Generating Tests for Robotized Painting Using Constraint Programming
Authors: Morten Mossige, Arnaud Gotlieb, Hein Meling
IJCAI 2016 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | To address these challenges, we have developed and deployed a cost-effective, automated test generation technique aimed at validating the timing behavior of the process control system. The approach is based on a constraint optimization model written in Prolog. This model has been integrated into an automated continuous integration environment, allowing the model to be solved on demand prior to test execution, which allows us to obtain the most optimal and diverse set of test scenarios for the current system configuration. |
| Researcher Affiliation | Collaboration | Morten Mossige ABB Robotics morten.mossige@no.abb.com Arnaud Gotlieb Simula Research Laboratory arnaud@simula.no Hein Meling University of Stavanger hein.meling@uis.no |
| Pseudocode | No | The paper describes a CP model and its implementation, but does not provide pseudocode or algorithm blocks. |
| Open Source Code | No | The paper mentions developing a CP model in SICStus Prolog and its integration into ABB's CI process, but does not state that the code itself is open source or publicly available. |
| Open Datasets | No | The paper describes generating test scenarios using a CP model for a specific industrial system (ABB's IPS) and does not refer to any publicly available dataset or provide access information for data used. |
| Dataset Splits | No | The paper does not specify any dataset splits for training, validation, or testing, as it focuses on generating tests for a specific system rather than using a fixed dataset. |
| Hardware Specification | No | The paper mentions 'embedded controllers' and running the model 'on a single physical setup' but provides no specific details about the CPU, GPU, or other hardware components used for running the experiments or the CI process. |
| Software Dependencies | Yes | This paper summarizes our previous work [Mossige et al., 2014] on using constraint programming (CP) to generate automatically timed-event sequences (i.e., test scenarios) for ABB s integrated process control system (IPS) and to execute them as part of a CI process. To this end, we developed a constraint optimization model in SICStus Prolog [Carlsson et al., 1997] to test the IPS under operational conditions. ... This section details our implementation of the CP model with SICStus Prolog and its clpfd library [Carlsson et al., 1997], and its exploitation in the CI process at ABB Robotics. ... The complete system contains about 2k lines of Prolog code, 300 lines of C code (a DLL interface between Python and SICStus), and about 3k lines of Python code. |
| Experiment Setup | No | The paper describes the overall process of integrating the CP model into a CI environment and mentions identifying 'test scenarios' (e.g., normal, overlap, kill brush) as test objectives. However, it does not provide specific hyperparameters, training configurations, or detailed system-level settings typically found in an 'experimental setup' section for training a model. |