The model k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document}-CSP is a random CSP model with moderately growing arity k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document} of constraints. By incorporating certain linear structure, k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document}-CSP is revised to a random linear CSP, named k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document}-hyper-F\documentclass[12pt]{minimal}
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\begin{document}$${\mathbb F}$$\end{document}-linear CSP. It had been shown theoretically that the two models exhibit exact satisfiability phase transitions when the constraint density r\documentclass[12pt]{minimal}
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\begin{document}$$r$$\end{document} is varied accordingly. In this paper, we use finite-size scaling analysis to characterize the threshold behaviors of the two models with finite problem size n\documentclass[12pt]{minimal}
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\begin{document}$$n$$\end{document}. A series of experimental studies are carried out to illustrate the scaling window of the model k\documentclass[12pt]{minimal}
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\begin{document}$$k$$\end{document}-CSP.
