== DESCRIPTION: The RightScale AWS gems have been designed to provide a robust, fast, and secure interface to Amazon EC2, EBS, S3, SQS, SDB, and CloudFront. These gems have been used in production by RightScale since late 2006 and are being maintained to track enhancements made by Amazon. The RightScale AWS gems comprise: - RightAws::Ec2 -- interface to Amazon EC2 (Elastic Compute Cloud) and the associated EBS (Elastic Block Store) - RightAws::S3 and RightAws::S3Interface -- interface to Amazon S3 (Simple Storage Service) - RightAws::Sqs and RightAws::SqsInterface -- interface to first-generation Amazon SQS (Simple Queue Service) (API version 2007-05-01) - RightAws::SqsGen2 and RightAws::SqsGen2Interface -- interface to second-generation Amazon SQS (Simple Queue Service) (API version 2008-01-01) - RightAws::SdbInterface and RightAws::ActiveSdb -- interface to Amazon SDB (SimpleDB) - RightAws::AcfInterface -- interface to Amazon CloudFront, a content distribution service == FEATURES: - Full programmmatic access to EC2, EBS, S3, SQS, SDB, and CloudFront. - Complete error handling: all operations check for errors and report complete error information by raising an AwsError. - Persistent HTTP connections with robust network-level retry layer using RightHttpConnection). This includes socket timeouts and retries. - Robust HTTP-level retry layer. Certain (user-adjustable) HTTP errors returned by Amazon's services are classified as temporary errors. These errors are automaticallly retried using exponentially increasing intervals. The number of retries is user-configurable. - Fast REXML-based parsing of responses (as fast as a pure Ruby solution allows). - Uses libxml (if available) for faster response parsing. - Support for large S3 list operations. Buckets and key subfolders containing many (> 1000) keys are listed in entirety. Operations based on list (like bucket clear) work on arbitrary numbers of keys. - Support for streaming GETs from S3, and streaming PUTs to S3 if the data source is a file. - Support for single-threaded usage, multithreaded usage, as well as usage with multiple AWS accounts. - Support for both first- and second-generation SQS (API versions 2007-05-01 and 2008-01-01). These versions of SQS are not compatible. - Support for signature versions 0 and 1 on SQS, SDB, and EC2. - Interoperability with any cloud running Eucalyptus (http://eucalyptus.cs.ucsb.edu) - Test suite (requires AWS account to do "live" testing).
Diff::LCS computes the difference between two Enumerable sequences using the McIlroy-Hunt longest common subsequence (LCS) algorithm. It includes utilities to create a simple HTML diff output format and a standard diff-like tool. This is release 1.4.3, providing a simple extension that allows for Diff::LCS::Change objects to be treated implicitly as arrays and fixes a number of formatting issues. Ruby versions below 2.5 are soft-deprecated, which means that older versions are no longer part of the CI test suite. If any changes have been introduced that break those versions, bug reports and patches will be accepted, but it will be up to the reporter to verify any fixes prior to release. The next major release will completely break compatibility.
CI::Reporter is an add-on to Ruby testing frameworks that allows you to generate XML reports of your test runs. The resulting files can be read by a continuous integration system that understands Ant's JUnit report format.
Test coverage reports for Xcode projects
Collects test coverage data from your Ruby test suite and sends it to Code Climate's hosted, automated code review service. Based on SimpleCov.
Parallel tests across CI server nodes based on each test file's time execution. It generates a test time execution report and uses it for future test runs.
Ruby gem to merge Cucumber JSON reports and build mobile-friendly HTML Test Report, JSON report and retry file.
A suite for basic and advanced statistics on Ruby. Tested on CRuby 1.9.3, 2.0.0 and 2.1.1. See `.travis.yml` for more information. Include: - Descriptive statistics: frequencies, median, mean, standard error, skew, kurtosis (and many others). - Correlations: Pearson's r, Spearman's rank correlation (rho), point biserial, tau a, tau b and gamma. Tetrachoric and Polychoric correlation provides by statsample-bivariate-extension gem. - Intra-class correlation - Anova: generic and vector-based One-way ANOVA and Two-way ANOVA, with contrasts for One-way ANOVA. - Tests: F, T, Levene, U-Mannwhitney. - Regression: Simple, Multiple (OLS), Probit and Logit - Factorial Analysis: Extraction (PCA and Principal Axis), Rotation (Varimax, Equimax, Quartimax) and Parallel Analysis and Velicer's MAP test, for estimation of number of factors. - Reliability analysis for simple scale and a DSL to easily analyze multiple scales using factor analysis and correlations, if you want it. - Dominance Analysis, with multivariate dependent and bootstrap (Azen & Budescu) - Sample calculation related formulas - Structural Equation Modeling (SEM), using R libraries +sem+ and +OpenMx+ - Creates reports on text, html and rtf, using ReportBuilder gem - Graphics: Histogram, Boxplot and Scatterplot.
Cucumber adaptor to generate rich allure test reports
Cucumber adaptor to generate rich allure test reports
Get automatic inline test reporting for JUnit-conforming XML files.
