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I remember reading an article saying something like
"The number of bugs introduced doesn't vary much with different programming languages, but it depends pretty much on SLOC (source lines of code). So, using the programming language that can implement the same functions with smaller SLOC is preferable in terms of stability."
The author wanted to stress the advantages of using Functional Programming, as normally one can program with a smaller number of LOC. I remember the author cited a research paper about the irrelevance of choice of programming language and the number of bugs.
Is there anyone who knows the research paper or the article?
Paul Graham wrote something very like this in his essay Succinctness is Power. He quotes a report from Ericsson, which may be the paper you remember?
Reports from the field, though they will necessarily be less precise than "scientific" studies, are likely to be more meaningful. For example, Ulf Wiger of Ericsson did a study that concluded that Erlang was 4-10x more succinct than C++, and proportionately faster to develop software in:
Comparisons between Ericsson-internal development projects indicate similar line/hour productivity, including all phases of software development, rather independently of which language (Erlang, PLEX, C, C++, or Java) was used. What differentiates the different languages then becomes source code volume.
I'm not sure if it's the source you're thinking of, but there's something about this in Code Complete chapter 27.3 (p652) - that references "Program Quality and Programmer Productivity" (Jones 1977) and "Estimating Software Costs" (Jones 1998).
I've seen this argument about "succinctness = power" a few times, and I've never really bought it. That's because there are languages (e.g., J, Ursala) which are quite succinct but not (IMO) easy to read because they put so much meaning into individual symbols.
Perhaps the true metric should be the extent to which it is possible to write a particular algorithm both clearly and succinctly. Mind you, I don't know how to measure that.
The book of pragmatic Thinking & Learning points to this article.
Can a Manufacturing Quality Model Work for Software?
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Can anyone gives some suggestions for good natural language processing book. Following are the factors I have in mind:
It gives a good overview of these huge topics without too much depth.
Concepts need to explain in picture form.
Sample code in JAVA/Python/R.
You can look at online courses about NLP. They oftain contain videos, exercices, writing documents, suggested readings...
I especially like this one : https://www.coursera.org/course/nlp (see suggested readings section for instance). You can access the lectures here : https://class.coursera.org/nlp/lecture (pdf + video + subtitles).
I believe there are three options for you--I wrote one of them so take this with a grain of salt.
1) Natural Language Processing with Python
by Steven Bird et al. http://amzn.com/0596516495. This book covers using the NLP api NLTK and is considered a solid book for intro to NLP. Lots of code, a more academic take on what NLP is and I assume broadly used in undergraduate NLP classes.
2) Natural Language Processing with Java by Richard Reese http://amzn.to/1D0liUY. This covers a range of APIs, including LingPipe below, and introduces NLP concepts and how they are implemented in a range of open source APIs. It is a more shallow dive into NLP but it is a gentler introduction and it covers how a bunch of APIs solve the same problem so it may help you pick what API to use.
3) Natural Language Processing with Java and LingPipe Cookbook by Breck Baldwin (me) and Krishna Dayanidhi http://amzn.to/1MvgHxa. This is meant for industrial programmers and it covers the concepts common in commercial NLP applications. The book is a much deeper dive into evaluation, problem specification, varied technologies that on the face do the same thing. But it expects you to learn from examples (overwhelmingly Twitter data).
All the books have lots of code, one in Python, the other two in Java. Both present mature APIs with a large installed base.
None of the books do much in the way of graphical explanation of what the software is doing.
Good luck
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I'd like to model software components and their interaction between them, what information is passed, what processes take place in each component(not too detailed) and a clear specification of the input/output of the components.
What i've seen so far in UML is far too abstract and doesn't go into too much detail.
Any suggestions?
Someg guys Design programs on papers as diagrams,
Then pass them to software developer to Contruct.
This appraoach is tried: "Clever guys" do modeling, and pass models to "ordinary" developers to do laborious task. And this not worked.
We like analogies. So many times we make analogy to construction industry where some guys do models-bluprints and other do building-contruction.And we first think that UML or other models diagrams are equivalent to construction industry models-blueprints. But it seems that we are wrong.
To make an analogy with construction industry our blueprints are not
models-diagrams, our blueprints are actually the code we write.
Detailed Paper Models like Cooking Receipes
It is not realistic to design a software system entirely on a paper with detailed models upfront.Software development is iterative and incremental process.
