Trending October 2023 # Bug/Defect Triage In Software Testing # Suggested November 2023 # Top 10 Popular

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What is ‘Defect Triage’?

Defect triage is a process where each bug is prioritized based on its severity, frequency, risk, etc. Triage term is used in the Software testing / QA to define the severity and priority of new defects.

Why do we need to have ‘Defect Triage’?

The goal of Bug Triage is to evaluate, prioritize and assign the resolution of defects. The team needs to validate severities of the defect, make changes as per need, finalize resolution of the defects, and assign resources. Mainly used in agile project management.

How often ‘Defect Triage’ needs to be conducted in a release?

The frequency of Defect triage meeting is not fixed. It depends on project situation.

Here, are some important factors that decide the frequency of Defect Triage Meetings:

These Important factors are:

As per the project schedule

Number of defects in the system

Impact on schedules of team members’ availability

Overall project health

Usually, Defect Triage Meetings are held two or three times in a week.

Who are the mandatory and other participants of ‘Defect Triage’?

Mandatory Participants

Below project members always take part in Defect Triage Meetings.

Project Manager

Test Team Leader

Technical Lead

Development Team Leader

Optional Participants

Developers

Testers

Business Analyst

Roles and Responsibilities of participants during ‘Defect Triage.’ Test Team Leader

Scheduled bug triage meeting and send meeting notification for attendees.

Create a defect report and send it to all attendees before the meeting.

Assign priority and severity of the defects.

Give a presentation so that other members understand Root Cause of defect.

Every meeting note is captured and sent to meeting attendees.

Development Lead

Helps in the prioritization of the defects.

Discuss defect difficulty and explain the risk involved because of that defect.

Allocate work to fix defects to relevant developers.

Update the defect resolution and include development notes in case any information is missing or any additional information needed by developers.

Project Manager

Help in the prioritization of the defects.

Discuss the next iteration release date for QA.

Need to make sure that related user representatives are also invited to the bug triage meeting.

What happens during ‘Defect Triage’ Meeting?

Test Team leader sends out a bug report with the new defects. During the defect triage meeting, each defect is analyzed to see whether right priority and severity are assigned to it.

Priorities are rearranged if needed.

Defects are analyzed and evaluated by the degree of their severity.

This include discussion regarding the complexity of the defect, risks, rejection, reassignment of errors is done.

Updates are captured in bug tracking system.

The QA engineer will make the changes to each defect and discuss them with each attendee.

The “Comments” field is updated correctly by noting essential points of the meeting.

What is the outcome of the ‘Defect Triage’?

At the end of every meeting, Defect Triage Metrics will be prepared and given to all the attendees. This report acts as the meeting minutes which will prove helpful for future meetings.

Conclusion:

Defect triage is a process where each bug is prioritized based on its severity, frequency, risk, etc.

The goal of Bug Triage is to evaluate, prioritize and assign the resolution of defects.

The frequency of defect triage meeting is decided according to the project schedule, number of defects in the system, overall project health, etc.

Project Manager, Test Team Leader, Technical Lead, Development Team Leader are taken part in this meeting.

Defects are analyzed and evaluated by the degree of their severity.

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What Is Domain Testing In Software Testing? (With Example)

What is Domain Testing?

Domain Testing is a Software Testing process in which the application is tested by giving a minimum number of inputs and evaluating its appropriate outputs. The primary goal of Domain testing is to check whether the software application accepts inputs within the acceptable range and delivers required output.

It is a Functional Testing technique in which the output of a system is tested with a minimal number of inputs to ensure that the system does not accept invalid and out of range input values. It is one of the most important White Box Testing methods. It also verifies that the system should not accept inputs, conditions and indices outside the specified or valid range.

Domain testing differs for each specific domain so you need to have domain specific knowledge in order to test a software system.

