Componentized　service-oriented　software　systems　always　consist　of　loosely　coupled　hetero-geneous　service　components,　each　of　which　contains　a　large　number　of　configuration　items　configured　with　high　flexibility.　Complex　dependencies　exist　between　service　components,　resulting　in　their　interrelated　configuration　items,　so　the　operations　of　deploying,　updating　and　migrating　components　are　prone　to　errors.　For　configuration　items　related　with　each　other,　changing　one　configuration　item　requires　to　modify　other　related　configuration　items.　Otherwise,　violating　constraints　perhaps　happens,　which　should　cause　system　failure.　Therefore,　analyzing　associations　between　configuration　items　is　one　key　to　ensure　the　reliability　of　a　system.　This　paper　proposes　a　service　configuration　approach　based　on　association　mining.　Our　approach　crawls　configuration　files　from　Internet,　narrows　the　analysis　scope　to　frequently　changed　configuration　items,　generates　association　coefficients　for　item　pairs　according　to　the　similarity　of　items＇　name,　value　and　type,　determines　the　set　of　candidate　item　pairs　with　rules,　and　then　outputs　a　list　of　ordered　configuration　item　pairs　for　query.　We　have　deployed　two　typical　open-source　software　systems　to　validate　our　approach　for　mining　configuration　associations　between　configuration　items　with　case　studies.　Experimental　results　show　that　our　approach　can　accurately　detect　most　associations　between　configuration　items.　©　2020,　Science　Press.　All　right　reserved.