# Excel to Code [![Tests Passing](https://travis-ci.org/tamc/excel_to_code.svg?branch=master)](https://travis-ci.org/tamc/excel_to_code) excel_to_c - roughly translate some Excel files into C. excel_to_ruby - roughly translate some Excel files into Ruby. This allows spreadsheets to be: 1. Embedded in other programs, such as web servers, or optimisers 2. Without depending on any Microsoft code For example, running [these commands](examples/simple/compile.sh) turns [this spreadsheet](examples/simple/simple.xlsx) into [this Ruby code](examples/simple/ruby/simple.rb) or [this C code](examples/simple/c/simple.c). # Install Requires Ruby. Install by: gem install excel_to_code # Run To just have a go: excel_to_c <excel_file_name> This will produce a file called excelspreadsheet.c For a more complex spreadsheet: excel_to_c --compile --run-tests --settable <name of input worksheet> --prune-except <name of output worksheet> <excel file name> See the full list of options: excel_to_c --help # Gotchas, limitations and bugs 0. No custom functions, no macros for generating results 1. Results are cached. So you must call reset(), then set values, then read values. 2. It must be possible to replace INDIRECT and OFFSET formula with standard references at compile time (e.g., INDIRECT("A"&"1") is fine, INDIRECT(userInput&"3") is not. 3. Doesn't implement all functions. [See which functions are implemented](docs/Which_functions_are_implemented.md). 4. Doesn't implement references that involve range unions and lists (but does implement standard ranges) 5. Sometimes gives cells as being empty, when excel would give the cell as having a numeric value of zero 6. The generated C version does not multithread and will give bad results if you try. 7. The generated code uses floating point, rather than fully precise arithmetic, so results can differ slightly. 8. The generated code uses the sprintf approach to rounding (even-odd) rather than excel's 0.5 rounds away from zero. 9. Ranges like this: Sheet1!A10:Sheet1!B20 and 3D ranges don't work. Report bugs: <https://github.com/tamc/excel_to_code/issues> # Changelog See [Changes](CHANGES.md). # License See [License](LICENSE.md) # Hacking Source code: <https://github.com/tamc/excel_to_code> Documentation: * [Installing from source](docs/installing_from_source.md) * [Structure of this project](docs/structure_of_this_project.md) * [How does the calculation work](docs/how_does_the_calculation_work.md) * [How to fix parsing errors](docs/How_to_fix_parsing_errors.md) * [How to implement a new Excel function](docs/How_to_add_a_missing_function.md) Some notes on how Excel works under the hood: * [The Excel file structure](docs/implementation/excel_file_structure.md) * [Relationships](docs/implementation/relationships.md) * [Workbooks](docs/implementation/workbook.md) * [Worksheets](docs/implementation/worksheets.md) * [Cells](docs/implementation/cell.md) * [Tables](docs/implementation/tables.md) * [Shared Strings](docs/implementation/shared_strings.md) * [Array formulae](docs/implementation/array_formulae.md)
rcov is a code coverage tool for Ruby. It is commonly used for viewing overall test unit coverage of target code. It features fast execution (20-300 times faster than previous tools), multiple analysis modes, XHTML and several kinds of text reports, easy automation with Rake via a RcovTask, fairly accurate coverage information through code linkage inference using simple heuristics, colorblind-friendliness...
"Code coverage tool for ruby 2.0 to 2.3. Simply "require 'coco'" from rspec or unit/test. Build simple html report. Report sources that have no tests. Configurable if you need to.
Connects CI::Reporter to Test::Unit
Track test executions and report to Buildkite Test Analytics
Report your Ruby app test suite code coverage with Danger.
Inventory Inventory keeps track of the contents of your Ruby¹ projects. Such an inventory can be used to load the project, create gem specifications and gems, run unit tests, compile extensions, and verify that the project’s content is what you think it is. ¹ See http://ruby-lang.org/ § Usage Let’s begin by discussing the project structure that Inventory expects you to use. It’s pretty much exactly the same as the standard Ruby project structure¹: ├── README ├── Rakefile ├── lib │ ├── foo-1.0 │ │ ├── bar.rb │ │ └── version.rb │ └── foo-1.0.rb └── test └── unit ├── foo-1.0 │ ├── bar.rb │ └── version.rb └── foo-1.0.rb Here you see a simplified version of a project called “Foo”’s project structure. The only real difference from the standard is that the main entry point into the library is named “foo-1.0.rb” instead of “foo.rb” and that the root sub-directory of “lib” is similarly named “foo-1.0” instead of “foo”. The difference is the inclusion of the API version. This must be the major version of the project followed by a constant “.0”. The reason for this is that it allows concurrent installations of different major versions of the project and means that the wrong version will never accidentally be loaded with require. There’s a bigger difference in the content of the files. ‹Lib/foo-1.0/version.rb› will contain our inventory instead of a String: require 'inventory-1.0' class Foo Version = Foo.new(1, 4, 0){ authors{ author 'A. U. Thor', 'a.u.thor@example.org' } homepage 'http://example.org/' licenses{ license 'LGPLv3+', 'GNU Lesser General Public License, version 3 or later', 'http://www.gnu.org/licenses/' } def dependencies super + Dependencies.new{ development 'baz', 1, 3, 0 runtime 'goo', 2, 0, 0 optional 'roo-loo', 3, 0, 0, :feature => 'roo-loo' } end def package_libs %w[bar.rb] end } end We’re introducing quite a few concepts at once, and we’ll look into each in greater detail, but we begin by setting the ‹Version› constant to a new instance of an Inventory with major, minor, and patch version atoms 1, 4, and 0. Then we add a couple of dependencies and list the library files that are included in this project. The version numbers shouldn’t come as a surprise. These track the version of the API that we’re shipping using {semantic versioning}². They also allow the Inventory#to_s method to act as if you’d defined Version as ‹'1.4.0'›. Next follows information about the authors of the project, the project’s homepage, and the project’s licenses. Each author has a name and an email address. The homepage is simply a string URL. Licenses have an abbreviation, a name, and a URL where the license text can be found. We then extend the definition of ‹dependencies› by adding another set of dependencies to ‹super›. ‹Super› includes a dependency on the version of the inventory project that’s being used with this project, so you’ll never have to list that yourself. The other three dependencies are all of different kinds: development, runtime, and optional. A development dependency is one that’s required while developing the project, for example, a unit-testing framework, a documentation generator, and so on. Runtime dependencies are requirements of the project to be able to run, both during development and when installed. Finally, optional dependencies are runtime dependencies that may or may not be required during execution. The difference between runtime and optional is that the inventory won’t try to automatically load an optional dependency, instead leaving that up to you to do when and if it becomes necessary. By that logic, runtime dependencies will be automatically loaded, which is a good reason for having dependency information available at runtime. The version numbers of dependencies also use semantic versioning, but note that the patch atom is ignored unless the major atom is 0. You should always only depend on the major and minor atoms. As mentioned, runtime dependencies will be automatically loaded and the feature they try to load is based on the name of the dependency with a “-X.0” tacked on the end, where ‘X’ is the major version of the dependency. Sometimes, this isn’t correct, in which case the :feature option may be given to specify the name of the feature. You may also override