Don't go "wild" with Associative arrays in SystemVerilog - PySlint it!

 Hash tables, modeled via Associative arrays is a powerful data structure in SystemVerilog. Python calls it as "dictionary". One of the "wild" features of SystemVerilog is that it allows associative arrays to be declared with arbitrary key type. An example:

        class wild_c;

          string wild_hash_table [*];

        endclass : wild_c

While the above is a legal SystemVerilog code, may even be seen as "easier" to write, it is bad from a reuse perspective. Some of the side effects (mostly bad) are:

  • Unclear data structure to begin with - for writer and then the reader/maintainer of the code. 
  • As the key can be anything, SV does not allow wildcard indexed associative array to be iterated via foreach loop.
  • It cannot be passed as function parameter.
  • Many find* methods do not work on wild-card indexed associative arrays. For instance, find_first would need to return a queue of the keys, and when used on wild-card indexed array, it would be a queue of "mixed key types", SystemVerilog does not support such queues.
Good news is, PySlint catches such usage and flags it really fast, see a sample below:


So, pull it from PySlint and deploy today!


Comments

  1. AsFigoDecember 11, 2023 at 7:47 AM

    This comment has been removed by the author.

    ReplyDelete
  2. AsFigoDecember 11, 2023 at 7:52 AM

    Good point by Ben Cohen on what's next step - please use a defined datatype as index such as int.
    int my_hash_table [int];

    ReplyDelete
  3. for.August 29, 2026 at 2:41 AM

    great

    ReplyDelete
  4. for.August 29, 2026 at 2:42 AM

    Associative arrays are a useful way to represent hash-table-like structures in SystemVerilog, and the comparison with Python dictionaries makes the concept easy to understand. The article also highlights an important maintainability concern: using wildcard key types can make a data structure harder to understand, reuse, and process reliably.

    For Python developers interested in understanding similar data structures and programming concepts, Python Online Course can provide a useful foundation for working with dictionaries, collections, and other built-in data structures.

    ReplyDelete
  5. for.August 29, 2026 at 2:42 AM

    It is also interesting to see how static analysis tools can identify problematic coding patterns early. Comparing approaches across languages helps developers recognize why explicit data structures and clear key types are important for writing code that is easier to maintain and reuse.

    Developers who want to strengthen their broader Python programming skills can also explore Python Online Training, particularly when working with dictionaries and other collection-based programming techniques.Python Projects For Final Year

    ReplyDelete

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