We demystified the automation puzzle. Relentless validation tamed!

June 28th, 2010

A large global provider of BI solutions has a product suite that runs on five platforms supporting thirteen languages with each platform suite requiring multiple machines to deliver the BI solution. The entire multi-platform suite is released on single CD multiple times a year.

The problem that stumped them was “how to automate the final-install validation of multi-platform distributed product”. They had automated the testing of the individual components using SilkTest, but they were challenged with “how to unify this and run off a central console on various platforms at the same time”.

Considering each platform-combination took about a day, this required approximate two months of final installation build validation, and by the time they were done with this release, the next release was waiting! This was a relentless exercise, consuming significant QA bandwidth and time, and did not allow the team to do things more interesting or important.

The senior Management wanted single-push-button automation -identify what platform combination to schedule next, allocate machine automatically from the server farm, install and configure automatically, fire the appropriate Silk scripts and monitor progress to significantly reduce time and cost by lowering QA bandwidth involved in this effort. After deep analysis, in-house QA team decided this was a fairly complex automation puzzle and required a specialist! This is when where we were brought in.

After an intense deep-dive lasting about four weeks, we came up with a custom master-slave based test infrastructure architecture that allowed a central console to schedule various jobs onto the slaves, utilizing a custom developed control & monitoring protocol.  The solution was built using Java-Swing, Perl, Expect and adapters to handle Silk scripts. Some parts of the solution where on Windows platform while some on UNIX.  This custom infrastructure allowed for scheduling parallel test runs, automatic allocation of machines from a server farm, installing appropriate components on appropriate machines, configuring them and finally monitoring the progress of validation through a web console.

This test infrastructure enabled a significant reduction of the multi-platform configuration validation. The effort reduced from eight weeks to three weeks. We enjoyed this work simply because it was indeed a boutique work fraught with quite a few challenges. We believe that this was possible because we analyzed the challenging problem from wearing a development hat and not the functional test automation hat.

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Delivering peace of mind- Assessing release worthiness

June 28th, 2010

The product helps to detect different types of telecom fraud, be it in wireless or wire line networks. It also helps to detect fraud in roaming, pre-paid and post-paid environments and tailor-made for GSM/CDMA/Fixed/GPRS network. The product team comprised of strong development team ably supported by an in-house QA team. The product was developed using J2EE technologies and had undergone multiple versions of build – currently in version 6.0 – with wide installation base in Asian/US market. The company had an ambitious plan to expand the product reach and move into a new market – European market. The product went through multiple feature upgrade/modifications to meet the needs of the new market. Though the product was tested diligently by the in-house QA team, the management was skeptical about the release worthiness of the product. They preferred to have an independent third party product assessment to enhance their delivery confidence before the formal product launch.

STAG singularly focused to ensure the defect escapes are minimized. Hence a three-pronged approach was adopted to determine the breadth and depth of testing required -

  • Identify what poses high business risks? What has been de-risked already? What remains as risk that is to be assessed?
  • How well has the “net” been cast to uncover defects in the lifecycle? Are the methods to uncover defects expansive/complete?
  • Are the test cases (i.e. those inputs that have the ‘power’ to detect anomalies) good?  Do the already existing test cases and therefore the tests conducted have the power to uncover high-risk business issues?

Fixing the high impact defects improved the stability of the product– which otherwise could have led to USD 250K support cost in the initial months. The release worthiness certificate lowered the business risk for the customer and newly gained delivery confidence by the customer management powered their successful product launch and on time to market.

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Validation Suite – An innovative way to leveraging test assets & reducing cost of validation

June 28th, 2010

The test lifecycle produces rich set of assets-strategy, test scenarios/cases, defects, scripts, test data. Other than using these to validate the current release of product, how are these significantly leveraged in the future? How do these assets enable faster ramp-up, de-skilling, optimize testing? Patterns have been used as a method to extract experience and enable a normal person to behave like an experienced person. Sadly, patterns are not commonplace in test engineering.

Validation Suite is a product from STAG that is similar to patterns. Based on HBT (Hypothesis Based Testing) methodology, it enables identifying potential defect types for common features/construction-components along with a common validation strategy consisting of Quality Levels, Test Types and finally a list of common test scenarios/cases/data. The intent is to ensure that we do not start all over again, and leverage the experience typically encoded as tacit knowledge in the individuals.

STAG has applied this to create specific validation suites in the areas of eLearning, ERP, Bluetooth and Mobile applications. These can reduce the cost of validation by 30% and reduce ramp-up time significantly. The key business benefits are (1) Fast ramp-up (2) Readymade test strategy (3) Higher product quality (4) Faster time-to-market and (5) Lower validation cost.