other parts of a dependency by passing in a block to the dependency, much like we’re doing for inventories. The rest of an inventory will list the various files included in the project. This project only consists of one additional file to those that an inventory automatically include (Rakefile, README, the main entry point, and the version.rb file that defines the inventory itself), namely the library file ‹bar.rb›. Library files will be loaded automatically when the main entry point file loads the inventory. Library files that shouldn’t be loaded may be listed under a different heading, namely “additional_libs”. Both these sets of files will be used to generate a list of unit test files automatically, so each library file will have a corresponding unit test file in the inventory. We’ll discuss the different headings of an inventory in more detail later on. Now that we’ve written our inventory, let’s set it up so that it’s content gets loaded when our main entry point gets loaded. We add the following piece of code to ‹lib/foo-1.0.rb›: module Foo load File.expand_path('../foo-1.0/version.rb', __FILE__) Version.load end That’s all there’s to it. The inventory can also be used to great effect from a Rakefile using a separate project called Inventory-Rake³. Using it’ll give us tasks for cleaning up our project, compiling extensions, installing dependencies, installing and uninstalling the project itself, and creating and pushing distribution files to distribution points. require 'inventory-rake-1.0' load File.expand_path('../lib/foo-1.0/version.rb', __FILE__) Inventory::Rake::Tasks.define Foo::Version Inventory::Rake::Tasks.unless_installing_dependencies do require 'lookout-rake-3.0' Lookout::Rake::Tasks::Test.new end It’s ‹Inventory::Rake::Tasks.define› that does the heavy lifting. It takes our inventory and sets up the tasks mentioned above. As we want to be able to use our Rakefile to install our dependencies for us, the rest of the Rakefile is inside the conditional #unless_installing_dependencies, which, as the name certainly implies, executes its block unless the task being run is the one that installs our dependencies. This becomes relevant when we set up Travis⁴ integration next. The only conditional set-up we do in our Rakefile is creating our test task via Lookout-Rake⁵, which also uses our inventory to find the unit tests to run when executed. Travis integration is straightforward. Simply put before_script: - gem install inventory-rake -v '~> VERSION' --no-rdoc --no-ri - rake gem:deps:install in the project’s ‹.travis.yml› file, replacing ‹VERSION› with the version of Inventory-Rake that you require. This’ll make sure that Travis installs all development, runtime, and optional dependencies that you’ve listed in your inventory before running any tests. You might also need to put env: - RUBYOPT=rubygems in your ‹.travis.yml› file, depending on how things are set up. ¹ Ruby project structure: http://guides.rubygems.org/make-your-own-gem/ ² Semantic versioning: http://semver.org/ ³ Inventory-Rake: http://disu.se/software/inventory-rake-1.0/ ⁴ Travis: http://travis-ci.org/ ⁵ Lookout-Rake: http://disu.se/software/lookout-rake-3.0/ § API If the guide above doesn’t provide you with all the answers you seek, you may refer to the API¹ for more answers. ¹ See http://disu.se/software/inventory-1.0/api/Inventory/ § Financing Currently, most of my time is spent at my day job and in my rather busy private life. Please motivate me to spend time on this piece of software by donating some of your money to this project. Yeah, I realize that requesting money to develop software is a bit, well, capitalistic of me. But please realize that I live in a capitalistic society and I need money to have other people give me the things that I need to continue living under the rules of said society. So, if you feel that this piece of software has helped you out enough to warrant a reward, please PayPal a donation to now@disu.se¹. Thanks! Your support won’t go unnoticed! ¹ Send a donation: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=now@disu.se&item_name=Inventory § Reporting Bugs Please report any bugs that you encounter to the {issue tracker}¹. ¹ See https://github.com/now/inventory/issues § Authors Nikolai Weibull wrote the code, the tests, the documentation, and this README. § Licensing Inventory is free software: you may redistribute it and/or modify it under the terms of the {GNU Lesser General Public License, version 3}¹ or later², as published by the {Free Software Foundation}³. ¹ See http://disu.se/licenses/lgpl-3.0/ ² See http://gnu.org/licenses/ ³ See http://fsf.org/
Like Rails' assert_difference, but more compact and readable syntax through hashes, testing ranges and improved error reporting.
CQL is a domain specific language used for querying a Cucumber (or other Gherkin based) test suite. The goal of CQL is to increase the ease with which useful information can be extracted from a modeled test suite and turned into summarized data or reports.
Lookout Lookout is a unit testing framework for Ruby¹ that puts your results in focus. Tests (expectations) are written as follows expect 2 do 1 + 1 end expect ArgumentError do Integer('1 + 1') end expect Array do [1, 2, 3].select{ |i| i % 2 == 0 } end expect [2, 4, 6] do [1, 2, 3].map{ |i| i * 2 } end Lookout is designed to encourage – force, even – unit testing best practices such as • Setting up only one expectation per test • Not setting expectations on non-public APIs • Test isolation This is done by • Only allowing one expectation to be set per test • Providing no (additional) way of accessing private state • Providing no setup and tear-down methods, nor a method of providing test helpers Other important points are • Putting the expected outcome of a test in focus with the steps of the calculation of the actual result only as a secondary concern • A focus on code readability by providing no mechanism for describing an expectation other than the code in the expectation itself • A unified syntax for setting up both state-based and behavior-based expectations The way Lookout works has been heavily influenced by expectations², by {Jay Fields}³. The code base was once also heavily based on expectations, based at Subversion {revision 76}⁴. A lot has happened since then and all of the work past that revision are due to {Nikolai Weibull}⁵. ¹ Ruby: http://ruby-lang.org/ ² Expectations: http://expectations.rubyforge.org/ ³ Jay Fields’s blog: http://blog.jayfields.com/ ⁴ Lookout revision 76: https://github.com/now/lookout/commit/537bedf3e5b3eb4b31c066b3266f42964ac35ebe ⁵ Nikolai Weibull’s home page: http://disu.se/ § Installation Install Lookout with % gem install lookout § Usage Lookout allows you to set expectations on an object’s state or behavior. We’ll begin by looking at state expectations and then take a look at expectations on behavior. § Expectations on State: Literals An expectation can be made on the result of a computation: expect 2 do 1 + 1 end Most objects, in fact, have their state expectations checked by invoking ‹#==› on the expected value with the result as its argument. Checking that a result is within a given range is also simple: expect 0.099..0.101 do 0.4 - 0.3 end Here, the more general ‹#===› is being used on the ‹Range›. § Regexps ‹Strings› of course match against ‹Strings›: expect 'ab' do 'abc'[0..1] end but we can also match a ‹String› against a ‹Regexp›: expect %r{a substring} do 'a string with a substring' end (Note the use of ‹%r{…}› to avoid warnings that will be generated when Ruby parses ‹expect /…/›.) § Modules Checking that the result includes a certain module is done by expecting the ‹Module›. expect Enumerable do [] end This, due to the nature of Ruby, of course also works for classes (as they are also modules): expect String do 'a string' end This doesn’t hinder us from expecting the actual ‹Module› itself: expect Enumerable do Enumerable end or the ‹Class›: expect String do String end for obvious reasons. As you may have figured out yourself, this is accomplished