Specflow: Can some step definitions be used feature wide? - specflow

When a feature requires some given steps, you need to specify for each scenario "Given I have done something And something else And the last thing...". Doing all those steps for every scenario can be tedious.
One solution could be to specify all this in one Given step (Given I am set up to test feature X). However, it's not something very precise while reading the feature steps.
This is why I'd like to know if step definitions can be used feature wide. I'd use something like this :
Feature: My feature
Obvious feature description here.
Given I have done something
And something else
And the last thing
Scenario: Y validation
When I type X
Then I should see Y
Scenario: Z validation
When I type X
Then I should see Z
Over this :
Feature: My feature
Obvious feature description here.
Scenario: Y validation
Given I have done something
And something else
And the last thing
When I type X
Then I should see Y
Scenario: Z validation
Given I have done something
And something else
And the last thing
When I type X
Then I should see Z
Any solution is welcome, but I'd like something that can be understood while reading the .feature file, instead of having to dig in the code.
Thanks

There a great and easy solution to your problem in Gherkin, the language used to write feature files. It's called Background and is a couple of steps that is executed before each scenario in the file.
See this wiki page for more information; https://github.com/cucumber/cucumber/wiki/Background

When using the Backgroung tag your scenarios and feature will look more or less like this:
Feature: My feature
As a person
I want to do something
So that something can happen
Background: My Background
Given I have done something
And something else
And the last thing
Scenario: Y validation
When I type X
Then I should see Y
Scenario: Z validation
When I type X
Then I should see Z

Related

How to predict a textual field on the basis of input features

I'm stuck with a problem statement of predicting an identifier for a product on the basis of couple of product features. A sample of data available to me looks like the one shown below:
ABC10L 20.0 34 XYZ G345F FG MKD -> 000000DEF_VYA
Here, ABC10L,20.0,34,XYZ,G345F,FG,MKD are the features and 000000DEF_VYA is the unique identifier associated with the product. Initially I tried to formulate this problem as a regression problem but I'm not sure how to generate textual output from my model and what should be my cost function. Also, I'm not sure is regression the right tool to solve the issue here.
Please help in suggesting the right approach and how I may proceed to solve this !!!

Z3: Complex numbers?

I have been searching on whether z3 supports complex numbers and have found the following: https://leodemoura.github.io/blog/2013/01/26/complex.html
The author states that (1) Complex numbers are not yet implemented in Z3 as a built-in (this was written in 2013), and (2) that Complex numbers can be encoded on top of the Real numbers provided by Z3.
The basic idea is to represent a Complex number as a pair of Real numbers. He defines the basic imaginary number with I=(0,1), that is: I means the real part equals 0 and the imaginary part equals 1.
He offers the encoding (I mean, we can test it on our machines), where we can solve the equation x^2+2=0. I received the following result:
sat
x = (-1.4142135623?)*I
The sat result does make sense, since this equation is solvable in the simulation of the theory of complex numbers (as a result of the theory of algebraically closed fields) we have just made. However, the root result does not make sense to me. I mean: what about (1.4142135623?)*I?
I would understand to receive the two roots, but, if only one received, I do not understand why I get the negated solution.
Maybe I misread something or I missed something.
Also, I would like to say if complex numbers have already been implemented built in Z3. I mean, with a standard:
x = Complex("x")
And with tactics of kind of a NCA (from nonlinear complex arithmetic).
I have not seen any reference to this theory in SMT-LIB either.
AFAIK there is no plan to add complex numbers to SMT-LIB. There's a Google group for SMT-LIB and it might make sense to send a post there to see if there is any interest there.
Note, that particular blog post says "find a root"; this is just satisfiability, i.e. it finds one solution, not all of them. (But you can ask for another one by adding an assertion that says x should be different from the first result.)

Deap: Want to know the generation that created the best individual

I'm running a genetic algorithm program and can find the best individual at the end of the run (hof[0]), but i want to know which generation produced it. Is there any attributes of hof[0] that will help print the individual and the generation that created it.
I tried looking at the manuals and Google for answers but could not find it anywhere.
I also couldn't find a list of the attributes of individuals that I could print. Can someone point to the right link and documentation to that.
Thanks
This deap post suggest tracking the logbook, or explicitly adding the generation to the individual along with fitness:
https://groups.google.com/g/deap-users/c/r7fZbMwHg3I/m/BAzHh2ogBAAJ
For the latter:
If you are working with the algo locally(recommended if working beyond a tutorial as something always comes up like adding plotting or this very questions) then you can modify the fitness update line to resemble:
fitnesses = toolbox.map(toolbox.evaluate, invalid_ind)
for ind, fit in zip(invalid_ind, fitnesses):
ind.fitness.values = fit
ind.generation = gen # now we can: print(hof[0].gen)
if halloffame is not None:
halloffame.update(population)
There is no built in way to do this (yet/to the best of my knowledge), and implementing this so would probably be quite a large task. The simplest of which (simplest in thought, not in implementation) would be to change the individual to be a tuple, where tup[0] is the individual and tup[1] is the generation it was produced in, or something similar.
If you're looking for a hacky way, you could maybe try writing the children of each generation to a text file and cross-checking your final solution with the text file; but other than that I'm not sure.
You could always try posting on their Google Group, though it can take a couple of days for a reply.
Good luck!

