Job Title

Job Description

Category

Computer science, Machine learning

Scope

2 students completing 30 credits each

Background

Our code-base consists of millions of lines of code based on GLIb / GStreamer which is prone to memory leaks. Identifying them as early as possible, preferably at the time of writing the code, is a challenging but very important task. Despite extensive unit testing, regression testing and manual QA testing we sometimes fail to do so.

Considering the importance of our products running continuously at maximum performance and without reboot, a memory leak can easily lead to negative customer experience and spending a lot of time in analysing customer input, debugging sessions and manually reading source before the problem gets eventually fixed. 

Using standard tools such as Coverity, Valgrind and others have often shown for one reason or another, not to be enough. 

Goal

The thesis work should answer the following questions:

• Are there any existing LLM models suitable for this purpose?
• How much training an existing model (with dataset generated, for example, from GTK-Doc comment blocks and code samples) can further improve its abilities to help us discover memory leaks
• and at the same time keep false positive alerts to an acceptable minimum
• Can we integrate such an approach in our daily work

Who are you?

For this Thesis proposal we target students with a strong interest in Machine learning. Most likely you are studying a Master Program in Computer science.

OK, I am interested! What do I do now?
You are valuable to us – how nice that you are interested in one of our proposals! There are a few things for you to keep in mind when applying.

• Applications are accepted in both Swedish and English, and you apply via the proposal advert.
• The announced thesis is open only to students affiliated with a Swedish University/College either directly or via an exchange program.
• When the thesis proposal states that it includes two students working together, we would like you to apply in pairs. In these cases, send one application each but make sure to clearly state in your application who your co-applicant is. If you have any questions regarding this, please do not hesitate to contact us.
• Please attach your CV and University/College grade summary.

Who to contact for any questions regarding the position!

Ognyan Tonchev, ognyan.tonchev@axis.com

Type of Employment

Posting End Date

Certain roles at Axis require background checks, which means applicable verifications will be done in these recruitments. Notice will be provided before we take any action.

About Axis Communications

We enable a smarter, safer world by creating innovative solutions for improving security and business performance. As a network technology company and industry leader, we offer solutions in video surveillance, access control, intercom, and audio systems, enhanced by intelligent analytics applications.

With around 4500 committed employees in over 50 countries, we collaborate with partners worldwide. Together, we thrive in our friendly, open, and collaborative culture and inspire each other to think beyond the expected. United by our commitment to inclusion, diversity, and sustainability, we consistently seek to develop our skills and way of working.

Let´s create a smarter, safer world

For more information about Axis, please visit our website www.axis.com.

Listen to Get To Know Axis – Podcast