by first trying ‹#==› and, if it returns ‹false›, then trying ‹#===› on the expected ‹Module›. This is also true of ‹Ranges› and ‹Regexps›. § Booleans Truthfulness is expected with ‹true› and ‹false›: expect true do 1 end expect false do nil end Results equaling ‹true› or ‹false› are slightly different: expect TrueClass do true end expect FalseClass do false end The rationale for this is that you should only care if the result of a computation evaluates to a value that Ruby considers to be either true or false, not the exact literals ‹true› or ‹false›. § IO Expecting output on an IO object is also common: expect output("abc\ndef\n") do |io| io.puts 'abc', 'def' end This can be used to capture the output of a formatter that takes an output object as a parameter. § Warnings Expecting warnings from code isn’t very common, but should be done: expect warning('this is your final one!') do warn 'this is your final one!' end expect warning('this is your final one!') do warn '%s:%d: warning: this is your final one!' % [__FILE__, __LINE__] end ‹$VERBOSE› is set to ‹true› during the execution of the block, so you don’t need to do so yourself. If you have other code that depends on the value of $VERBOSE, that can be done with ‹#with_verbose› expect nil do with_verbose nil do $VERBOSE end end § Errors You should always be expecting errors from – and in, but that’s a different story – your code: expect ArgumentError do Integer('1 + 1') end Often, not only the type of the error, but its description, is important to check: expect StandardError.new('message') do raise StandardError.new('message') end As with ‹Strings›, ‹Regexps› can be used to check the error description: expect StandardError.new(/mess/) do raise StandardError.new('message') end § Queries Through Symbols Symbols are generally matched against symbols, but as a special case, symbols ending with ‹?› are seen as expectations on the result of query methods on the result of the block, given that the method is of zero arity and that the result isn’t a Symbol itself. Simply expect a symbol ending with ‹?›: expect :empty? do [] end To expect it’s negation, expect the same symbol beginning with ‹not_›: expect :not_nil? do [1, 2, 3] end This is the same as expect true do [].empty? end and expect false do [1, 2, 3].empty? end but provides much clearer failure messages. It also makes the expectation’s intent a lot clearer. § Queries By Proxy There’s also a way to make the expectations of query methods explicit by invoking methods on the result of the block. For example, to check that the even elements of the Array ‹[1, 2, 3]› include ‹1› you could write expect result.to.include? 1 do [1, 2, 3].reject{ |e| e.even? } end You could likewise check that the result doesn’t include 2: expect result.not.to.include? 2 do [1, 2, 3].reject{ |e| e.even? } end This is the same as (and executes a little bit slower than) writing expect false do [1, 2, 3].reject{ |e| e.even? }.include? 2 end but provides much clearer failure messages. Given that these two last examples would fail, you’d get a message saying “[1, 2, 3]#include?(2)” instead of the terser “true≠false”. It also clearly separates the actual expectation from the set-up. The keyword for this kind of expectations is ‹result›. This may be followed by any of the methods • ‹#not› • ‹#to› • ‹#be› • ‹#have› or any other method you will want to call on the result. The methods ‹#to›, ‹#be›, and ‹#have› do nothing except improve readability. The ‹#not› method inverts the expectation. § Literal Literals If you need to literally check against any of the types of objects otherwise treated specially, that is, any instances of • ‹Module› • ‹Range› • ‹Regexp› • ‹Exception› • ‹Symbol›, given that it ends with ‹?› you can do so by wrapping it in ‹literal(…)›: expect literal(:empty?) do :empty? end You almost never need to do this, as, for all but symbols, instances will match accordingly as well. § Expectations on Behavior We expect our objects to be on their best behavior. Lookout allows you to make sure that they are. Reception expectations let us verify that a method is called in the way that we expect it to be: expect mock.to.receive.to_str(without_arguments){ '123' } do |o| o.to_str end Here, ‹#mock› creates a mock object, an object that doesn’t respond to anything unless you tell it to. We tell it to expect to receive a call to ‹#to_str› without arguments and have ‹#to_str› return ‹'123'› when called. The mock object is then passed in to the block so that the expectations placed upon it can be fulfilled. Sometimes we only want to make sure that a method is called in the way that we expect it to be, but we don’t care if any other methods are called on the object. A stub object, created with ‹#stub›, expects any method and returns a stub object that, again, expects any method, and thus fits the bill. expect stub.to.receive.to_str(without_arguments){ '123' } do |o| o.to_str if o.convertable? end You don’t have to use a mock object to verify that a method is called: expect Object.to.receive.name do Object.name end As you have figured out by now, the expected method call is set up by calling ‹#receive› after ‹#to›. ‹#Receive› is followed by a call to the method to expect with any expected arguments. The body of the expected method can be given as the block to the method. Finally, an expected invocation count may follow the method. Let’s look at this formal specification in more detail. The expected method arguments may be given in a variety of ways. Let’s introduce them by giving some examples: expect mock.to.receive.a do |m| m.a end Here, the method ‹#a› must be called with any number of arguments. It may be called any number of times, but it must be called at least once. If a method must receive exactly one argument, you can use ‹Object›, as the same matching rules apply for arguments as they do for state expectations: expect mock.to.receive.a(Object) do |m| m.a 0 end If a method must receive a specific argument, you can use that argument: expect mock.to.receive.a(1..2) do |m| m.a 1 end Again, the same matching rules apply for arguments as they do for state expectations, so the previous example expects a call to ‹#a› with 1, 2, or the Range 1..2 as an argument on ‹m›. If a method must be invoked without any arguments you can use ‹without_arguments›: expect mock.to.receive.a(without_arguments) do |m| m.a end You can of course use both ‹Object› and actual arguments: expect mock.to.receive.a(Object, 2, Object) do |m| m.a nil, 2, '3' end The body of the expected method may be given as the block. Here, calling ‹#a› on ‹m› will give the result ‹1›: expect mock.to.receive.a{ 1 } do |m| raise 'not 1' unless m.a == 1 end If no body has been given, the result will be a stub object. To take a block, grab a block parameter and ‹#call› it: expect mock.to.receive.a{ |&b| b.call(1) } do |m| j = 0 m.a{ |i| j = i } raise 'not 1' unless j == 1 end To simulate an ‹#each›-like method, ‹#call› the block several times. Invocation count expectations can be set if the default expectation of “at least once” isn’t good enough. The following expectations are possible • ‹#at_most_once› • ‹#once› • ‹#at_least_once› • ‹#twice› And, for a given ‹N›, • ‹#at_most(N)› • ‹#exactly(N)› • ‹#at_least(N)› § Utilities: Stubs Method stubs are another useful thing to have in a unit testing framework. Sometimes you need to override a method that does something a test shouldn’t do, like access and alter bank accounts. We can override – stub out – a method by using the ‹#stub› method. Let’s assume that we have an ‹Account› class that has two methods, ‹#slips› and ‹#total›. ‹#Slips› retrieves the bank slips that keep track of your deposits to the ‹Account› from a database. ‹#Total› sums the ‹#slips›. In the following test we want to make sure that ‹#total› does what it should do without accessing the database. We therefore stub out ‹#slips› and make it return something that we can easily control. expect 6 do |m| stub(Class.new{ def slips raise 'database not available' end def total slips.reduce(0){ |m, n| m.to_i + n.to_i } end }.new, :slips => [1, 2, 3]){ |account| account.total } end To make it easy to create objects with a set of stubbed methods there’s also a convenience method: expect 3 do s = stub(:a => 1, :b => 2) s.a + s.b end This short-hand notation can also be used for the expected value: expect stub(:a => 1, :b => 2).to.receive.a do |o| o.a + o.b end and also works for mock objects: expect mock(:a => 2, :b => 2).to.receive.a do |o| o.a + o.b end Blocks are also allowed when defining stub methods: expect 3 do s = stub(:a => proc{ |a, b| a + b }) s.a(1, 2) end If need be, we can stub out a specific method on an object: expect 'def' do stub('abc', :to_str => 'def'){ |a| a.to_str } end The stub is active during the execution of the block. § Overriding Constants Sometimes you need to override the value of a constant during the execution of some code. Use ‹#with_const› to do just that: expect 'hello' do with_const 'A::B::C', 'hello' do A::B::C end end Here, the constant ‹A::B::C› is set to ‹'hello'› during the execution of the block. None of the constants ‹A›, ‹B›, and ‹C› need to exist for this to work. If a constant doesn’t exist it’s created and set to a new, empty, ‹Module›. The value of ‹A::B::C›, if any, is restored after the block returns and any constants that didn’t previously exist are removed. § Overriding Environment Variables Another thing you often need to control in your tests is the value of environment variables. Depending on such global values is, of course, not a good practice, but is often unavoidable when working with external libraries. ‹#With_env› allows you to override the value of environment variables during the execution of a block by giving it a ‹Hash› of key/value pairs where the key is the name of the environment variable and the value is the value that it should have during the execution of that block: expect 'hello' do with_env 'INTRO' => 'hello' do ENV['INTRO'] end end Any overridden values are restored and any keys that weren’t previously a part of the environment are removed when the block returns. § Overriding Globals You may also want to override the value of a global temporarily: expect 'hello' do with_global :$stdout, StringIO.new do print 'hello' $stdout.string end end You thus provide the name of the global and a value that it should take during the execution of a block of code. The block gets passed the overridden value, should you need it: expect true do with_global :$stdout, StringIO.new do |overridden| $stdout != overridden end end § Integration Lookout can be used from Rake¹. Simply install Lookout-Rake²: % gem install lookout-rake and add the following code to your Rakefile require 'lookout-rake-3.0' Lookout::Rake::Tasks::Test.new Make sure to read up on using Lookout-Rake for further benefits and customization. ¹ Read more about Rake at http://rake.rubyforge.org/ ² Get information on Lookout-Rake at http://disu.se/software/lookout-rake/ § API Lookout comes with an API¹ that let’s you create things such as new expected values, difference reports for your types, and so on. ¹ See http://disu.se/software/lookout/api/ § Interface Design The default output of Lookout can Spartanly be described as Spartan. If no errors or failures occur, no output is generated. This is unconventional, as unit testing frameworks tend to dump a lot of information on the user, concerning things such as progress, test count summaries, and flamboyantly colored text telling you that your tests passed. None of this output is needed. Your tests should run fast enough to not require progress reports. The lack of output provides you with the same amount of information as reporting success. Test count summaries are only useful if you’re worried that your tests aren’t being run, but if you worry about that, then providing such output doesn’t really help. Testing your tests requires something beyond reporting some arbitrary count that you would have to verify by hand anyway. When errors or failures do occur, however, the relevant information is output in a format that can easily be parsed by an ‹'errorformat'› for Vim or with {Compilation Mode}¹ for Emacs². Diffs are generated for Strings, Arrays, Hashes, and I/O. ¹ Read up on Compilation mode for Emacs at http://www.emacswiki.org/emacs/CompilationMode ² Visit The GNU Foundation’s Emacs’ software page at http://www.gnu.org/software/emacs/ § External Design Let’s now look at some of the points made in the introduction in greater detail. Lookout only allows you to set one expectation per test. If you’re testing behavior with a reception expectation, then only one method-invocation expectation can be set. If you’re testing state, then only one result can be verified. It may seem like this would cause unnecessary duplication between tests. While this is certainly a possibility, when you actually begin to try to avoid such duplication you find that you often do so by improving your interfaces. This kind of restriction tends to encourage the use of value objects, which are easy to test, and more focused objects, which require simpler tests, as they have less behavior to test, per method. By keeping your interfaces focused you’re also keeping your tests focused. Keeping your tests focused improves, in itself, test isolation, but let’s look at something that hinders it: setup and tear-down methods. Most unit testing frameworks encourage test fragmentation by providing setup and tear-down methods. Setup methods create objects and, perhaps, just their behavior for a set of tests. This means that you have to look in two places to figure out what’s being done in a test. This may work fine for few methods with simple set-ups, but makes things complicated when the number of tests increases and the set-up is complex. Often, each test further adjusts the previously set-up object before performing any verifications, further complicating the process of figuring out what state an object has in a given test. Tear-down methods clean up after tests, perhaps by removing records from a database or deleting files from the file-system. The duplication that setup methods and tear-down methods hope to remove is better avoided by improving your interfaces. This can be done by providing better set-up methods for your objects and using idioms such as {Resource Acquisition Is Initialization}¹ for guaranteed clean-up, test or no test. By not using setup and tear-down methods we keep everything pertinent to a test in the test itself, thus improving test isolation. (You also won’t {slow down your tests}² by keeping unnecessary state.) Most unit test frameworks also allow you to create arbitrary test helper methods. Lookout doesn’t. The same rationale as that that has been crystallized in the preceding paragraphs applies. If you need helpers you’re interface isn’t good enough. It really is as simple as that. To clarify: there’s nothing inherently wrong with test helper methods, but they should be general enough that they reside in their own library. The support for mocks in Lookout is provided through a set of test helper methods that make it easier to create mocks than it would have been without them. Lookout-rack³ is another example of a library providing test helper methods (well, one method, actually) that are very useful in testing web applications that use Rack⁴. A final point at which some unit test frameworks try to fragment tests further is documentation. These frameworks provide ways of describing the whats and hows of what’s being tested, the rationale being that this will provide documentation of both the test and the code being tested. Describing how a stack data structure is meant to work is a common example. A stack is, however, a rather simple data structure, so such a description provides little, if any, additional information that can’t be extracted from the implementation and its tests themselves. The implementation and its tests is, in fact, its own best documentation. Taking the points made in the previous paragraphs into account, we should already have simple, self-describing, interfaces