The Mercury Project
Motivation and Overview

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Motivation and Overview

Even though logic programming languages are theoretically superior to imperative programming languages such as C, C++, Pascal and Ada, existing logic programming languages such as Prolog are not widely used in industry for writing application programs. The two main reasons for this are

  • Compilers for current logic programming languages detect many fewer errors in programs than compilers for imperative programming languages do. Programmers therefore have to find all the errors themselves, usually with minimal debugging support. This significantly reduces productivity.

  • Implementations of logic programming languages are significantly slower than the implementations of imperative languages such as C. Therefore the designers of applications where performance is important do not even consider logic programming languages.

We are developing a new kind of logic programming language that solves both of these problems. Our new language, Mercury, has strong type and mode systems that detect a large percentage of program errors at compile time. The information provided by the type and mode systems then allows us to significantly increase the efficiency of the implementation. Meanwhile, unlike Prolog, Mercury retains all the desirable properties of logic programming languages. For example, the absence of side effects in Mercury by itself prevents large classes of errors that plague programs written in imperative languages. It also allows us to transform and optimize Mercury programs in ways that are emphatically not possible with programs written in imperative languages or in Prolog. For example, it is straightforward to integrate intelligent backtracking into Mercury, even though researchers have given up on doing the same for Prolog.

We are writing the Mercury compiler in Mercury itself. We used NU-Prolog and SICStus Prolog for boot-strapping until the compiler was able to compile itself. The compiler's type, mode and determinacy checkers have together prevented several hundred bugs in the compiler itself. Traditional Prolog systems cannot make such checks. Therefore had we been programming only in Prolog, many of these bugs would not have been detected, and locating the rest would have required manual tracing of the compiler's execution, taking several hours per bug. As it is, the Mercury compiler pinpointed these bugs automatically, and due to the help of the error messages, we have found that most bugs were quite easy to fix.

Our experience strongly supports our initial conjecture that Mercury is a comfortable language to program in, and that it is much easier to produce reliable programs in Mercury than in Prolog. The amount of functionality we have implemented so far also strongly suggests that it is easier to produce reliable programs in Mercury than in imperative languages such as C, C++, Pascal or Ada.

Our extensive benchmarking has shown our implementation to be almost twice as fast as the fastest existing logic programming system, Aquarius Prolog, about five times as fast as SICStus Prolog's native mode compiler, about ten times as fast as Quintus Prolog, and 20 to 36 times as fast as other Prolog implementations using bytecode interpreters.

Mercury does not sacrifice portability for speed. While previous fast logic programming systems generate native code and can thus run on only few types of system, we generate C code that can be compiled on almost all software and hardware platforms.

Aquarius and other high-performance Prolog systems base their optimizations on information gathered by global analysis. These analyses must make approximations to keep analysis times reasonable. Large programs tend to require more approximations, which makes optimization less effective. Despite using only predicate-level and module-level analyses, Mercury never makes approximations, and thus retains its speed even for the largest programs.

We designed the Mercury execution algorithm in October 1993. We started working on a Mercury compiler in December 1993. Semantic analysis started working around May 1994. We started generating code around August 1994; we started work on optimizations very soon after. The compiler successfully compiled itself on 24 February 1995. The first public beta release of the system was version 0.3 on 18 July 1995. The profiler was introduced in Version 0.4 on 15 September 1995. Checking of uniqueness information and the C language interface were introduced in Version 0.5 on 15 February 1996. Functional syntax and type and mode inference were introduced in Version 0.6 on 2 August 1996. Version 0.7, released on 15 August 1997, introduced generic I/O predicates and was the first to provide cross-module optimization.