{"id":36881,"date":"2019-10-31T22:14:28","date_gmt":"2019-10-31T19:14:28","guid":{"rendered":"https:\/\/prohoster.info\/blog\/deepcode-najdyot-oshibki-v-ishodnom-kode-po-pri-pomoshhi-ii\/"},"modified":"2019-10-31T22:14:28","modified_gmt":"2019-10-31T19:14:28","slug":"deepcode-najdyot-oshibki-v-ishodnom-kode-po-pri-pomoshhi-ii","status":"publish","type":"post","link":"https:\/\/prohoster.info\/da\/blog\/news\/deepcode-najdyot-oshibki-v-ishodnom-kode-po-pri-pomoshhi-ii","title":{"rendered":"DeepCode finder fejl i softwarekode ved hj\u00e6lp af AI","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

I dag annoncerede den schweiziske startup DeepCode<\/a><\/noindex>, der bruger kunstig intelligens og maskinl\u00e6ring til at automatisere analysen af programmeringskode, at de har modtaget en investering p\u00e5 4 millioner dollars fra risikokapitalfondene Earlybird, 3VC og Btov Partners. Virksomheden planl\u00e6gger at bruge disse midler til at implementere support for nye programmeringssprog i deres service samt til marketing af produktet p\u00e5 det globale IT-marked.<\/p>\n

\"DeepCode<\/p>\n

Kodeanalyse er n\u00f8dvendig for at opdage fejl, potentielle s\u00e5rbarheder, overtr\u00e6delser af almindeligt accepterede formateringsstile og meget mere i de tidlige faser af softwareudvikling, f\u00f8r koden anvendes noget sted. Denne procedure udf\u00f8res normalt parallelt med udviklingen af ny kode og straks efter at den er afsluttet, hvilket forudg\u00e5r selve testfasen. \"Softwaretest ser p\u00e5 koden udefra, men kodeanalyse giver dig mulighed for at se p\u00e5 den indefra,\" forklarer medstifter og administrerende direkt\u00f8r for DeepCode, Boris Paskalev, i et interview med VentureBeat.<\/p>\n

Ofte udf\u00f8res kodegennemgang af dens forfattere sammen med kolleger og ledere med henblik p\u00e5 at identificere \u00e5benlyse fejl, f\u00f8r de g\u00e5r videre til de n\u00e6ste faser af udviklingen. Jo st\u00f8rre projektet er, desto flere linjer kode skal kontrolleres, hvilket tager en betydelig m\u00e6ngde tid for programmerne. V\u00e6rkt\u00f8jer, der skal fremskynde denne proces, har eksisteret i lang tid, for eksempel statiske kodeanalysatorer som Coverity og PVS-Studio, men de er som regel begr\u00e6nsede i deres muligheder, da de fokuserer p\u00e5 \"irriterende og gentagne stilproblemer, formatering og sm\u00e5 logiske fejl\", forklarer Paskalev.<\/p>\n

<\/center><\/p>\n

DeepCode d\u00e6kker et bredere spektrum af problemer, som for eksempel at opdage s\u00e5rbarheder som cross-site scripting og SQL-injektioner, fordi de algoritmer, der er indarbejdet, ikke blot analyserer koden som en sekvens af tegn, men fors\u00f8ger at forst\u00e5 meningen og form\u00e5let med det skrevne program. Bag dette ligger et maskinl\u00e6ringssystem, der bruger milliarder af linjer kode fra offentlige open source-projekter til sin tr\u00e6ning. DeepCode analyserer tidligere versioner af koden og de \u00e6ndringer, der er blevet foretaget, for at studere, hvordan reelle programm\u00f8rer har rettet fejl, og derefter tilbyde lignende l\u00f8sninger til sine brugere. Derudover anvender systemet ogs\u00e5 traditionelle forudsigelsesalgoritmer til at finde mulige problemer i koden, der ligner de ovenfor n\u00e6vnte statiske analysatorer.<\/p>\n

Et af de centrale sp\u00f8rgsm\u00e5l ved brugen af DeepCode er: Hvor p\u00e5lidelig er den automatiske kodekontrol? En n\u00f8jagtighed under 100 % betyder, at udviklerne stadig er n\u00f8dt til at analysere deres kode manuelt. I s\u00e5 fald, hvor meget tid vil brugen af v\u00e6rkt\u00f8jer til automatisering af denne opgave faktisk frig\u00f8re? If\u00f8lge Paskelev kan DeepCode spare udviklerne cirka 50 % af den tid, de i \u00f8jeblikket bruger p\u00e5 selv at finde fejl, hvilket er en betydelig besparelse.<\/p>\n

Udviklere kan tilknytte DeepCode til deres kontoer p\u00e5 GitHub eller Bitbucket, og v\u00e6rkt\u00f8jet underst\u00f8tter ogs\u00e5 lokale GitLab-konfigurationer. Derudover har projektet et specielt API, der g\u00f8r det muligt for udviklere at integrere DeepCode i deres egne udviklingssystemer. Efter tilslutning til repository vil DeepCode analysere hver \u00e6ndring i koden og fremh\u00e6ve potentielle problemer.<\/p>\n

\"DeepCode<\/p>\n

\"I gennemsnit bruger udviklere omkring 30 % af deres tid p\u00e5 at finde og rette fejl, men DeepCode kan spare halvdelen af denne tid allerede nu, og endnu mere i fremtiden,\" h\u00e6vder Boris. \"Da DeepCode l\u00e6rer direkte fra det globale udviklerf\u00e6llesskab, er det i stand til at opdage flere problemer, end \u00e9n person eller en hel gruppe anmeldere nogensinde kunne finde.\"<\/p>\n

Udover dagens nyhed om investeringer har DeepCode ogs\u00e5 annonceret en ny v\u00e6rdifuld politik for sit produkt. Indtil nu har DeepCode v\u00e6ret gratis kun for open source softwareprojekter. Nu vil det dog v\u00e6re gratis at bruge til alle uddannelsesm\u00e6ssige form\u00e5l og endda for kommercielle virksomheder med f\u00e6rre end 30 udviklere. Det er tydeligt, at DeepCodes skaberne \u00f8nsker at g\u00f8re deres produkt mere popul\u00e6rt blandt sm\u00e5 teams. Derudover opkr\u00e6ver DeepCode 20 dollars pr. udvikler om m\u00e5neden ved implementering af l\u00f8sningen i skyen og 50 dollars pr. udvikler for lokal support.<\/p>\n

Tidligere har DeepCode-teamet allerede modtaget investeringer p\u00e5 1 million dollars. Med yderligere 4 millioner har virksomheden erkl\u00e6ret, at de planl\u00e6gger at udvide de sprog, de underst\u00f8tter, ud over Java, JavaScript og Python, herunder at tilf\u00f8je underst\u00f8ttelse af C#, PHP og C\/C++. De har ogs\u00e5 bekr\u00e6ftet, at de arbejder p\u00e5 deres egen integrerede udviklingsmilj\u00f8.<\/p>\n

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Kilde: 3dnews.ru<\/a><\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

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