SOAPSonar – Testing SOAP, REST or JSON Services

” What is the difference Testing a SOAP Services vs. JSON/REST or other service using SOAPSonar” After trying to answer this question verbally 3 times in the last week, I thought it a good idea to show it in a post.

  • SOAP – “Simple Object Access Protocol” usually uses XML, and has WSDL. It also has an explicit error format or SOAP Fault messages. It tends to be heavier weight and services are often far larger.
  • REST – Representational state transfer is a software architectural style consisting of a coordinated set of architectural constraints applied to components, connectors, and data elements, within a distributed hypermedia system of which JSON is one language.
  • JSON – JavaScript Object Notation, uses readable text (not tue XML)to transmit data objects, consisting of attribute–value pairs. JSON does not use WSDL (Similar WADL is unpopular, in draft and seldom used), but usually uses a service description document. JSON Schema is also seldom currently used. JSON has no explicit error format. This makes JSON light weight and ideal for mobile applications.

So what does that really mean for someone using SOAPSonar?

The Difference

With a SOAP Service

You can use the capture WSDL bar and enter the URI, with ?wsdl afterwards and discover all the available services. Try it now with

http://www.w3schools.com/webservices/tempconvert.asmx?wsdl.

Notice the TempConvert and two services are automatically populated. When you select FahrenheitToCelsius_1, notice the Body is populated with field in SOAPSonar. If you enter a value, commit and send, you get your XML response.

1. WSDL
SOAPSonar offers a way to view the XML request, using the tab labelled XML and request headers. The same is possible in JSON, also headers tend to be lighter weight

2. XML

You can Also go to Documents and View Schema, which most likey does not exist in JSON

3. View Schema

With A JSON Service

There is no WSDL that can be captured and the chances are there is no schema. This means it is not possible for a Tester to automatically discover services in the same way. In SOAPSonar, we start by selecting File, New Test Group and then we have to name the test group. We can then Add a new test, by right-click, New JSON Test or more generic New REST Test and then naming each one.

5 New JSON

We then need a URI, the query parameters and the Method. Lets use

http://webservices.daehosting.com/services/TemperatureConversions.wso/FahrenheitToCelcius/JSON

as the URI and ?nFahrenheit=decimal as parameter to send and GET as the method. Then for 80 as the value, we replace Decimal with 80. How do I know this?, I read the document definition and example. The REST view in SOAPSonar would be as below. Notice the body of the request is frequently empty

6 REST View

The JSON view, is a single query line in the URI, and the Method. There is no WSDL to View and although incorrect queries will error, the description is limited.

7 JSON

So how then do Testers know what to Test? Its usually one of 4 ways
  1. The tester reviews the JSON code and looks for all URI, Methods and attribute–value pairs and reverse engineers tests cases. This takes significant JSON knowledge
  2. The Tester relies on the service description document, which should define all attribute–value pairs, Methods, URI’s and Query Strings. This requires good documentation.
  3. The developer and / or tester (Agile facilitates this) create and define the unit tests together. This unit test is then used to validate the basic functionality of the each function by both developer and tester. The tester, then adds ADS, chains functions, tests negative scenarios, load, and all additional aspects of the function to get the desired coverage
  4. You embrace yet to be standards of JSON Schema (tough given its level of maturity)

With JSON services, defining success criteria is also extremely valuable, due to the lack explicit error format. Its also far easier far developer to make minor changes to code, as they dont need to update schema, making regression testing important.

The Same

So now that we covered the differences, the rest is much of the same. Lighter weight JSON services tend to be much smaller and services and the very easy structure to understand. Be it SOAP or REST, SOAPSonar (and CloudPort) will identify all the variables and display them in the same manner.

Here is what that SOAP service looks like in graphical view for both request and response in the Runtime Variables tab. Any of these variables can now be used for chaining, automation data sources, success criteria, regression and a variety of testing options, using the right-click option.

4 Variable reference

Here is what the JSON service looks like for the graphical view for both request and response in the Runtime Variables tab. Any of these variables can also be used in the same way as SOAP, for chaining, automation data sources, success criteria, regression and a variety of testing options, using the right-click option.

8. JSON Vairables

If you wish to use a variable with SOAP, you right-click and add it in the field.

9 Query

If you wish to use a variable with JSON, you right-click and add it in the URI (or body occasionally) in the same way.

10 JSON Query

Conclusion

Yes there are differences testing SOAP vs. REST when using SOAPSonar. The lightweight nature of JSON, that makes it attractive, requires closer ties to development and more rigorous documentation in order to ensure that the service is being “discovered” and tested. This means Testing and Development need a clearly defined process, de-mark, deliverables and co-operation between developers and testers.

I hope this helps those QA professionals as that are now testing JSON vs SOAP services to adapt to the changes quicker. Questions, Comments?