that have easily understood tests associated with them. Rationales for the use of a given data structure or system-design design documentation is better suited in separate documentation focused at describing exactly those issues. ¹ Read the Wikipedia entry for Resource Acquisition Is Initialization at http://en.wikipedia.org/wiki/Resource_Acquisition_Is_Initialization ² Read how 37signals had problems with slow Test::Unit tests at http://37signals.com/svn/posts/2742-the-road-to-faster-tests/ ³ Visit the Lookout-rack home page at http://disu.se/software/lookout-rack/ ⁴ Visit the Rack Rubyforge project page at http://rack.rubyforge.org/ § Internal Design The internal design of Lookout has had a couple of goals. • As few external dependencies as possible • As few internal dependencies as possible • Internal extensibility provides external extensibility • As fast load times as possible • As high a ratio of value objects to mutable objects as possible • Each object must have a simple, obvious name • Use mix-ins, not inheritance for shared behavior • As few responsibilities per object as possible • Optimizing for speed can only be done when you have all the facts § External Dependencies Lookout used to depend on Mocha for mocks and stubs. While benchmarking I noticed that a method in Mocha was taking up more than 300 percent of the runtime. It turned out that Mocha’s method for cleaning up back-traces generated when a mock failed was doing something incredibly stupid: backtrace.reject{ |l| Regexp.new(@lib).match(File.expand_path(l)) } Here ‹@lib› is a ‹String› containing the path to the lib sub-directory in the Mocha installation directory. I reported it, provided a patch five days later, then waited. Nothing happened. {254 days later}¹, according to {Wolfram Alpha}², half of my patch was, apparently – I say “apparently”, as I received no notification – applied. By that time I had replaced the whole mocking-and-stubbing subsystem and dropped the dependency. Many Ruby developers claim that Ruby and its gems are too fast-moving for normal package-managing systems to keep up. This is testament to the fact that this isn’t the case and that the real problem is instead related to sloppy practices. Please note that I don’t want to single out the Mocha library nor its developers. I only want to provide an example where relying on external dependencies can be “considered harmful”. ¹ See the Wolfram Alpha calculation at http://www.wolframalpha.com/input/?i=days+between+march+17%2C+2010+and+november+26%2C+2010 ² Check out the Wolfram Alpha computational knowledge engine at http://www.wolframalpha.com/ § Internal Dependencies Lookout has been designed so as to keep each subsystem independent of any other. The diff subsystem is, for example, completely decoupled from any other part of the system as a whole and could be moved into its own library at a time where that would be of interest to anyone. What’s perhaps more interesting is that the diff subsystem is itself very modular. The data passes through a set of filters that depends on what kind of diff has been requested, each filter yielding modified data as it receives it. If you want to read some rather functional Ruby I can highly recommend looking at the code in the ‹lib/lookout/diff› directory. This lookout on the design of the library also makes it easy to extend Lookout. Lookout-rack was, for example, written in about four hours and about 5 of those 240 minutes were spent on setting up the interface between the two. § Optimizing For Speed The following paragraph is perhaps a bit personal, but might be interesting nonetheless. I’ve always worried about speed. The original Expectations library used ‹extend› a lot to add new behavior to objects. Expectations, for example, used to hold the result of their execution (what we now term “evaluation”) by being extended by a module representing success, failure, or error. For the longest time I used this same method, worrying about the increased performance cost that creating new objects for results would incur. I finally came to a point where I felt that the code was so simple and clean that rewriting this part of the code for a benchmark wouldn’t take more than perhaps ten minutes. Well, ten minutes later I had my results and they confirmed that creating new objects wasn’t harming performance. I was very pleased. § Naming I hate low lines (underscores). I try to avoid them in method names and I always avoid them in file names. Since the current “best practice” in the Ruby community is to put ‹BeginEndStorage› in a file called ‹begin_end_storage.rb›, I only name constants using a single noun. This has had the added benefit that classes seem to have acquired less behavior, as using a single noun doesn’t allow you to tack on additional behavior without questioning if it’s really appropriate to do so, given the rather limited range of interpretation for that noun. It also seems to encourage the creation of value objects, as something named ‹Range› feels a lot more like a value than ‹BeginEndStorage›. (To reach object-oriented-programming Nirvana you must achieve complete value.) § News § 3.0.0 The ‹xml› expectation has been dropped. It wasn’t documented, didn’t suit very many use cases, and can be better implemented by an external library. The ‹arg› argument matcher for mock method arguments has been removed, as it didn’t provide any benefit over using Object. The ‹#yield› and ‹#each› methods on stub and mock methods have been removed. They were slightly weird and their use case can be implemented using block parameters instead. The ‹stub› method inside ‹expect› blocks now stubs out the methods during the execution of a provided block instead of during the execution of the whole except block. When a mock method is called too many times, this is reported immediately, with a full backtrace. This makes it easier to pin down what’s wrong with the code. Query expectations were added. Explicit query expectations were added. Fluent boolean expectations, for example, ‹expect nil.to.be.nil?› have been replaced by query expectations (‹expect :nil? do nil end›) and explicit query expectations (‹expect result.to.be.nil? do nil end›). This was done to discourage creating objects as the expected value and creating objects that change during the course of the test. The ‹literal› expectation was added. Equality (‹#==›) is now checked before “caseity” (‹#===›) for modules, ranges, and regular expressions to match the documentation. § Financing Currently, most of my time is spent at my day job and in my rather busy private life. Please motivate me to spend time on this piece of software by donating some of your money to this project. Yeah, I realize that requesting money to develop software is a bit, well, capitalistic of me. But please realize that I live in a capitalistic society and I need money to have other people give me the things that I need to continue living under the rules of said society. So, if you feel that this piece of software has helped you out enough to warrant a reward, please PayPal a donation to now@disu.se¹. Thanks! Your support won’t go unnoticed! ¹ Send a donation: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=now%40disu%2ese&item_name=Lookout § Reporting Bugs Please report any bugs that you encounter to the {issue tracker}¹. ¹ See https://github.com/now/lookout/issues § Contributors Contributors to the original expectations codebase are mentioned there. We hope no one on that list feels left out of this list. Please {let us know}¹ if you do. • Nikolai Weibull ¹ Add an issue to the Lookout issue tracker at https://github.com/now/lookout/issues § Licensing Lookout is free software: you may redistribute it and/or modify it under the terms of the {GNU Lesser General Public License, version 3}¹ or later², as published by the {Free Software Foundation}³. ¹ See http://disu.se/licenses/lgpl-3.0/ ² See http://gnu.org/licenses/ ³ See http://fsf.org/
A minitest plugin that adds a report of the top tests by number of objects allocated.