In this tutorial, you will learn-

Simpler Practice of Domain Testing

In domain testing, we divide a domain into sub-domains (equivalence classes) and then test using values from each subdomain. For example, if a website (domain) has been given for testing, we will be dividing the website into small portions (subdomain) for the ease of testing.

Domain might involve testing of any one input variable or combination of input variables.

Practitioners often study the simplest cases of domain testing less than two other names, “boundary testing” and “equivalence class analysis.”

Boundary testing – Boundary value analysis (BVA) is based on testing at the boundaries between partitions. We will be testing both the valid and invalid input values in the partition/classes.

Equivalence Class testing – The idea behind this technique is to divide (i.e. to partition) a set of test conditions into groups or sets that can be considered the same (i.e. the system should handle them equivalently), hence ‘equivalence partitioning.’

That simplified form applies for Domain testing –

Only to tests of input variables

Only when tested at the system level

Only when tested one at a time

Only when tested in a very superficial way

It can be simplified as below:

Variable

Valid Class Equivalence Class

Invalid Class Equivalence Class

Boundaries & Special cases

Notes

0-100

100

-1

>100

101

Explanation:

If a field accepts ranges from 0-100, the field should not accept -1 and 101 as they are invalid entries and beyond the boundaries.

The field should accept values such as 0,100 and any number between them.

Building table like these (in practice)

The table should eventually contain all variables. This means, all input variables, all output variables, and any intermediate variables that you can observe.

In practice, most tables that I have seen are incomplete. The best ones seen list all the variables and add detail for critical variables.

Domain Testing Strategy

While domain testing, you need to consider following things,

What domain are we testing?

How to group the values into classes?

Which values of the classes to be tested?

How to determine the result?

What domain are we testing?

Any domain which we test has some input functionality and an output functionality. There will be some input variables to be entered, and the appropriate output has to be verified.

Domain Testing Example

Consider a single input test scenario:

C = a+b, where a and b are input variables and C is the output variable.

Here in the above example, there is no need of classification or combination of the variables is required.

Consider the below multiple inputs and appropriate output scenario:

Consider a games exhibition for Children, 6 competitions are laid out, and tickets have to be given according to the age and gender input. The ticketing is one of the modules to be tested in for the whole functionality of Games exhibition.

According to the scenario, we got six scenarios based on the age and the competitions:

Age<5, both boys and girls should participate in Rhymes Competition.

Here the input will be Age and Gender and hence the ticket for the competition will be issued. This case partition of inputs or simply grouping of values come into the picture.

How to group the values into classes?

Partitioning some values means splitting it into non-overlapping subsets.

As we discussed earlier there are two types of partitioning:

Equivalence partitioning – Equivalence partitioning is a software testing technique that divides the input data of a software unit into partitions of equivalent data from which test cases can be derived. In principle, test cases are designed to cover each partition at least once.

Boundary value analysis – Boundary value analysis is a software testing technique in which tests are designed to include representatives of boundary values in a range. The idea comes from the boundary.

For the above example, we are partitioning the values into a subset or the subset. We are partitioning the age into the below classes :

Class 1: Children with age group 5 to 10

Class 2 : Children with age group less than 5

Class 3: Children with age group age 10 to 15

Class 4: Children with age group greater than 15.

Which values of the classes to be tested?

The values picked up for testing should be Boundary values:

Boundaries are representatives of the equivalence classes we sample them from. They’re more likely to expose an error than other class members, so they’re better representatives.

The best representative of an equivalence class is a value in between the range.

For the above example we have the following classes to be tested:

For example for the scenario #1:

Boundary values:

Values should be Equal to or lesser than 10. Hence, age 10 should be included in this class.

Values should be greater than 5. Hence, age 5 should not be included in this class.

Values should be Equal to or lesser than 10. Hence, age 11 should not be included in this class.

Values should be greater than 5. Hence, age 6 should be included in this class.

