L (complexity)

In computational complexity theory, L (also known as LSPACE, LOGSPACE or DLOGSPACE) is the complexity class containing decision problems that can be solved by a deterministic Turing machine using a logarithmic amount of writable memory space.[1][2] Formally, the Turing machine has two tapes, one of which encodes the input and can only be read,[3] whereas the other tape has logarithmic size but can be read as well as written. Logarithmic space is sufficient to hold a constant number of pointers into the input[1] and a logarithmic number of Boolean flags, and many basic logspace algorithms use the memory in this way.

  1. ^ a b Sipser (1997), p. 295, Definition 8.12
  2. ^ Garey & Johnson (1979), p. 177
  3. ^ On a read/write input tape, a linear amount of memory could be obtained by packing of symbols (as in the proof of the linear speedup theorem), thus evading the logspace contraint.