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Chapter 5: Problem 19

Alyssa P. Hacker wants a breakpoint feature in the simulator to help her debug her machine designs. You have been hired to install this feature for her. She wants to be able to specify a place in the controller sequence where the simulator will stop and allow her to examine the state of the machine. You are to implement a procedure (set-breakpoint ?machine \(\rangle\langle\) label \(\rangle\langle n\rangle\) ) that sets a breakpoint just before the \(n\)th instruction after the given label. For example, (set-breakpoint gcd-machine 'test-b 4) installs a breakpoint in gcd-machine just before the assignment to register a. When the simulator reaches the breakpoint it should print the label and the offset of the breakpoint and stop executing instructions. Alyssa can then use get-register-contents and set-register-contents! to manipulate the state of the simulated machine. She should then be able to continue execution by saying (proceed-machine \(\langle\) machine \(\rangle\) ) She should also be able to remove a specific breakpoint by means of (cancel-breakpoint ?machine \(\rangle\langle\) label \(\rangle\langle n\rangle\) ) or to remove all breakpoints by means of (cancel-all-breakpoints \(\langle\) machine \(\rangle\) )

Short Answer

Expert verified
Design and implement procedures for setting, handling, canceling breakpoints; test the system thoroughly.

Step by step solution

01

Understand the Problem

The problem requires setting a breakpoint in a machine simulator, allowing a user to pause execution at a specific point based on a label and offset. Additionally, the user should be able to continue execution or cancel breakpoints.
02

Design the Data Structure

We need a way to store breakpoints associated with each machine. This can be done with a dictionary or list where each entry holds information about the label, offset, and whether the breakpoint is active.
03

Implement `set-breakpoint` Procedure

This function should take a machine, a label, and an offset. It should calculate the exact instruction position based on the offset from the label and store this information in the breakpoints data structure.
04

Implement Breakpoint Handling in Simulator

Modify the simulator loop to check for breakpoints. Before executing each instruction, see if a breakpoint is set at that point. If so, pause execution and print the breakpoint details.
05

Implement `proceed-machine` Procedure

This function resumes the simulator's execution from where it stopped. It should continue checking for further breakpoints during execution.
06

Implement `cancel-breakpoint` Procedure

Provide a mechanism for removing a specific breakpoint. Identify the correct breakpoint in the data structure using the label and offset and remove it.
07

Implement `cancel-all-breakpoints` Procedure

Create a function to clear all breakpoints for a given machine. This will involve resetting the breakpoints data structure, effectively removing all stored breakpoints.
08

Test the Breakpoint System

Test the functionality by creating a test machine, setting breakpoints, verifying that execution stops, and checking that it can resume and that breakpoints can be canceled.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Debugging Techniques
Debugging is a crucial part of programming, enabling developers to identify and fix errors in code. A helpful debugging technique is using breakpoints, which allow programmers to pause execution at a specific point in the code and inspect the current state of the machine. This is especially important in complex systems, such as a machine simulator, where errors might arise from a sequence of instructions.

The concept of breakpoints involves several critical actions:
  • Setting breakpoints at specific instructions to halt execution.
  • Pausing the program execution to inspect variables and the program state.
  • Resuming execution after inspection to continue testing other parts of the program.
  • Removing breakpoints once they are no longer needed to streamline future debugging sessions.
These actions help programmers better understand how their code is functioning and where it might be going wrong, allowing them to correct issues effectively.
Machine Simulation
Machine simulation involves creating a virtual model of a machine's operation that can run instructions to mimic real-world processes. This simulation is vital for testing machine designs or programs in a controlled, cost-effective, and fail-safe environment before implementing them in physical hardware.

In the context of this exercise, machine simulation allows Alyssa P. Hacker to test and debug her designs. The simulator executes instructions and processes just as a real machine would, making it an excellent tool for verifying correctness and performance. This simulation provides a playground for:
  • Running sequences of instructions to see their effects on machine states.
  • Implementing features such as breakpoints to control execution flow.
  • Allowing manipulations of the state or registers of the simulated machine.
  • Resuming execution post-debugging to continue testing further operations.
Machine simulation is integral in iteratively improving designs, as it offers insights into how modifications affect the final product.
Programming Concepts
Breakpoints and machine simulation rely on several fundamental programming concepts that are essential in computer science education. Understanding these concepts helps ensure the accurate design and implementation of complex systems.

Important programming concepts involved include:
  • Data Structures: Used to store and manage information regarding breakpoints, such as labels and offsets, ensuring efficient access and manipulation.
  • Control Flow: To pause and resume execution, control flow constructs must handle the sequential order of instructions while accommodating stoppages at breakpoints.
  • Procedures and Functions: By encapsulating repetitive tasks like setting and canceling breakpoints, procedures keep the code organized and modular.
  • Conditionals: Used to determine whether a breakpoint should halt execution, ensuring the simulator checks each instruction appropriately before proceeding.
Understanding these programming concepts equips developers with the tools needed to write efficient and maintainable code, which is essential for large systems requiring rigorous testing and debugging.

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Most popular questions from this chapter

The following register-machine code is ambiguous, because the label here is defined more than once: start \(\quad(\) goto (label here)) here \(\quad\) (assign a (const 3)) \(\quad(\) goto (label there)) here \(\quad(\) assign a (const 4)) \(\quad(\) goto (label there)) there With the simulator as written, what will the contents of register a be when control reaches there? Modify the extract-labels procedure so that the assembler will signal an error if the same label name is used to indicate two different locations.