Equivalence partition Values:

Equivalence partition is referred when one has to test only one condition from each partition. In this, we assume that if one condition in a partition works, then all the condition should work. In the same way, if one condition in that partition does not work then we assume that none of the other conditions will work. For example,

Scenario

Boundary values to be taken

Equivalence partitioning values

Input age = 6

Input age = 5

Input age = 11

Input age = 10

Input age = 8

Input age = 6

Input age = 5

Input age = 11

Input age = 10

Input age = 8

Input age = 11

Input age = 10

Input age = 15

Input age = 16

Input age = 13

Input age = 11

Input age = 10

Input age = 15

Input age = 16

Input age = 13

Age<=5

Input age = 4

Input age = 5

Input age = 3

Input age = 15

Input age = 16

Input age = 25

How do we determine whether the program passed or failed the test?

Passing the functionality not only depends upon the results of the above scenarios. The input given and the expected output will give us the results and this requires domain knowledge.

Determining the results of the example:

Hence, if all the test cases of the above pass, the domain of issuing tickets in the competition get passed. If not, the domain gets failed.

Domain Testing Structure

Usually, testers follow the below steps in a domain testing. These may be customized/ skipped according to our testing needs.

Identify the potentially interesting variables.

Identify the variable(s) you can analyze now and order them (smallest to largest and vice versa).

Create and identify boundary values and equivalence class values as above.

Identify secondary dimensions and analyze each in a classical way. (In the above example, Gender is the secondary dimension).

Identify and test variables that hold results (output variables).

Evaluate how the program uses the value of this variable.

Identify additional potentially-related variables for combination testing.

Imagine risks that don’t necessarily map to an obvious dimension.

Identify and list unanalyzed variables. Gather information for later analysis.

Summarize your analysis with a risk/equivalence table.

Summary:

Domain testing, as it is described above, requires knowledge of providing right input to achieve the desired output. Thus, it is only possible to use it for small chunks of code.

Test Management Process In Software Testing

Test Management

Test Management is a process of managing the testing activities in order to ensure high quality and high-end testing of the software application. The method consists of organizing, controlling, ensuring traceability and visibility of the testing process in order to deliver a high-quality software application. It ensures that the software testing process runs as expected.

You become a Test Manager of the most important project in your company. The project task is to test the net banking facility of the esteemed “Guru99 Bank”

Everything seems to be great. Your boss trusts you. He counts on you. You have a good chance to prove yourself in your task. But the truth is:

Test Management is not just a single activity. It consists of a series of activities

Test Management Phases

This topic briefly introduces Test Management Process and shows you an overview of Test Management Phases.

Zephyr Enterprise is more than a test management solution; we are a test management partner ready to help you achieve all your testing activities from a single tool.

From creating test cases and plans, to defining user requirements and generating reports, Zephyr Enterprise arms you with the insights, flexibility, and visibility necessary to deliver software faster – with fewer bugs!

Features:

Premium Enterprise Support

Bi-directional Jira Integration

Enterprise-grade test planning and auditing

Ready-to-use reports and customizable dashboards

End-to-end traceability

Flexible support for third-party automation frameworks

Legacy ALM migration path and transition plan

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Test Management Process

Test Management Process is a procedure of managing the software testing activities from start to end. The test management process provides planning, controlling, tracking, and monitoring facilities throughout the whole project cycle. The process involves several activities like test planning, designing, and test execution. It gives an initial plan and discipline to the software testing process. To help manage and streamline these activities, consider using one of these top test management tools.

There are two main parts of Test Management Process: –

Planning

Risk Analysis

Test Estimation

Test Planning

Test Organization

Execution

Test Monitoring and Control

Issue Management

Test Report and Evaluation

Planning Risk Analysis and Solution

Risk is the potential loss (an undesirable outcome, however not necessarily so) resulting from a given action or an activity.

Risk Analysis is the first step that Test Manager should consider before starting any project. Because all projects may contain risks, early risk detection and identification of its solution will help Test Manager to avoid potential loss in the future & save on project costs.