Think of a map maker who make a paper map of city as big as city, since the modeler include every details without any abstraction level.Will it be usefull?
Is Modeling Useless ?
Definitely not. But you should apply it to difficult part of your problem-solution space, not every trival part of them.
So instead of giving every details of system on paper to developers, explore difficult part of problem-solution space with developers face to face using visual diagrams.
In software industry like it or hate it, Source Code is still the
King. And all models are liar until they are implemented and tested
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I want to solve geometry problems in online programming contests. But whenever I read them, I just find too difficult. Please suggest some books and resources which I can study computational geometry.
A classic work: Computational Geometry in C.
And there's also: http://www.cs.uu.nl/geobook/.
In order to solve basic geometry problems quickly, so that it runs within the time limits of the contest, you need to make certain you have a strong grasp of writing algorithms.
This page has some good suggestions on how to get better. It is set up as a two semester course of reading.
http://mrmbdctg.freehostia.com/contest_Tipsforbeginner.html
You can try the problem archive on TopCoder.
But you should register first.
On the filter choose:
Category: Geometry
Division II Level: Level One or Level Two.
Almost all problems have description of solutions.
They are pretty simple in comparison you choose random geometric problem from some contest archive.
On the page you can also find a lot of tutorials, including geometric ones.
I recommend two books (among others):
The Algorithm Design Manual By Steven S. Skiena - discusses algorithms in general, but has a lot of useful information about computational geometry
Computational Geometry: Algorithms and Applications
If you want to clear your basics, this is a good starting point - https://www.hackerearth.com/notes/computational-geometry-i-1/. There are some practice problems as well in the article.
You should also read through this article - http://www.toptal.com/python/computational-geometry-in-python-from-theory-to-implementation that covers some advanced concepts.
You must know convex hull and point-in-polygon. Often on TopCoder people create a reusable library for geometry applications, since the same is code is used many times.
Check lbackstrom's tutorial for start. Computional Geometry by de Berg, Cheong, van Kreveld, Overmars [edit: already mentioned by Bart] might be more than you need.
And of course there's Computational Geometry - An Introduction, by Preparata and Shamos. I own it, and recommend it for an introduction to the principles. Not really a dictionary of code, though.
Here are two excellent books, I used them as textbooks at university:
J D Foley, A van Dam et al. Introduction to Computer Graphics. Addison-Wesley, 1994, ISBN 0-201-60921-5.
D Hearn and M P Baker. Computer Graphics with Open GL (3rd edition). Prentice-Hall, 2004, ISBN 0-13-120238-3.
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I would like to write an interactive song. It would contain state and logic. A listener/user should be able to modify some state vars using a GUI or a MIDI interface. Listener accessible vars don't have to directly represent tempo, pitch or any other music property. They would rather represent values that logic would process in order to make changes to the song.
Do I have to write such platform myself or something fitting my imagination already exists?
Look at cSounds and PureData.
If you are happy to use Java, check out JFugue.
I have tried PureData, CSound and SuperCollider.
CSound is very cumbersome to program in, and has had severe stability issues for my requirements (24bit/96kHz realtime low latency linux) in version 4.
PureData is graphical, which makes it even harder to keep code neat and tidy then with text files. Composing is a pain because you have to build your own composition GUI, which can be powerful, but as long as I'm my only user I find it's just faster to use text.
The winner hands down is SuperCollider, because it is a smalltalk inspired object oriented language which is quite pleasant to work with. It is split into an OSC controlled sound server, and the client language. I can recommend the sound synthesis server and using the language to create instruments without reservation for its excellent stability, great flexibility and incredible power. I've used it live on stage and the performance is incredibly good.
The score creation language suffers from many-hands syndrome; in lack of recent clear leadership there are too many ways to do too many things with too many limitations, but it is still better than CSound because at least you can use reasonable high level structures.
Still looking for a composition language that just gets it right.
Have a look at Strasheela:
It's a composition system based on the programming language Oz. Learning Oz isn't easy, as it it combines the functional and the logic programming paradigm. However if you liked the SICP book, then you will probably like it too.
Strasheela treats music composition as a Constraint Statisfaction Problem (CSP), and seeks "solutions" for it. It means that the music style is defined as mathematical constraints on integer numbers (finite domain), that must be statisfied, and the built-in constraint solving system computes the solutions "automatically".