Our compiler is clever about avoiding unnecessary stack operations, but it is not clever at all when it comes to compiling calls to the primitive procedures of the language in terms of the primitive operations supplied by the machine. For example, consider how much code is compiled to compute \((+a 1):\) The code sets up an argument list in argl, puts the primitive addition procedure (which it finds by looking up the symbol + in the environment) into proc, and tests whether the procedure is primitive or compound. The compiler always generates code to perform the test, as well as code for primitive and compound branches (only one of which will be executed). We have not shown the part of the controller that implements primitives, but we presume that these instructions make use of primitive arithmetic operations in the machine's data paths. Consider how much less code would be generated if the compiler could open-code primitives-that is, if it could generate code to directly use these primitive machine operations. The expression (+ a 1) might be compiled into something as simple as \({ }^{43}\) (assign val (op lookup-variable-value) (const a) (reg env)) (assign val (op +) (reg val) (const 1)) In this exercise we will extend our compiler to support open coding of selected primitives. Special-purpose code will be generated for calls to these primitive ;; construct the procedure and skip over code for the procedure body (assign val (op make-compiled-procedure) (label entry2) (reg env)) (goto (label after-lambda1)) entry2 ;calls to factorial will enter here (assign env (op compiled-procedure-env) (reg proc)) (assign env (op extend-environment) (const (n)) (reg argl) (reg env)) begin actual procedure body (save continue) (save env) ;; compute (=n 1) (assign proc (op lookup-variable-value) (const =) (reg env)) (assign val (const 1)) (assign argl (op list) (reg val)) (assign val (op lookup-variable-value) (const n) (reg env)) (assign argl (op cons) (reg val) (reg argl)) (test (op primitive-procedure?) (reg proc)) (branch (label primitive-branch17)) compiled-branch16 (assign continue (label after-calli5)) (assign val (op compiled-procedure-entry) (reg proc)) (goto (reg val)) primitive-branch17 (assign val (op apply-primitive-procedure) (reg proc) (reg argl)) after-callis ; val now contains result of \((=\mathrm{n} 1)\) (restore env) (restore continue) (test (op false?) (reg val)) (branch (label false-branch4)) true-branch5 ; return 1 (assign val (const 1)) (goto (reg continue)) false-branch4 ;; compute and return (* (factorial (- n 1)) n) (assign proc (op lookup-variable-value) (const *) (reg env)) (save continue) (save proc) ; save* procedure (assign val (op lookup-variable-value) (const n) (reg env)) (assign argl (op list) (reg val)) (save argl) ; save partial argument list for * ;; compute (factorial (- n 1)), which is the other argument for* (assign proc (op lookup-variable-value) (const factorial) (reg env)) (save proc) ; save factorial procedure

Monitor the stack operations in the tree-recursive Fibonacci computation: (define (fib \(\mathrm{n}\) ) \((\) if \((<\mathrm{n} 2)\) \(\operatorname{n}(+(\mathrm{fib}(-\mathrm{n} 1))(\mathrm{fib}(-\mathrm{n} 2))))\) a. Give a formula in terms of \(n\) for the maximum depth of the stack required to compute \(\operatorname{Fib}(n)\) for \(n \geq 2\). Hint: In section \(1.2 .2\) we argued that the space used by this process grows linearly with \(n\). b. Give a formula for the total number of pushes used to compute \(\operatorname{Fib}(n)\) for \(n \geq 2\). You should find that the number of pushes (which correlates well with the time used) grows exponentially with \(n\). Hint: Let \(S(n)\) be the number of pushes used in computing \(\operatorname{Fib}(n)\). You should be able to argue that there is a formula that expresses \(S(n)\) in terms of \(S(n-1), S(n-2)\), and some fixed "overhead" constant \(k\) that is independent of \(n\). Give the formula, and say what \(k\) is. Then show that \(S(n)\) can be expressed as \(a \mathrm{Fib}(n+1)+b\) and give the values of \(a\) and \(b\).

The simulator can be used to help determine the data paths required for implementing a machine with a given controller. Extend the assembler to store the following information in the machine model: \- a list of all instructions, with duplicates removed, sorted by instruction type (assign, goto, and so on); \- a list (without duplicates) of the registers used to hold entry points (these are the registers referenced by goto instructions); \- a list (without duplicates) of the registers that are saved or restored; \- for each register, a list (without duplicates) of the sources from which it is assigned (for example, the sources for register val in the factorial machine of figure \(5.11\) are (const 1) and ( (op *) (reg n) (reg val))). Extend the message-passing interface to the machine to provide access to this new information. To test your analyzer, define the Fibonacci machine from figure \(5.12\) and examine the lists you constructed. Exercise \(5.13\) Modify the simulator so that it uses the controller sequence to determine what registers the machine has rather than requiring a list of registers as an argument to make-machine. Instead of pre-allocating the registers in make- machine, you can allocate them one at a time when they are first seen during assembly of the instructions.

Compile the iterative factorial procedure (define (factorial n) (define (iter product counter) (if (> counter n) product (iter (* counter product) (+ counter 1)))) (iter 1 1)) Annotate the resulting code, showing the essential difference between the code for iterative and recursive versions of factorial that makes one process build up stack space and the other run in constant stack space.
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