Update the compiler research projects

_gsocproposals/2025/proposal_Clad-PyTorch.md

@@ -34,7 +34,7 @@ This project aims to integrate Clad-generated functions into PyTorch using its C
 
 ## Mentors
 * **[Vassil Vassilev](mailto:[email protected])**
-* [Christina Koutsou](mailto:@[email protected])
+* [David Lange](mailto:[email protected])
 
 ## Links
 * [Repo](https://github.com/vgvassilev/clad)

_gsocproposals/2025/proposal_Clad-ThrustAPI.md

@@ -32,8 +32,8 @@ Clad is a clang plugin for automatic differentiation that performs source-to-sou
 * Clang frontend
 
 ## Mentors
-* **[Christina Koutsou](mailto:@[email protected])**
-* [Vassil Vassilev](mailto:vvasilev@cern.ch)
+* **[Vassil Vassilev](mailto:[email protected])**
+* [David Lange](mailto:david.lange@cern.ch)
 
 ## Links
 * [Repo](https://github.com/vgvassilev/clad)

_gsocproposals/2025/proposal_IDD.md

@@ -0,0 +1,39 @@
+---
+title: Interactive Differential Debugging - Intelligent Auto-Stepping and Tab-Completion
+layout: gsoc_proposal
+project: CppInterOp
+year: 2025
+difficulty: medium
+duration: 350
+mentor_avail: June-October
+organization:
+  - CompRes
+---
+
+## Description
+
+Differential debugging is a time-consuming task that is not well supported by existing tools. Existing state-of-the-art tools do not consider a baseline(working) version while debugging regressions in complex systems, often leading to manual efforts by developers to achieve an automatable task.
+
+The differential debugging technique analyzes a regressed system and identifies the cause of unexpected behaviors by comparing it to a previous version of the same system. The idd tool inspects two versions of the executable – a baseline and a regressed version. The interactive debugging session runs both executables side-by-side, allowing the users to inspect and compare various internal states.
+
+This project aims to implement intelligent stepping (debugging) and tab completions of commands. IDD should be able to execute until a stack frame or variable diverges between the two versions of the system, then drop to the debugger. This may be achieved by introducing new IDD-specific commands. IDD should be able to tab complete the underlying GDB/LLDB commands. The contributor is also expected to set up the necessary CI infrastructure to automate the testing process of IDD.
+
+## Expected Results
+
+* Enable stream capture
+* Enable IDD-specific commands to execute until diverging stack or variable value.
+* Enable tab completion of commands.
+* Set up CI infrastructure to automate testing IDD.
+* Present the work at the relevant meetings and conferences.
+
+## Requirements
+
+* Python & C/C++ programming
+* Familiarity debugging with GDB/LLDB
+
+## Mentors
+* **[Vipul Cariappa](mailto:[email protected])**
+* [Martin Vasilev](mailto:[email protected])
+
+## Links
+* [IDD Repository](https://github.com/compiler-research/idd)

gsoc/2025/mentors.md

@@ -15,7 +15,6 @@ layout: plain
 * Mateusz Fila [[email protected]](mailto:[email protected]) CERN
 * Chris Gutschow [[email protected]](mailto:[email protected]) UCLondon
 * Aaron Jomy [[email protected]](mailto:[email protected]) CERN/CompRes
-* Christina Koutsou [[email protected]](mailto:@[email protected]) CompRes
 * Stephan Lachnit [[email protected]](mailto:[email protected]) DESY
 * David Lange [[email protected]](mailto:[email protected]) CompRes
 * Serguei Linev [[email protected]](mailto:[email protected]) GSI