Jun Hu

Junze Hu, Xiangyu Jin, Yizhe Zeng et al.

We introduce QLPro, a vulnerability detection framework that systematically integrates LLMs and static analysis tools to enable comprehensive vulnerability detection across entire open-source projects.We constructed a new dataset, JavaTest, comprising 10 open-source projects from GitHub with 62 confirmed vulnerabilities. CodeQL, a state-of-the-art static analysis tool, detected only 24 of these vulnerabilities while QLPro detected 41. Furthermore, QLPro discovered 6 previously unknown vulnerabilities, 2 of which have been confirmed as 0-days.

A. Koegel, C. Furet, T. Suzuki et al.

The Thinking Wave is an ongoing development of visualization concepts showing the real-time effort and confidence of semi-autonomous vehicle (AV) systems. Offering drivers access to this information can inform their decision making, and enable them to handle the situation accordingly and takeover when necessary. Two different visualizations have been designed, Concept one, Tidal, demonstrates the AV systems effort through intensified activity of a simple graphic which fluctuates in speed and frequency. Concept two, Tandem, displays the effort of the AV system as well as the handling dynamic and shared responsibility between the driver and the vehicle system. Working collaboratively with mobility research teams at the University of Tokyo, we are prototyping and refining the Thinking Wave and its embodiments as we work towards building a testable version integrated into a driving simulator. The development of the thinking wave aims to calibrate trust by increasing the drivers knowledge and understanding of vehicle handling capacity. By enabling transparent communication of the AV systems capacity, we hope to empower AV-skeptic drivers and keep over-trusting drivers on alert in the case of an emergency takeover situation, in order to create a safer autonomous driving experience.

Ziyou Jiang, Lin Shi, Celia Chen et al.

Despite the valuable information contained in software chat messages, disentangling them into distinct conversations is an essential prerequisite for any in-depth analyses that utilize this information. To provide a better understanding of the current state-of-the-art, we evaluate five popular dialog disentanglement approaches on software-related chat. We find that existing approaches do not perform well on disentangling software-related dialogs that discuss technical and complex topics. Further investigation on how well the existing disentanglement measures reflect human satisfaction shows that existing measures cannot correctly indicate human satisfaction on disentanglement results. Therefore, in this paper, we introduce and evaluate a novel measure, named DLD. Using results of human satisfaction, we further summarize four most frequently appeared bad disentanglement cases on software-related chat to insight future improvements. These cases include (i) ignoring interaction patterns; (ii) ignoring contextual information; (iii) mixing up topics; and (iv) ignoring user relationships. We believe that our findings provide valuable insights on the effectiveness of existing dialog disentanglement approaches and these findings would promote a better application of dialog disentanglement in software engineering.

Cun Li, Jun Hu, Bart Hengeveld et al.

Family mementos document events shaping family life, telling a story within and between family members. The elderly collected some mementos for children, but never recorded stories related to those objects. In this paper, in order to understand the status quo of memento storytelling and sharing of elderly people, contextual inquiry was conducted, which further helped us to identify design opportunities and requirements. Resulting design was defined after brainstorm and user consultation, which was Slots- Memento, a system consisting a slot machine-like device used by the elderly and a flash drive used by the young. The Slots machine-like device utilizes with the metaphor of slots machine, which integrates functions of memento photo displaying, story recording, and preservation. In the flash disk, the young could copy memento photos to it. The system aims to facilitate memento story sharing and preservation within family members. Preliminary evaluation and user test were conducted in evaluation section, the results showed that Slots-Memento was understood and accepted by the elderly users. Photos of mementos were easy to recall memories. It enabled the elderly people to be aware of the stories of the family mementos, as well as aroused their desire to share them with family members. Related research methodology includes contextual inquiry, brainstorming, prototyping, scenario creation, and user test.