidlauskas MSE-2008-09, pp. 43. TEK/avd. för programvaruteknik, 2008.

The work

Författare / Author: Denis Kacan, Darius Sidlauskas,
Titel / Title: Information Visualization and Machine Learning Applied on Static Code Analysis
Abstrakt Abstract:

Software engineers will possibly never see the perfect source code in their lifetime, but they are seeing much better analysis tools for finding defects in software. The approaches used in static code analysis emerged from simple code crawling to usage of statistical and probabilistic frameworks. This work presents a new technique that incorporates machine learning and information visualization into static code analysis. The technique learns patterns in a program’s source code using a normalized compression distance and applies them to classify code fragments into faulty or correct. Since the classification frequently is not perfect, the training process plays an essential role. A visualization element is used in the hope that it lets the user better understand the inner state of the classifier making the learning process transparent.
An experimental evaluation is carried out in order to prove the efficacy of an implementation of the technique, the Code Distance Visualizer. The outcome of the evaluation indicates that the proposed technique is reasonably effective in learning to differentiate between faulty and correct code fragments, and the visualization element enables the user to discern when the tool is correct in its output and when it is not, and to take corrective action (further training or retraining) interactively, until the desired level of performance is reached.

Ämnesord / Subject: Datavetenskap - Computer Science\Software Engineering

Nyckelord / Keywords: Software validation, static analyzer, normalized compression distance, source code visualization

Publication info

Dokument id / Document id:
Program:/ Programme Masterprogram i Software engineering 120 p/Master´s program in Software engineering 120 p
Registreringsdatum / Date of registration: 06/28/2008
Uppsatstyp / Type of thesis: Masterarbete/Master's Thesis (120 credits)


Handledare / Supervisor: Stefan Axelsson
Examinator / Examiner: Robert Feldt
Organisation / Organisation: Blekinge Institute of Technology
Institution / School: TEK/avd. för programvaruteknik
S-372 25 Ronneby
+46 455 38 50 00

Files & Access

Bifogad uppsats fil(er) / Files attached: thesis_mse_2008_09.pdf (1164 kB, öppnas i nytt fönster)