Scrapes Cucumber *.feature files to build reports on tag usage and test inventory
RSpec Tracer is a specs dependency analyzer, flaky tests detector, tests accelerator, and coverage reporter tool for RSpec. It maintains a list of files for each test, enabling itself to skip tests in the subsequent runs if none of the dependent files are changed. It uses Ruby's built-in coverage library to keep track of the coverage for each test.
Perfecto Reporting is a multiple execution digital report, that enables quick navigation within your latest build execution. Get visibility of your test execution status and quickly identify potential problems with an aggregated report. Hone-in and quickly explore your test results all within customized views, that include logical steps and synced artifacts. Distinguish between test methods within a long execution. Add personalized logical steps and tags according to your team and organization. For release notes see: https://github.com/PerfectoCode/Samples/blob/master/Reporting/README.md
Library that manages reporting of swift test results to test rail.
A set of tools to support reporting SimpleCov Coverage to CodeClimate with Parallel tests on CircleCI
rcov is a code coverage tool for Ruby. It is commonly used for viewing overall test unit coverage of target code. It features fast execution (20-300 times faster than previous tools), multiple analysis modes, XHTML and several kinds of text reports, easy automation with Rake via a RcovTask, fairly accurate coverage information through code linkage inference using simple heuristics, colorblind-friendliness...
This plugin produces generic test execution reports supported by SonarQube from JUnit test reports generated by fastlane.
Report test results to Gunter.
Generates an XML report that the SonarQube Generic Test Data parser can understand
Continuous integration should really just be a script that captures the output of running your project update & test commands and presents recent results in a static html page. By keeping test reports in json, per-project CI configuration in 3 probably-one-line scripts, things are kept simple, quick, and super extensible. Want to use git, svn, or hg? No problem. Need to fire off results to Campfire? It's built-in. CI depends on cron.
A test-unit runner that reports test result in JUnit XML format.
rutema [http://github.com/damphyr/rutema](http://github.com/damphyr/rutema) rutema is a test execution tool and a framework for organizing and managing test execution across different tools. It enables the combination of different test tools while it takes care of logging, reporting, archiving of results and formalizes execution of automated and manual tests. It's purpose is to make testing in heterogeneous environments easier. ### Why?
Generate tests report output compatible with robottelo py.test output.
# DECC 2050 CALCULATOR TOOL A C version and ruby wrapper for the www.decc.gov.uk 2050 energy and climate change excel calculator Further detail on the project: http://www.decc.gov.uk/2050 Canonical source: http://github.com/decc/decc_2050_model ## DEPENDENCIES 1. ruby 1.9.2 (including development headers) 2. basic c development headers This has ONLY been tested on OSX and on Ubuntu 64 bit EC2 ami. Grateful for reports from other platforms. In the util folder there is an example script that creates a new EC2 EMI, installs all the dependencies and then compiles the gem. It may be useful if you are trying to figure out the complete set of dependencies. ## INSTALLATION Note that this compiles the underlying c code, which might take 10-20 minutes or so gem install decc_2050_model ## UPDATING TO NEWER VERSIONS OF EXCEL MODEL First of all, you need to be working on the github version of the code, not the rubygem: git clone http://github.com/decc/decc_2050_model Then put the new spreadsheet in spreadsheet/model.xlsx Then, from the top directory of the gem: bundle bundle exec rake The next step is to check whether Rakefile, lib/model/_model_result.rb and lib/model/model_structure.rb need to be altered so that they pick up the correct places in the underlying excel. The final stage is to build and install the new gem: gem build model.gemspec gem install decc_2050_model-<version>.gem ... where <version> is the version number of the gem file that was created in the folder. Now follow the instructions in the twenty-fifty server directory in order to ensure that it is using this new version of the gem.
A Cucumber formatter which integrates with Report Portal and supports both the parallel_tests gem and cucumber-messages
Formats RSpec-3 test report in TAP format with a proper nested display of example groups and includes stats for the total number of passed, failed, and pending tests per example group. It supports four different TAP format styles.
Generates coverage report for routes hit by your request/integration/feature tests including capybara ones
A gem that runs jasmine javascript tests with all the goodness of coverage reports.
one9 is a commandline tool to help convert your ruby 1.8.7 code to 1.9.2. It works by spying on your tests and detecting 1.9 changes. Once your test suite finishes, one9 prints a report listing the exact locations of methods that have changed in 1.9. To make the transition even easier, one9 can open this list in an editor. So what's your excuse for not upgrading to 1.9.2? ;)
Value Value is a library for defining immutable value objects in Ruby. A value object is an object whose equality to other objects is determined by its value, not its identity, think dates and amounts of money. A value object should also be immutable, as you don’t want the date “2013-04-22” itself to change but the current date to change from “2013-04-22” to “2013-04-23”. That is, you don’t want entries in a calendar for 2013-04-22 to move to 2013-04-23 simply because the current date changes from 2013-04-22 to 2013-04-23. A value object consists of one or more attributes stored in instance variables. Value sets up an #initialize method for you that let’s you set these attributes, as, value objects being immutable, this’ll be your only chance to do so. Value also adds equality checks ‹#==› and ‹#eql?› (which are themselves equivalent), a ‹#hash› method, a nice ‹#inspect› method, and a protected attribute reader for each attribute. You may of course add any additional methods that your value object will benefit from. That’s basically all there’s too it. Let’s now look at using the Value library. § Usage You create value object class by invoking ‹#Value› inside the class (module) you wish to make into a value object class. Let’s create a class that represent points on a plane: class Point Value :x, :y end A ‹Point› is thus a value object consisting of two sub-values ‹x› and ‹y› (the coordinates). Just from invoking ‹#Value›, a ‹Point› object will have a constructor that takes two arguments to set instance variables ‹@x› and ‹@y›, equality checks ‹#==› and ‹#eql?