Reducing Scope – the Amount of Software Testing

Our example used at TASSQ and in our a More Detailed look at Service Plan Costing we used a fix number of test cases (50,000). At the TASSQ event, many immediately wanted to discuss ways to reduce the number of test cases. This is just as important an aspect as streamlining the test process once this is done. Due to time constraints, I decided to leave it till now. But, what kind of things can be done to reduce the sheer scope of testing needed?

This is too long for a single post, but over the next few weeks, I will build it out each area. Looking at high level areas to focus at though, we have 4 key areas to focus on

  1. SDLC Strategies
  2. Test Iteration Strategies
  3. Test Cycle Strategies
  4. Maintenance Strategies

1. SDLC Strategies

What is your corporate mandate? Is these a free internet service, that is best effort, or do errors have potentially huge financial risks? How long is this software expected to be in use (next release), and how mission critical is it to your business? The way we approach testing should reflect our business needs.

The second aspect is more architectural. I have already posted one post on API Versioning Strategies. How the service and the client are designed and managed in the SDLC, can greatly impact the amount of testing needed.

2. Test Iteration Strategies

This looks at way to reduce the number or effort required in each test Iteration. Can you share the same test case for Functional and Performance Testing? How can you ensure that development did fix the issues in the last release? Do you really need to retest code that was not changed?

Strategies here vary a great deal depending on if you using AGILE or Waterfall or some other Development methodology.

3. Test Cycle Strategies

This area looks at way to reduce the number and the complexity of doing individual test. A lot of this has to do with desired percentage coverage, but automation, data sources and regression are all aspects.

4. Maintenance Strategies

Far to often we focus on getting the software into production, yet its generally accepted that testing during the maintenance cycle can be well over half the testing costs. This is about, automation,  regression and continual testing strategies that can reduce the maintenance testing costs or coverage.

I cant poll the audience here, but as usual, we share and learn. So please if you have thoughts or suggestions on the subject of reducing the amount of testing required, please let me know.

 


 

Continuous Testing in Agile

Along with performance testing, there were 2 other themes that continually came up in conversations during STAR Canada.

  1. How should QA integrate in a Agile environment
  2. The need for “Continuous Testing”.

While there are thousands of articles about Continuous Testing, and hundreds of thousands on Agile, there seems little on both. Perhaps due to some apparent conflicts.

Lets look at a theoretical QA in an agile environment. Say your organization Sprints are 2 weeks in length, each scrum having 8-10 members for manageability. Due to project time constraints,  there are 5 scrums working concurrently, each focussed on a different component of development of your application. What test cycles are done as part of the sprint and what cycles are done outside or as cross functional teams?

Agile Testing Levels

It was pointed out that although common, doing only unit tests and integration testing on your Sprints code, then jumping to acceptance testing of that sprint, is not Agile. Agile should in fact have all test stages built into the Sprint. Many companies ignore various test cycles like load, integration and security testing of the end to end system as there simply is not time in each Sprint.

An alternate approach is to created independent teams outside of the Agile development. Their role is to test integration, load, security and systems in integrated environments. Defects identified are then fed back into the scrum meetings and allocated to particular Sprint. This also is not really Agile, falling into some kind of hybrid. The challenge here is that issues are often identified after sprints are finished and so not really continuous testing either.

A second approach, was to create cross functional roles were the scrum masters and one or more members of each sprint were allocated to doing systems level testing and possibly fixes. These cross functional teams, would near the end of each sprint, break out of their old scrum into the new role. The challenge with this approach is that on shorter sprints, and large systems, they can land up spending more time in the cross functional role than in their own scrum.

Continuous Testing

Continuous Testing is somewhat the same as Baseline and Regression Testing, but need not only testing against a Baseline. Its about continually testing while developing through the entire SDLC. The benefit that issues can be identified far earlier (Shift Left approach) resulting in lower costs to address. Agile environments at first glance, seem to favour continuous testing, but does that include, regression, integration and systems testing across Sprints? If each test case takes 9 minutes to complete, 1 tester can only run 53 test cases in a day or 533 tests in a Sprint. This is simply not enough coverage to test all systems and other tests continuously. The result, is partial or low test coverage.

Enter Automation

If as part of each Sprint, a fully developed set of test cases are developed by each Sprint in the same application (eg SOAPSonar) covering their development efforts. The incremental work to role these up into test cases for integration, load etc would be minimal. Each sprint then shares a set of Integration, performance, load and regression etc tests that they simply run as part of their sprint. Being automated, these can even run after hours. The result is continuous testing of both at the Systems level and the Sprint level, without the heavy resource requirements of manual testing. issues be the system wide, or sprint level can then be addressed in Sprint.

Conclusion

The concern with this is the same as with any automation project, “Will The Development of the Automation Scripts Not Take More Time than the Resulting Benefit.” This is a tool selection question. Finding the right tool for your team to use to minimize the time taken developing and maintaining various test cases from function through load and regression, to acceptance testing.

Would you like to weigh in with your thoughts or comments on the subject?