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CS MSc Thesis Zoom Presentation 23 September 2021

Föreläsning

Tid: 2021-09-23 13:00 till 14:00
Plats: Online via: https://lu-se.zoom.us/j/64706239738
Kontakt: birger [dot] swahn [at] cs [dot] lth [dot] se
Spara händelsen till din kalender


One Computer Science MSc thesis to be presented on 23 September via Zoom

Thursday, 23 September there will be a master thesis presentation in Computer Science at Lund University, Faculty of Engineering.

The presentation will take place via Zoom at: https://lu-se.zoom.us/j/64706239738

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.


13:00-14:00

Presenters: Kevin Andersson, Mohammad Abo Al Anein
Title: Data-driven Deployment of Program Analysis Fixes
Examiner: Görel Hedin
Supervisors: Emma Söderberg (LTH), David Åkerman (Axis), Jon Sten (Axis)

Program analyzers can be really helpful in developing code, helping to find otherwise unnoticed issues and helping developers avoid common mistakes. However, using analyzers often come with needing to handle false positives, confusing warning messages and configurations that are specific to each analyzer. To counteract these issues, a data-driven program analysis system can be used to enable continuous tuning during run-time. One such recently developed system is called MEAN, short for MEta ANalyzer, a relatively new system that is actively in development. This means that the program might be missing features in comparison to other data-driven program analyzers, one of these being the ability to provide fix suggestions. In this thesis, the goal is to investigate how a fix suggestion feature might best be implemented and tested in MEAN. This fix suggestion feature will provide MEAN with the capability to not only send messages, but also to send specified suggestions that can automatically be integrated into the code.. Furthermore, this thesis will require some deployment of MEAN with these new features in order to evaluate how well the new changes are received. The conclusions reached in this thesis is that the new feature is well received, but could be implemented better, that is, while the use of the feature is easy to understand, the actual process of using the new feature might be unnecessarily clunky. Overall, the addition of fix suggestions appear to have improved the interaction, and provides developers with a quick and easy way of integrating suggestions into their code.

Link to presentation: https://lu-se.zoom.us/j/64706239738

Link to popular science summary: TBU