› (which are the same), a ‹#hash› method, a nice ‹#inspect› method, and two protected attribute readers ‹#x› and ‹#y›. We can thus already creat ‹Point›s: origo = Point.new(0, 0) The default of making the attribute readers protected is often good practice, but for a ‹Point› it probably makes sense to be able to access its coordinates: class Point public(*attributes) end This’ll make all attributes of ‹Point› public. You can of course choose to only make certain attributes public: class Point public :x end Note that this public is standard Ruby functionality. Adding a method to ‹Point› is of course also possible and very much Rubyish: class Point def distance(other) Math.sqrt((other.x - x)**2 + (other.y - y)**2) end end For some value object classes you might want to support optional attributes. This is done by providing a default value for the attribute, like so: class Money Value :amount, [:currency, :USD] end Here, the ‹currency› attribute will default to ‹:USD›. You can create ‹Money› via dollars = Money.new(2) but also kronor = Money.new(2, :SEK) All required attributes must come before any optional attributes. Splat attributes are also supported: class List Value :'*elements' end empty = List.new suits = List.new(:spades, :hearts, :diamonds, :clubs) Splat attributes are optional. Finally, block attributes are also available: class Block Value :'&block' end block = Block.new{ |e| e * 2 } Block attributes are optional. Comparison beyond ‹#==› is possible by specifingy the ‹:comparable› option to ‹#Value›, listing one or more attributes that should be included in the comparison: class Vector Value :a, :b, :comparable => :a end Note that equality (‹#==› and ‹#eql?›) is always defined based on all attributes, regardless of arguments to ‹:comparable›. Here we say that comparisons between ‹Vector›s should be made between the values of the ‹a› attribute only. We can also make comparisons between all attributes of a value object: class Vector Value :a, :b, :comparable => true end To sum things up, let’s use all possible arguments to ‹#Value› at once: class Method Value :file, :line, [:name, 'unnamed'], :'*args', :'&block', :comparable => [:file, :line] end A ‹Method› consists of file and line information, a possible name, some arguments, possibly a block, and is comparable on the file and line on which they appear. Check out the {full API documentation}¹ for a more explicit description, should you need it or should you want to extend it. ¹ See http://disu.se/software/value/api/ § Financing Currently, most of my time is spent at my day job and in my rather busy private life. Please motivate me to spend time on this piece of software by donating some of your money to this project. Yeah, I realize that requesting money to develop software is a bit, well, capitalistic of me. But please realize that I live in a capitalistic society and I need money to have other people give me the things that I need to continue living under the rules of said society. So, if you feel that this piece of software has helped you out enough to warrant a reward, please PayPal a donation to now@disu.se¹. Thanks! Your support won’t go unnoticed! ¹ Send a donation: https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=now%40disu%2ese&item_name=Value § Reporting Bugs Please report any bugs that you encounter to the {issue tracker}¹. ¹ See https://github.com/now/value/issues § Authors Nikolai Weibull wrote the code, the tests, the manual pages, and this README. § Licensing Value is free software: you may redistribute it and/or modify it under the terms of the {GNU Lesser General Public License, version 3}¹ or later², as published by the {Free Software Foundation}³. ¹ See http://disu.se/licenses/lgpl-3.0/ ² See http://gnu.org/licenses/ ³ See http://fsf.org/
Watch and Notify your not tested routes of a RoR Application, it also has a simple report about Routes defines, used and tested
Crawls a static site mirror testing all links. Reports links which don't return 200 or redirect to a 200.
== DESCRIPTION: Charlie is a library for genetic algorithms (GA) and genetic programming (GP). == FEATURES: - Quickly develop GAs by combining several parts (genotype, selection, crossover, mutation) provided by the library. - Sensible defaults are provided with any genotype, so often you only need to define a fitness function. - Easily replace any of the parts by your own code. - Test different strategies in GA, and generate reports comparing them. Example report: http://charlie.rubyforge.org/example_report.html == INSTALL: * sudo gem install charlie == EXAMPLES: This example solves a TSP problem (also quiz #142): N=5 CITIES = (0...N).map{|i| (0...N).map{|j| [i,j] } }.inject{|a,b|a+b} class TSP < PermutationGenotype(CITIES.size) def fitness d=0 (genes + [genes[0]]).each_cons(2){|a,b| a,b=CITIES[a],CITIES[b] d += Math.sqrt( (a[0]-b[0])**2 + (a[1]-b[1])**2 ) } -d # lower distance -> higher fitness. end use EdgeRecombinationCrossover, InversionMutator end Population.new(TSP,20).evolve_on_console(50) This example finds a polynomial which approximates cos(x) class Cos < TreeGenotype([proc{3*rand-1.5},:x], [:-@], [:+,:*,:-]) def fitness -[0,0.33,0.66,1].map{|x| (eval_genes(:x=>x) - Math.cos(x)).abs }.max end use TournamentSelection(4) end Population.new(Cos).evolve_on_console(500)
== DESCRIPTION: rutemaweb is the web frontend for rutema. It can be used as a viewer for database files created with the rutema ActiveRecord reporter. It also provides you with some basic statistics about the tests in your database in the form of diagrams of debatable aesthetics but undoubtable value! == FEATURES/PROBLEMS: == SYNOPSIS: rutemaweb [results.db] and browse to http://localhost:7000 for the glorious view == REQUIREMENTS: * patir (http://patir.rubyforge.org) * activerecord (http://ar.rubyonrails.com/) * sqlite3 (http://rubyforge.org/projects/sqlite-ruby/) * ramaze (http://www.ramaze.net/) * ruport (http://rubyreports.org/) * acts_as_reportable * erubis * gruff/RMagick (optional, but needed if you want to see the statistics graphs)
SPlat is an integration platform to make use of SMS integration really easy. Using this platform has the following advantages: * Single point of integration * Change vendors without changing code. * Send and receive SMS. * Generic Exception Handling. * Standardized reports. * SMS tagged user groups. * SMS bogus gateway for testing. * Scheduling SMS for delivery.
QAT is a Cucumber-based toolkit for automating tests, including a list fo modules for: - Time manipulation - Test reporting - Configuration management - Jenkins Integration
CI::Reporter is an add-on to Test::Unit, RSpec and Cucumber that allows you to generate XML reports of your test, spec and/or feature runs. The resulting files can be read by a continuous integration system that understands Ant's JUnit report XML format, thus allowing your CI system to track test/spec successes and failures.
== DESCRIPTION: rutema_web is the web frontend for rutema. It can be used as a viewer for database files created with the rutema ActiveRecord reporter. It also provides you with some basic statistics about the tests in your database in the form of diagrams of debatable aesthetics but undoubtable value! == SYNOPSIS: rutema_web config.yaml and browse to http://localhost:7000 for the glorious view Here is a sample of the configuration YAML: --- :db: :adapter: sqlite3 :database: rutema_test.db :settings: :page_size: 10 :last_n_runs: 20 :port: 7000 :show_setup_teardown: true The :db: section should be the activerecord adapter configuration. The :settings: section controls the behaviour of the web app.