Validation suite for your product can be created by mining your test assets by applying the HBT methodology to create a structured and rich asset base that provides significant leverage subsequently.

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How many “negative test cases” should there be?

April 29th, 2010

Before we answer the question let us ensure that we have common understanding of what is positive or negative test cases. In HBT, positive test cases are those whose input values are valid, while a negative test case is one with at least one of the test inputs (i.e. Test data) being incorrect (i.e. out of specification).

The objective of positive test cases is “conformance” while the objective of negative test cases is “robustness”. If a majority of test case are positive, then it implies that we are primarily interested in conformance i.e. ensuring the system handles correct inputs well. This we know is not sufficient, as accidental incorrect inputs should not result in unexpected possibly risky/dangerous behaviour. Hence we need test cases that are indeed “negative”.

So, coming back to the question, what is a good enough distribution of positive and negative test cases? Any quick answer like 75% should not be trusted as they have no basis. So, how do we answer this question? Step back now and look at the number of inputs for a given test case, the clue is there. For example at a lower level of testing, where say we are validating a screen, the number of inputs may be many as the screen may be populated. As we go up the testing level, e.g. Testing a feature that uses a few screens, the test data is not the various individual inputs on the screen, but aggregate data (think like a record) and these may be fewer in number compared to the earlier levels.

Having understood that the number of test data (or inputs) at lower levels is far higher than those at the higher levels, it is only logical to conclude that the number of negative test cases at lower levels. Now how much should that be?  To answer his finally without resorting to magic (!), let us illustrate with simple example. If there are 5 inputs and each input has six possible values (3 positive i.e. valid and 3 negative i.e. invalid) then using simple combinatorial math, we can see that there be (minimally) 3*5=15 negative test cases and (minimally) 5 positive test cases. In this case the 15/(15+5)= (75%) of test cases are negative.

In closing, understanding the number of inputs and clear understanding of what an input at a testing level is (The STEM Core concept “Input granularity principle” of HBT methodology helps in understanding as what an input at a level is) it is possible to quickly estimate the minimal number of negative test cases. This is very useful in quickly ascertaining whether the test cases are conformance and robustness oriented.

This is covered in “HBT.10: Effective review of test cases”, a title in our HBT Series of workshops

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Requirements traceability is “Necessary but not sufficient”

April 29th, 2010

When asked about “how do you know that your test cases are adequate?”, the typical answer is Requirement Traceability Matrix(RTM) has been generated and that each requirement does indeed have test cases.

Is this logic strong enough? Unfortunately NO! Why? Assume that each requirement had just one test case. This implies that we have good RTM i.e. each requirement has been covered. What we do know is that could there additional test cases for some of the requirements? So RTM is a necessary condition but NOT a sufficient condition.

So, what does it take to be sufficient? If we had a clear notion of types of defects that could affect the customer experience and then mapped these to test cases, we have Fault Traceability Matrix (FTM as proposed by HBT). This allows us to be sure that our test cases can indeed detect those defects that will impact customer experience.

Note that in HBT potential defects types are mapped to the Cleanliness Criteria derived earlier. Cleanliness criteria are those that have to be met to ensure that customer has a good experience with the system.

This is covered in “HBT.10 : Effective review of test cases”, a title in our HBT Series of workshops.

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Effectiveness and Efficiency of test cases

April 29th, 2010

Given that we have set of test cases, we would like then them to be effective. What does “effective” mean? Effectiveness of test cases is the ability of the test cases to be able to detect (or uncover) the defects that can affect the customer experience.  So a clear understanding of what *types of defects* are we looking for and a mapping of the test cases to these test cases would enable a scientific way of assessing effectiveness.

What is efficiency? It is ensuring that we execute the test cases in as short a time as possible with optimal effort and no more.  Understanding (1) the priority or business importance of test cases, (2) knowing what test cases to execute in what part of the lifecycle (3) clear segregation of test cases by various types of tests and levels enables to optimize testing and become efficient.

This is covered in our HBT Series of workshop “HBT.10 : Effective review of test cases”.

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Ensuring testable non-functional requirements

April 29th, 2010

Non-functional requirements are notoriously non-testable! By this, we mean it is more typical that non-functional requirements are fuzzy/less-clear. In a simplistic form “The system should be robust” is non-testable i.e. It is definitely not clear as how to validate this!

Rather than identifying non-functional requirements and describing them, it is suggested that we look at each requirement and partition these into functional and non-functional aspects and probe into the key attributes to be satisfied for the requirement. For attribute, GQM (Goal-Question-Metric) of core concept of STEM enables deriving metric(s) to ensure that each attribute is indeed testable.  Later the various similar attributes across all the requirements can be aggregated to create the system-wide non-functional requirement.