P.S.: I cannot program in Oz, but I'm on my way of learning it.
See High level languages for Computer Music and Programming Languages used for music for help.
I am not sure if it covers what you are after for, but have a look at Java Sound API. For a FAQ about what it can do see here. The benefits are that is already bundled in the SDK and JRE and that is cross platform. Also, you could build the GUI using any Java toolkit.
If it weren't for the interactive bits, I'd suggest looking at Haskore or Nyquist, both effectively being DSLs for music generation.
Definitely take a look at Alex McLean's livecoding demos, though. It's more flexible and interactive as you can possibly imagine, using SuperCollider through OpenSoundControl.
Answer is for .NET:
I found something, checkout NAudio by Mark Heath, a great .NET music library I would say it should be contained in the BCL.
midi-dot-net is another great C# project by Tom Lokovic.
For music interaction, PureData, Max/MSP and OpenMusic (these two last are from IRCAM) are the best. PureData is freeware. Google them!
I don't really get what you want to do, but here is a list of some CL music software, both for composition and cognition: http://www.cliki.net/Music
You're looking for an Audio Programming Language. Another option you should consider is Processing - used by many artists and musicians for this type of work.
-Adam
Its a shame that none said about Chuck................
Chuck is a programming language that is specifically built for music/audio generation and composition.
You can download Chuck at http://chuck.stanford.edu
its a lot easier to use,and is a lot familiar to c,c++,java etc,however its easier to learn too.You can find at Coursera about chuck for free from California arts university,link here.
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Can anyone point me towards any references that attempt to formulate an economics of software development? In my own research, I discovered a book by Barry Boehm on this, but it seems very awkward and theoretical.
Dependency Structure Matrices seem to offer something worthwhile. Carliss Baldwin has used these in some work on modularization, boundaries, and transaction costs. A lot of it comes off as just common sense, though.
Also, economists have developed something called Behavioral Economics. Is there a "Behavioral Software Engineering" that addresses cognitive biases in developers or groups of developers?
Here's an interesting looking reference:
http://www.amazon.com/Knowledge-Sharing-Software-Development-Comparing/dp/3639100840/ref=sr_1_1?ie=UTF8&s=books&qid=1232979573&sr=1-1
Before Hal Varian became the Chief Economist at Google, he had worked on the economics of information technology at Berkeley, although he did not focus on software development per se. Nevertheless I would recommend a look at his paper on the more general topic from 2001. You can find a more complete list of his research work on his website. Hope that helps.
Software as Capital wasn't a waste of time, though you won't find any math in it and it reads like a PhD thesis because it started as one.
Another review.
I think that what you're looking for might fall under a sociology of software development... sociologists study all modern subjects, and from there you will no doubt find references to an economics of software development if there is one.
Facts and Fallacies of Software Engineering by Robert Glass has some dollar amounts associated with some activities (or, at least, percentage of total budget). Don't know if that helps at all, but it's something.
Several years ago I taught an "Economics of E-Commerce" course using Varian's book INFORMATION RULES. His idea of lock-in, though, leads the reader almost towards a drug-addict model of purchaser behaviour and exploitation. This book is more of an economics of e-business than an analysis of the software development process.
In terms of actually making software, there are ideas in the Mythical Man Month well worth knowing about.
The "Applied Information Economics" approach of Douglas Hubbard could be part of what you're looking for. If we assume software development is (often|always|sometimes|???) about supporting decision making by providing (better|more accurate|more up to date|whatever) information, then AIE helps as it's a technique for quantifying the value of better information. Read Hubbard's book How to Measure Anything for a good overview of the idea.
Also, the book Software By Numbers by Mark Denne and Jane Cleland-Huang provides a model for managing software projects by using something they call the "Incremental Funding Methodology". IFM is based on decomposing software projects into features based on the business value created, rather than decomposing them along technical boundaries. They then use a series of calculations based on Discounted Cash Flow (DCF), Net Present Value (NPV), Internal Rate of Return (IRR), etc. to show when in the project lifecycle the project will reach self-funding status, when it will reach "breakeven" and when it will generate a real positive cash return for the organization.
You might also find the Capability Cases book of interest. It doesn't strictly deal with any economic issues in detail, but it's an approach to software specification which attempts to more clearly map software capabilities to business strategy and business issues.