Many programmers have had to deal with an overwritten variable resulting for example from an aliasing problem. The culprit is obviously the last write-access to that memory location before the manifestation of the bug. The usual technique for removing such bugs starts with the debugger by (1) finding the last write and (2) moving the control point of execution back to that time by re-executing the program from the beginning. We wish to automate this. Step (2) is easy if we can somehow mark the last write found in step (1) and control the execution-point to move it back to this time. In this paper we propose a new concept, position, that is, a point in the program execution trace, as needed for step (2) above. The position enables debuggers to automate the control of program execution to support common debugging activities. We have implemented position in C by modifying GCC and in Java with a bytecode transformer. Measurements show that position can be provided with an acceptable amount of overhead.
Ducass ' e @cite_26 allows the programmer to control the execution not by source statement orientation, but by event orientation such as assignments, function calls, loops, and so on. Users write Prolog-like forms to designate breakpoints which have complex conditions. This mechanism is complementary to our system and suitable for a front end of it in order to designate appropriate positions where we would move control point to.
@cite_26
2028053566 2096979400 2045474169 1985444680
In this paper, we compose six di erent Python and Prolog VMs into 4 pairwise compositions: one using C interpreters; one running on the JVM; one using meta-tracing interpreters; and one using a C interpreter and a meta-tracing interpreter. We show that programs that cross the language barrier frequently execute faster in a meta-tracing composition, and that meta-tracing imposes a significantly lower overhead on composed programs relative to mono-language programs. 1. Overview Programming language composition aims to allow the mixing of programming languages in a fine-grained manner. This vision brings many challenging problems, from the interaction of language semantics to performance. In this paper, we investigate the runtime performance of composed programs in high-level languages. We start from the assumption that execution of such programs is most likely to be through composing language implementations that use interpreters and VMs, rather than traditional compilers. This raises the question: how do di erent styles of composition a ect performance? Clearly, such a question cannot have a single answer but, to the best of our knowledge, this issue has not been explored in the past. This paper's hypothesis is that meta-tracing - a relatively new technique used to produce JIT (Just-In-Time) compilers from interpreters (1) - will lead to faster interpreter composition than traditional approaches. To test this hypothesis, we present a Python and Prolog composition which allows Python programs to embed and call Prolog programs. We then implement the composition in four di erent ways, comparing the absolute times and the relative cross-language costs of each. In addition to the 'traditional' approaches to composing interpreters (in C and upon the JVM), we also investigate the application of meta-tracing to interpreter composition. The experiments we then carry out confirm our initial hypothesis. There is a long tradition of composing Prolog with other languages (with e.g. Icon (2), Lisp (3), and Smalltalk (4)) because one can express certain types of programs far easier in Prolog than in other languages. We have two additional reasons for choosing this pairing. First, these languages represent very di erent points in the language design space: Prolog's inherently Delaying-based tabling mechanisms, such as the one adopted in XSB, are non-linear in the sense that the computation state of delayed calls has to be preserved. In this paper, we present the implementation of a linear tabling mechanism. The key idea is to let a call execute from the backtracking point of a former variant call if such a call exists. The linear tabling mechanism has the following advantages over non-linear ones: (1) it is relatively easy to implement; (2) it imposes no overhead on standard Prolog programs; and (3) the cut operator works as for standard Prolog programs and thus it is possible to use the cut operator to express negation-as-failure and conditionals in tabled programs. The weakness of the linear mechanism is the necessity of re-computation for computing fix-points. However, we have found that re-computation can be avoided for a large portion of calls of directly-recursive tabled predicates. We have implemented the linear tabling mechanism in B-Prolog. Experimental comparison shows that B-Prolog is close in speed to XSB and outperforms XSB when re-computation can be avoided. Concerning space efficiency, B-Prolog is an order of magnitude better than XSB for some programs. Abstract This paper proposes a new logic programming language called GOLOG whose interpreter automatically maintains an explicit representation of the dynamic world being modeled, on the basis of user supplied axioms about the preconditions and effects of actions and the initial state of the world. This allows programs to reason about the state of the world and consider the effects of various possible courses of action before committing to a particular behavior. The net effect is that programs may be written at a much higher level of abstraction than is usually possible. The language appears well suited for applications in high level control of robots and industrial processes, intelligent software agents, discrete event simulation, etc. It is based on a formal theory of action specified in an extended version of the situation calculus. A prototype implementation in Prolog has been developed. Presents Coca, an automated debugger for C, where the breakpoint mechanism is based on events related to language constructs. Events have semantics, whereas the source lines used by most debuggers do not have any. A trace is a sequence of events. It can be seen as an ordered relation in a database. Users can specify precisely which events they want to see by specifying values for event attributes. At each event, visible variables can be queried. The trace query language is Prolog with a handful of primitives. The trace query mechanism searches through the execution traces using both control flow and data, whereas debuggers usually search according to either control flow or data. As opposed to fully "relational" debuggers which use plain database querying mechanisms, the Coca trace querying mechanism does not require any storage. The analysis is done on-the-fly, synchronously with the traced execution. Coca is therefore more powerful than "source-line" debuggers and more efficient than relational debuggers.