In this manner non-functional requirements are clearer and testable.

This is covered in “HBT.2: Rapid Understanding of customer expectations”, a title in our HBT Series of workshops.

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Rapidly understanding the usage profile

April 29th, 2010

Understanding the rate and number of transactions probably on a real system is critical to ensure that the system is designed well and later sized and deployed well. Good understanding of the business domain is seen as a key enabler to arrive at the usage profile.

Operational profiling (A STEM core concept) is a scientific way to quickly arrive at a real life profile of usage. Good understanding of this concept alleviates the problem of lack of deep domain knowledge to understand the usage profile. This core concept consists of these key aspects:

  1. Mode – Represents a time period of usage e.g. End of month, where the usage patterns are distinctive and different.
  2. Key operations (features/requirements) used
  3. Types of end users associated with the key features/requirements
  4. Number of end users for each type of users
  5. Rate of arrival of transactions

In short, for a given mode, identify the end users types and their key operations and then identify the number of users for each type of user and then identify the rate of arrival of transaction. Employing this core concept allows us to think better and ask specific questions to understand the marketplace and the usage profile in a typical and worst-case scenario.

This allows us to get a better understanding of the usage and helps in identifying business risks and derive an effective strategy.

This is covered in “HBT.2 : Rapid Understanding of customer expectations”, a title in our HBT Series of workshops.

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Landscaping – A STEM Core concept to understanding system & expectations

April 29th, 2010

Understanding a system is non-linear process i.e. we have derive a lot of questions that are interconnected and then seek answers individually and then connect the various answers.

Landscaping is a core concept in STEM (STAG Test Engineering Method) that powers HBT (Hypothesis based testing) that lists the various aspects related to the system, customer, marketplace, technology and forces one to connect these concepts. What emanates is like an interesting web of information (aka Mindmap) that enables you to come up with intelligent questions and there enable rapid understanding.

For example, connecting marketplace, with requirements and end-users, one can arrive at the question: “What are the various markets that we are planning to deploy our system and in these markets, who are the various kinds of end user types and what does each one from the system?

To quote a specific instance, a two-liner requirement spawned 40+ questions rapidly, that when clarified allowed us to understand the requirement in about an hour. In fact, this uncovered issues in the product being built, as certain aspects of the requirements were completely missed by the developers in their implementation. It is to be noted that our ability to identify questions and therefore understand were not due our domain skills, it was purely due to the application of HBT methodology powered by the defect detection technology(STEM) to the problem at hand.

This is covered in “HBT.2: Rapid Understanding of customer expectations”, a title in our HBT Series of workshops.

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Launching two new HBT series of workshops in MAY 2010

April 21st, 2010

STAG is launching two new workshops in the “HBT Series” in May 2010. We thank our participants of Robust Test Design workshop conducted in Chennai, for suggesting that we come with a new workshop for “How to understand customer expectations rapidly” . Thank you!

The workshops are:

  1. Rapid understanding of customer expectations  on May 27, 2010 at Bangalore and on June 7 at Chennai.
  2. Effective review of test cases  on May 28, 2010 at Bangalore and June 8, 2010 at Chennai.

Workshop details:

Rapid understanding of customer expectations (1-day workshop)

Objective: How to rapidly understand expectations/requirements of the software to be validated in a scientific manner.

Target audience: Test manager, Project manager, Test lead, Test Engineers

To test effectively, estimate correctly, a good understanding of the software/application is very important. The act of understanding is a high maturity skill requiring multiple skills. Domain knowledge is seen as a critical enabler to good understanding. Good documentation of the requirements is also a key ingredient. In real life however, the available documentation of requirements/specifications always lacks the details required for effective testing, and is typically not in sync with the software/system being built. Therefore the test staff with their domain knowledge is expected to come up with good questions and clarify the missing elements and understand the intended behaviors. This is easier said that done, as deep domain knowledge is typically a scarce commodity.

This workshop takes a scientific approach to “act of understanding the intentions or expectations” by identifying key elements required of any requirement/specification and identifying a personal process powered by scientific concepts to ensure that we rapidly understand the intentions and identify the missing elements.

The first two stages of Hypothesis-based testing(HBT) methodology focuses on “Understanding expectations” and “Understand context”, this is powered by the “Business Value Understanding” discipline of STEM, the underlying defect detection technology that powers HBT. This discipline employs seven scientific concepts to enable that the various aspects to understand the expectations can indeed be done in a scientific manner.