You will learn more detail about the Risk Analysis and Solution here.

Test Estimation

An estimate is a forecast or prediction. Test Estimation is approximately determining how long a task would take to complete. Estimating effort for the test is one of the major and important tasks in Test Management.

Benefits of correct estimation:

Accurate test estimates lead to better planning, execution, and monitoring of tasks under a test manager’s attention.

Allow for more accurate scheduling and help realize results more confidently.

You will learn more details about the Test Estimation and metrics here.

Test Planning

A Test Plan can be defined as a document describing the scope, approach, resources, and schedule of intended Testing activities.

A project may fail without a complete Test Plan. Test planning is particularly important in large software system development.

In software testing, a test plan gives detailed testing information regarding an upcoming testing effort, including:

Test Strategy

Test Objective

Exit /Suspension Criteria

Resource Planning

Test Deliverables

You will learn more detail about Test Planning in this article.

Test Organization

Test Organization in Software Testing is a procedure of defining roles in the testing process. It defines who is responsible for which activities in the testing process. The same process also explains test functions, facilities, and activities. The competencies and knowledge of the people involved are also defined. However, everyone is responsible for the quality of the testing process.

Now you have a Plan, but how will you stick to the plan and execute it? To answer that question, you have Test Organization phase.

Generally speaking, you need to organize an effective Testing Team. You have to assemble a skilled team to run the ever-growing testing engine effectively.

Execution Test Monitoring and Control

What will you do when your project runs out of resources or exceeds the time schedule? You need to Monitor and Control Test activities to bring it back on schedule.

Test Monitoring and Control is the process of overseeing all the metrics necessary to ensure that the project is running well, on schedule, and not out of budget.

Monitoring

Monitoring is a process of collecting, recording, and reporting information about the project activity that the project manager and stakeholder needs to know

To Monitor, Test Manager does the following activities

Define the project goal, or project performance standard

Observe the project performance, and compare the actual and the planned performance expectations

Record and report any detected problem which happens to the project

Controlling

Project Controlling is a process of using data from monitoring activity to bring actual performance to planned performance.

In this step, the Test Manager takes action to correct the deviations from the plan. In some cases, the plan has to be adjusted according to project situation.

Issue Management

As mentioned at the beginning of the article, all projects may have potential risks. When the risk happens, it becomes an issue.

In the life cycle of any project, there will be always unexpected problems and questions that crop up. For example:

The company cuts down your project budget

Your project team lacks the skills to complete the project

The project schedule is too tight for your team to finish the project at the deadline.

Risks to be avoided while testing:

Missing the deadline

Exceed the project budget

Lose the customer’s trust

When these issues arise, you have to be ready to deal with them – or they can potentially affect the project’s outcome.

How do you deal with the issues? What is issue management? Find the answer in this article

Test Report & Evaluation

The project has already been completed. It’s now time to look back at what you have done.

The purpose of the Test Evaluation Reports is:

“Test Evaluation Report” describes the results of the Testing in terms of Test coverage and exit criteria. The data used in Test Evaluation are based on the test results data and test result summary.

Software Testing Methodologies – Learn Qa Models

What is Software Testing Methodology?

The tactics and testing kinds utilized to ensure that the Application Under Test satisfies customer requirements are referred to as software testing methodology. To validate the AUT, test methodologies include functional and non-functional testing. Unit testing, integration testing, system testing, performance testing, and other testing methodologies are examples. A test objective, test strategy, and deliverables are all outlined in each testing methodology.

Many firms use the terms Development Methodologies and Testing Methodologies interchangeably since Software Testing is a vital aspect of any Development Methodology. In contrast to the previous definition of Testing Methodologies, Testing Methodologies might also refer to Waterfall, Agile, and other QA methods. The discussion of various forms of testing adds little value to the readers. As a result, we’ll go over the various development models.

Waterfall Model

Software development in the waterfall paradigm proceeds progressively through many phases such as Requirements Analysis, Design, and so on. In this paradigm, the following phase doesn’t start until the previous one is finished.

