2020/10/12 by Rahul Krishna, Shahriar Iqbal, Krishna, Rahul +7
Computer Science · #FOS: Computer and information sciences #FOS: Electrical engineering #Formal Methods in Verification #Real-Time Systems Scheduling #Software Engineering (cs.SE) #Software Testing and Debugging Techniques #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2010.06061
openalex publication_date 2020/10/12 · openalex created_date 2021/03/15 · openalex updated_date 2026/07/28
Modern computing platforms are highly-configurable with thousands of interacting configurations. However, configuring these systems is challenging. Erroneous configurations can cause unexpected non-functional faults. This paper proposes CADET (short for Causal Debugging Toolkit) that enables users to identify, explain, and fix the root cause of non-functional faults early and in a principled fashion. CADET builds a causal model by observing the performance of the system under different configurations. Then, it uses casual path extraction followed by counterfactual reasoning over the causal model to: (a) identify the root causes of non-functional faults, (b) estimate the effects of various configurable parameters on the performance objective(s), and (c) prescribe candidate repairs to the relevant configuration options to fix the non-functional fault. We evaluated CADET on 5 highly-configurable systems deployed on 3 NVIDIA Jetson systems-on-chip. We compare CADET with state-of-the-art configuration optimization and ML-based debugging approaches. The experimental results indicate that CADET can find effective repairs for faults in multiple non-functional properties with (at most) 17% more accuracy, 28% higher gain, and 40× speed-up than other ML-based performance debugging methods. Compared to multi-objective optimization approaches, CADET can find fixes (at most) 9× faster with comparable or better performance gain. Our case study of non-functional faults reported in NVIDIA's forum show that CADET can find 14% better repairs than the experts' advice in less than 30 minutes.