Communities　exist　anywhere　in　various　complex　networks,　and　community　evolution　tracking　is　one　of　the　most　well-liked　areas　of　inquiry　in　the　study　of　dynamic　complex　networks.　Community　evolution　tracking　has　many　applications　in　daily　life,　such　as　predicting　social　network　behaviors　or　analyzing　the　spread　of　infectious　illnesses.　However,　the　majority　of　existing　evolution　tracking　algorithms　obtain　community　detection　results　before　matching　the　community　in　tracking　evolution　events,　making　it　difficult　to　trace　the　whole　evolution　of　communities　because　of　community　matching　errors.　In　addition,　the　majority　of　evolution　tracking　algorithms　do　not　adequately　account　for　the　potential　scenarios　in　community　evolution,　resulting　in　erroneous　detection　of　evolution　events.　In　this　research,　a　community　evolution　tracking　algorithm　based　on　edge　variation　discerning　and　core　node　extension　is　proposed.　First,　we　detect　communities　based　on　the　core　node　extension　strategy,　which　avoids　the　problem　of　community　matching　errors.　Second,　we　track　community　evolution　based　on　the　edge　variation　discerning　strategy,　which　fully　considers　various　situations　that　may　occur　during　the　community　evolution　process.　According　to　the　outputs　of　our　experiments,　our　system　can　effectively　track　the　evolution　of　communities　in　synthetic　dynamic　networks.　©　2023,　The　Author(s),　under　exclusive　license　to　Springer　Nature　Singapore　Pte　Ltd.