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How to review dotnet code

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  • T Offline
    T Offline
    Tridip Bhattacharjee
    wrote on last edited by
    #1

    i am looking for guidance or best practice to review my code or review my colleague code working in same company. two way i guess exist to review code. one is manual process and one should be automated process where people may use various tools to review code. so please discuss two different process called manually review code and automated way review code using tools. please guide me in details. thanks

    tbhattacharjee

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    • T Tridip Bhattacharjee

      i am looking for guidance or best practice to review my code or review my colleague code working in same company. two way i guess exist to review code. one is manual process and one should be automated process where people may use various tools to review code. so please discuss two different process called manually review code and automated way review code using tools. please guide me in details. thanks

      tbhattacharjee

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      Pete OHanlon
      wrote on last edited by
      #2

      For automatic reviews, you can use FxCop and StyleCop. For manual reviews, you really should search the web for manual review processes, read them and agree with your colleagues on the best approach to conduct reviews; that's partly going to depend on your code cycle workflow (do you review pre commit to Source Control, or do you do it post commit and in a separate review stage for instance). We can't really help you that much on that side.

      This space for rent

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      • T Tridip Bhattacharjee

        i am looking for guidance or best practice to review my code or review my colleague code working in same company. two way i guess exist to review code. one is manual process and one should be automated process where people may use various tools to review code. so please discuss two different process called manually review code and automated way review code using tools. please guide me in details. thanks

        tbhattacharjee

        L Offline
        L Offline
        Lost User
        wrote on last edited by
        #3

        "Review" for what? How do you measure "success"? Machine learning involves calculating "distances" from some "ideal". You need to "classify" your problem (i.e. what are the "measures") before you can achieve anything meaningful. Unless you actually have some "good code" as a reference and for "training" purposes, you will get nowhere.

        "(I) am amazed to see myself here rather than there ... now rather than then". ― Blaise Pascal

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