MASTERMINDS OF PROGRAMMING PDF
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Meyer also noted the SPARK language, a stripped-down form of Ada and thus related to Pascal which is provable evidently in large part because it lacks pointers, and thus aliasing of memory addresses.
However, I think he is hasty. I have written many small tools in my career, usually in a scripting language of some sort, and I wouldn't mind in the least if someone handed me a limited language I could use, and prove my little tools correct. I think I'd get a fair amount of satisfaction from that, particularly if it reduced the time I spent instrumenting them and chasing down bug reports about them.
There is a large space of mundane little problems in the world, and I think it's a win, not a lose, if we can implement our solutions to those small, mundane problems in robust little boxes.
It has to beat shoehorning more places into a complex system where things can go wrong. Most of the classic Unix shell utilities are written in non-OO C. Wouldn't it be awesome if we could re-implement them in a provable language? Oh, well--one can dream. Finally, I have to admit that some of the material in the book goes over my head. For example, at one point Meyer notes that dynamic binding and function pointers are incompatible language features.
I have to assume this is because the way dynamic binding is implemented is by keeping function pointers internal to the implementation, such that they are rewritten as necessary at runtime once an object's type is determined.
If one let the programmer muck with the pointers as well, there would be no guarantees that a method call would be resolvable or sensible at runtime. But I'm having to guess at this, so I could be wrong. They just call them references. There are advantages to having pointers implicit as well as disadvantages. The equivalent in Java for a user-defined container of objects of userdefined types would be 56 words: 1 for the reference to the container, plus 3 for the container, plus 10 for the references to the objects, plus 20 for the objects, plus 24 for the free store headers for the 12 independently allocated objects.
Obviously, these numbers are approximate because the free store heap overhead is implementation defined in both languages.
However, the conclusion is clear: by making references ubiquitous and implicit, Java may have simplified the programming model and the garbage collector implementation, but it has increased the memory overhead dramatically—and increased the memory access cost requiring more indirect accesses and allocation overheads proportionally. There is, however, an important place where pointers—and pointer manipulation—is a boon: the direct and efficient expression of data structures.
Scoped resource management takes care of most needs; smart pointers and specialized handles can be used to deal with most of the rest. This contrast to Java where built-in types such and char and int follow it, but user-defined types do not, and indeed cannot. As in Simula, all user-defined types in Java have reference semantics.
If that object is a scoped variable, the lifetime of the variable puts a maximum limit on the time the resource is held. Typically, a constructor acquires the resource and the destructor releases it. Obviously, not every resource can be handled in this way, but many can, and for those, resource management becomes implicit and efficient.
Bjarne: I think top-down and bottom-up are the wrong way to characterize those design decisions. This pervades both the basic language facilities and the abstraction facilities in ways that are not shared by all languages.
Using the Language How do you debug? Bjarne: By introspection. I study the program for so long and poke at it more or less systematically for so long that I have sufficient understanding to provide an educated guess where the bug is.
Testing is something else, and so is design to minimize errors. I intensely dislike debugging and will go a long way to avoid it. If I am the designer of a piece of software, I build it around interfaces and invariants so that it is hard to get seriously bad code to compile and run incorrectly. Then, I try hard to make it testable. Testing is the systematic search for errors.
It is hard to systematically test badly structured systems, so I again recommend a clean structure of the code. Testing can be automated and is repeatable in a way that debugging is not.
Having flocks of pigeons randomly peck at the screen to see if they can break a GUI-based application is no way to ensure quality systems. It is hard to give general advice because the best techniques often depend on what is feasible for a given system in a given development environment.
However: identify key interfaces that can be systematically tested and write test scripts that exercise those. Automate as much as you can and run those automated tests often. And do keep regression tests and run them frequently. Make sure that every entry point into the system and every output can be systematically tested.
Compose your system out of quality components: monolithic programs are unnecessarily hard to understand and test. At what level is it necessary to improve the security of software? Bjarne: First of all: security is a systems issue.
Masterminds Of Programming
No localized or partial remedy will by itself succeed. Remember, even if all of your code was perfect, I could probably still gain access to your stored secrets if I could steal your computer or the storage device holding your backup. Actually, I prefer not to keep important secrets online and leave serious security to the experts.
But what about programming languages and programming techniques?
ABC (programming language)
This is a most dangerous notion that leaves the code littered with unsystematic tests guarding against ill-formulated imagined threats. It also makes code ugly, large, and slow.
There has to be a place behind a barrier where code can be written simply, elegantly, and efficiently without worrying about random pieces of code abusing random pieces of other code.
Only then can we focus on correctness, quality, and serious performance. The idea that anyone can provide an untrusted callback, plug-in, overrider, whatever, is plain silly. We have to distinguish between code that defends against fraud, and code that simply is protected against accidents. I do not think that you can design a programming language that is completely secure and also useful for real-world systems.
They are stuck in an 80s style of programming.
Bjarne: Certainly, I do recommend it and not everybody is reluctant. Is it something in the OO paradigm? In addition, GCC was slow to mature.
Some people in the C community seem to maintain an almost willful ignorance based on decade-old experiences. The most relevant other paradigm in the context of high-performance and close-to-the-hardware use is generic programming sometimes abbreviated to GP. There is nothing that requires you to go hog-wild with exceptions, class hierarchies, or templates.
A good programmer uses the more advanced features where they help more directly to express ideas and do so without avoidable overheads. Bjarne: You seem to assume that code first was written in C and that the programmer started out as a C programmer. I have seen people do that and be very happy with the problems they left behind. People can—if they so choose—use those just like the built-in types.
I would say no. That is major leverage in many applications and a major step up in abstraction from C. Beyond that, people can start to benefit from libraries, such as Boost, and start to appreciate some of the functional programming techniques inherent in generic programming.
However, I think the question is slightly misleading.
A few favourites
OOP and Concurrency The average complexity and size in number of lines of code of software seems to grow year after year.
Does OOP scale well to this situation or just make things more complicated? I have the feeling that the desire to make reusable objects makes things more complicated and, in the end, it doubles the workload.
Key features include:. ABC was originally a monolithic implementation , leading to an inability to adapt to new requirements, such as creating a graphical user interface.
ABC could not directly access the underlying file system and operating system. This article is based on material taken from the Free On-line Dictionary of Computing prior to 1 November and incorporated under the "relicensing" terms of the GFDL , version 1. From Wikipedia, the free encyclopedia. ABC Paradigm multi-paradigm: Masterminds of Programming:Bjarne: I think top-down and bottom-up are the wrong way to characterize those design decisions.
We have tried to minimize impact by choosing new keywords that are not heavily used.
So when parallel computing and Single Instruction, Multiple Data came along, APL folks updated their compilers, and all existing APL programs were magically faster without any tweaking.
Why did you choose to support multiple paradigms? One of the interesting things was they wanted SQL to be used by users, not just developers. Forth, Chuck Moore Forth is a small and very nifty language that holds a special place in my heart.
Most of the classic Unix shell utilities are written in non-OO C. Yes, one could argue that the over-engineered modeling language has turned into a programming language driven by case-tools.