Can you "teach" computers to do algebra using variable expressions (eg aX+bX=(a+b)X)

Let's say in the example lower case is constant and upper case is variable.
I'd like to have programs that can "intelligently" do specified tasks like algebra, but teaching the program new methods should be easy using symbols understood by humans. For example if the program told these facts:
aX+bX=(a+b)X
if a=bX then X=a/b
Then it should be able to perform these operations:
2a+3a=5a
3x+3x=6x
3x=1 therefore x=1/3
4x+2x=1 -> 6x=1 therefore x= 1/6
I was trying to do similar things with Prolog as it can easily "understand" variables, but then I had too many complications, mainly because two describing a relationship both ways results in a crash. (not easy to sort out)
To summarise: I want to know if a program which can be taught algebra by using mathematic symbols only. I'd like to know if other people have tried this and how complicated it is expected to be. The purpose of this is to make programming easier (runtime is not so important)
It depends on what do you want machine to do and how intelligent it should be.
Your question is mostly about AI but not ML. AI deals with formalization of "human" tasks while ML (though being a subset of AI) is about building models from data.
Described program may be implemented like this:
Each fact form a pattern. Program given with an expression and some patterns can try to apply some of them to expression and see what happens. If you want your program to be able to, for example, solve quadratic equations given rule like ax² + bx + c = 0 → x = (-b ± sqrt(b²-4ac))/(2a) then it'd be designed as follows:
Somebody gives a set of rules. Rule consists of a pattern and an outcome (solution or equivalent form). Think about the pattern as kind of a regular expression.
Then the program is asked to show some intelligence and prove its knowledge via doing something with a given expression. Here comes the major part:
you build a graph of expressions by applying possible rules (if a pattern is applicable to an expression you add new vertex with the corresponding outcome).
Then you run some path-search algorithm (A*, for example) to find sequence of transformations leading to the form like x = ...
I think this is an interesting question, although it off topic in SO (tool recommendation)
But nevertheless, because it captured my imagination, I wrote couple of function using R that can solve stuff like that quite easily
First, you'll have to install R, after words you'll need to download package called stringr
So in R console run
install.packages("stringr")
library(stringr)
And then you can define the following functions that I wrote
FirstFunc <- function(temp){
paste0(eval(parse(text = gsub("[A-Z]", "", temp))), unique(str_extract_all(temp, "[A-Z]")[[1]]))
}
SecondFunc <- function(temp){
eval(parse(text = strsplit(temp, "=")[[1]][2])) / eval(parse(text = gsub("[[:alpha:]]", "", strsplit(temp, "=")[[1]][1])))
}
Now, the first function will solve equations like
aX+bX=(a+b)X
While the second will solve equations like
4x+2x=1
For example
FirstFunc("3X+6X-2X-3X")
will return
"4X"
Now this functions is pretty primitive (mostly for the propose of illustration) and will solve equation that contain only one variable type, something like FirstFunc("3X-2X-2Y") won't give the correct result (but the function could be easily modified)
The second function will solve stuff like
SecondFunc("4x-2x=1")
will return
0.5
or
SecondFunc("4x+2x*3x=1")
will return
0.1
Note that this function also works only for one unknown variable (x) but could be easily modified too

Backtracking in Erlang

First of all sorry for my English.
I would like to use a backtracking algorithm in Erlang. It would serve as a guessing to solve partially filled sudokus. A 9x9 sudoku is stored as a list of 81 elements, where every element stores the possible number which can go into that cell.
For a 4x4 sudoku my initial solution looks like this:
[[1],[3],[2],[4],[4],[2],[3],[1],[2,3],[4],[1],[2,3],[2,3],[1],[4],[2,3]]
This sudoku has 2 solutions. I have to write out both of them. After that initial solution reached, I need to implement a backtracking algorithm, but I don't know how to make it.
My thought is to write out the fixed elements into a new list called fixedlist which will change the multiple-solution cells to [].
For the above mentioned example the fixedlist looks like this:
[[1],[3],[2],[4],[4],[2],[3],[1],[],[4],[1],[],[],[1],[4],[]]
From here I have a "sample", I look for the lowest length in the solutionlist which is not equal to 1, and I try the first possible number of this cell and I put it to that fixedlist. Here I have an algorithm to update the cells and checks if it is still a solvable sudoku or not. If not, I don't know how to step back one and try a new one.
I know the pseudo code of it and I can use it for imperative languages but not for erlang. (prolog actually implemented backtrack algorithm, but erlang didn't)
Any idea?
Re: My bactracking functions.
These are the general functions which provide a framework for handling back-tracking and logical variables similar to a prolog engine. You must provide the function (predicates) which describe the program logic. If you write them as you would in prolog I can show you how to translate them into erlang. Very briefly you translate something like:
p :- q, r, s.
in prolog into something like
p(Next0) ->
Next1 = fun () -> s(Next0) end,
Next2 = fun () -> r(Next1) end,
q(Next2).
Here I am ignoring all other arguments except the continuations.
I hope this gives some help. As I said if you describe your algorithms I can help you translate them, I have been looking for a good example. You can, of course, just as well do it by yourself but this provides some help.

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