jan
CS MSc Thesis Presentation 16 January 2026
One Computer Science MSc thesis to be presented on 16 January
Friday, 16 January there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.
The presentation will take place in E:2116.
Note to potential opponents: Register as an opponent to the presentation of your choice by sending an email to the examiner for that presentation (firstname [dot] lastname [at] cs [dot] lth [dot] se). Do not forget to specify the presentation you register for! Note that the number of opponents may be limited (often to two), so you might be forced to choose another presentation if you register too late. Registrations are individual, just as the oppositions are! More instructions for opponents are found here on the LTH thesis project page.
15:15-16:00 in E:2116
- Presenters: Fredrik Wastring, Björn Tenje Persson
- Title: Early defect detection through ephemeral preview environments
- Examiner: Sule Tekkesinoglu
- Supervisor: Ulf Asklund (LTH), Sebastian Nordin (iFACTS AB), Malin Jeppsson (iFACTS AB)
Ephemeral preview environments (EPEs) enable production-like validation in trunk-based development workflows but are rarely studied in highly configurable, customer-specific software. This thesis presents a case study at iFACTS AB, where limitations in local development and shared staging environments contributed to defects reaching production. To address this, a preview-environment platform was designed and implemented, including a web portal, GitOps-based orchestration using Argo CD, Kubernetes, and Helm, and curated customer dataset templates. A new workflow was introduced with a pre-merge “preview gate” requiring branch-specific deployments with representative data before merging to trunk. The solution was evaluated using an embedded mixed-method approach, combining Technology Acceptance Model constructs to assess adoption and PERT-based estimates to quantify avoided rework. Developers and QA reported high confidence in usability and setup, with minor concerns about dataset freshness and UI issues. Across three cases, the evaluation indicated an average reduction of rework effort of approximately 48 percent per story, suggesting earlier defect detection through EPEs.
Om evenemanget
Plats:
E:2116
Kontakt:
birger [dot] swahn [at] cs [dot] lth [dot] se