One Computer Science MSc thesis to be presented on 4 April

Thursday, 4 April there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering. See also this page for three more presentations: https://cs.lth.se/kalendarium/?evenemang=three-more-cs-msc-thesis-presentations-4-april-2024

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.lastname@cs.lth.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 are found on this page.

11:15-12:00 in E:2116

Presenters: Sean Jentz, Karolina Haara Löfstedt
Title: Representing and Classifying Diff of Hierarchically Dependent Queries to a Graph Database
Examiner: Per Andersson
Supervisors: Lars Bendix (LTH), Anton Berghult (InfraSight Labs AB)

Queries in vScope fetch data from a graph database. This data is then transformed and displayed in various formats. The queries are structured hierarchically and are implemented as interdependent XML-formatted files. The files are contained in Git repositories and change requests are currently reviewed by developers with Git in a text-based format. InfraSight Labs wants to simplify the process around query configuration in order to enable non-developers to take over the task. This thesis investigates the possibility of a tool that can catch changes to queries and visualize them at a higher level of abstraction than the diff function provided by Git. We found that we can detect and classify changes to queries and their dependencies with the use of reflection and persisting annotations. This is exemplified with a proof of concept diffing tool. The tool serialized Java objects from XML-files and compared them using reflection, then used annotations provided to the fields to classify the impact of a change. The conclusion is that it is possible to represent changes made to query files at a higher level of abstraction than the text based Git diff function. Integrating the tool into the current product is left for future work.

Link to popular science summary: To be uploaded