This has been successfully used by STAG in its engagements to rapidly identify questions to understand expectations. To quote a specific instance, a two-liner requirement spawned 40+ questions rapidly, that when clarified allowed us to understand the requirement in about hour. In fact, this uncovered issues in the product being built,  as certain aspects of the requirements were completely missed by the developers in their implementation. It is to be noted that our ability to identify questions and therefore understand were not due our domain skills, it was purely due to the application of HBT methodology powered by the defect detection technology(STEM) to the problem at hand.

The topics covered in this workshop are:

  • How to create the big picture and get a good overall view (Landscaping)
  • Identifying end users and their needs
  • Identifying business requirements and  corresponding technical requirements
  • Identifying critical attributes and ensuring that they are testable
  • Understanding the usage patterns/operational profile
  • Identifying business risks and prioritization
  • Understanding intended behaviors for designing test scenarios/cases
  • Formulating cleanliness criteria

The participants will be able to create a User type list, Requirement list, Operational profile, Interaction matrix, Cleanliness criteria  and key questions to understanding expectations at the end of this workshop.

The delivery style will be application oriented, an application will be used to illustrate the concepts and the process of doing.

Each participant will be given a HBT cookbook (NEW!) in addition to the workshop slide set and application case study.

Effective review of test cases (1-day workshop)

Objective: How to assess effectiveness, completeness, consistency and future automation-ability of test cases.

Target audience: Test leads and Test engineers

Test effectiveness is a function of the quantity and quality of test scenarios/cases. The difficult  aspect is assessing if the designed scenarios/cases are indeed adequate. As always, a deep domain and technical knowledge is seen as a critical aspect to effectively review the test scenarios/cases. The challenging part is that deep domain/technical skills is always in short supply.

This workshop teaches a scientific approach to assess the quality of test scenarios/cases by applying a goal centered to testing – “What types of defects should I detect”?. Commencing with identification of potential defect types that will impact the customer experience, the designed scenarios/cases are analyzed for fault coverage in addition to requirements coverage. HBT powered by STEM has a clear structure for effective test scenarios/cases (TS/TC) and this is the basis for assessment of the scenarios/cases. The STEM Test Case Architecture (STEM-TCA) architecture slices the scenarios/cases is multiple ways and allows one to see the gaps in the designed scenarios/cases. For example STEM-TCA requires TS/TC to be segregated by potential defect types and then by quality levels and then by test types, by conformance vs robustness, by importance and other attributes. This approach enables a scientific enquiry process and allows one to assess rapidly and effectively without totally relying on the domain knowledge.

STAG has used this successfully in its boutique service offering of “Test case re-engineering” in its engagements to increase coverage(i.e. defect finding ability)  significantly with its customers. One such interesting work is listed in our blog “Re-architecting  test assets increases test coverage by 250%.” In addition, STAG  has used these concepts to assess completeness of TS/TC for its Japanese customers in their “Diagnostics &  control” solution offering.

At the end of workshop you will able to review the designed scenarios/cases rapidly & effectively enabling you to “produce better bait” to catch the fish! I.e defect defects. The information content of test scenarios/cases plays a vital part of in embarking on successful automation to improve efficiencies. Moving from effectiveness, the workshop will be also enable assessing the efficiency aspect of the testing I.e how can I order and deliver design  assets that will enable faster testing. This is addressed in the assessment of TS/TC on the  automation-fitness aspect.

The topics covered in this workshop are:

  • Understanding the goal of TS/TC i.e. what types of defects should we detect?
  • Assessing basic completeness using RTM(Requirement traceability matrix)
  • Understanding the caveat of RTM i.e. it is necessary but sufficient enough
  • Creating fault traceability matrix
  • Understanding the STEM-TCA
  • Identifying information needed for assessment
  • The personal assessment process for effectiveness and efficiency of TS/TC
  • Understanding the distribution of conformation-oriented(positive) vs robustness (negative)oriented over the various levels of test
  • Limitations of black box techniques
  • What information related to internal aspects of the software do I need to know i.e. how to use white box techniques effectively
  • Metrics that are useful to substantiate the assessment like Test breadth, Test depth and Test granularity

The participants will be able to a create clear assessment report with appropriate metrics   to judge the efficacy and efficiency aspects  at the end of this  workshop.

The delivery style will be application oriented implying test scenarios/case of an real-life application will be used to illustrate the concepts and the process of doing.

Each participant will be given a HBT cookbook (NEW!) in addition to the workshop slide set and application case study.

Both these workshops are limited to a maximum of 25 participants on first-come basis. Email learning at stagsoftware dot com for registration or for more information. We are excited about launching these two unique workshops and look forward to interacting with you.

Click here to download the HBT Series of Workshops brochure.

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