What Is the Testing Methodology?

The requirements phase is the first phase in the waterfall paradigm, and it is here that all of the project requirements are fully determined before testing begins. The test team brainstorms the scope of testing, develops a test strategy, and creates a thorough test plan during this phase.

Only once the software design is complete will the team begin executing test cases to confirm that the built program works as planned.

In this procedure, the testing team only moves on to the next step when the portion is subjected to several waterfall iterations. A new module is created or an existing module is improved at the conclusion of each cycle. This module is built into the software architecture, and the entire system is put through its paces.

What is the approach to testing?

The entire system is tested as soon as the iteration is done. Testing feedback is accessible right away and is included in the following cycle.

Based on previous iterations’ experience, the testing time necessary in that software requirements would not change during the project. However, as the criteria get more sophisticated, they experience multiple adjustments and evolve over time. Occasionally, the buyer is unsure about what he wants. Despite the fact that the iterative model overcomes this problem, it still follows the waterfall methodology.

Software is built with an Agile approach in incremental, quick cycles. Customer, developer, and client interactions are prioritized above procedures and tools. Rather than significant preparation, the agile technique focuses on adjusting to change.

What Is the Testing Methodology?

Agile development methodologies employ incremental testing, which ensures that each project release is adequately tested. This guarantees development cycles. Simple engineering activities are grouped into a project. Programmers create a basic piece of software and then provide feedback to the consumer. The customer’s feedback is taken into account, and the engineers move on to the next assignment.

Extreme programming is frequently done in teams of two.

Extreme Programming is utilized in environments where the client needs change often.

What Is the Testing Methodology?

Extreme programming is based on the Test-Driven Development methodology, which is defined as follows −

To check the new feature that has yet to be implemented, add a Test Case to the test suite.

Run all of the tests, and because the functionality hasn’t been developed yet, the new test case must fail.

To implement the feature/functionality, write some code.

Re-run the test suite. Since the functionality has been written, the to choose from. Each testing approach and methodology is tailored to a considerations all influence the approach used.

Testing input is encouraged early in the development life cycle by certain techniques, while others wait until a functional model of the system is available.

What is the best way to build up software testing methodologies?

Testing software code should not be the exclusive purpose of software testing approaches. The overall picture should be examined, and the testing approach should satisfy the project’s primary aim.

Scheduling − The key to implementing good testing techniques is realistic scheduling, and the plan should accommodate the demands of every team member.

Deliverables that have been defined − Well-defined deliverables should be offered to keep all members of the team on the same page. There should be no uncertainty in the content of the deliverables.

Methodology for testing − The testing team should be able to create the appropriate test methodology after scheduling is complete and stated deliverables are made accessible. The team should be informed about the optimum test method for the project through definition documents and development meetings.

Reporting − Transparent reporting is tough to obtain, yet this phase defines the project’s testing strategy’s efficacy.

Validation and Verification

The V-methodology is a branch of the waterfall model that is used for small projects with well-defined software needs. It is organized in a ‘V-shaped’ form that includes coding, verification, and validation. Because coding is the foundation of the model, each development phase is accompanied by testing, allowing for the early discovery of mistakes at each stage.

Methodology for Testing

In terms of parallel testing processes undertaken at each development step, the ‘V-model’ differs from the waterfall approach. The verification process guarantees that the product has been produced appropriately, while the validation phase assures that it is the correct product for the job.

The static verification stages in the model begin with a business requirement analysis, followed by system design, architectural design, and module design. Following that, the coding step ensures that the appropriate language and tools are selected in accordance with the coding standards and rules. Finally, the validation process guarantees that unit testing, integration testing, system testing, and application testing are performed on each module and stage of development.

Advantages

Testing and validation at each level enable the early detection of faults in the development process.

It’s a low-cost, quick-turnaround testing method.

Because of its stiffness, it’s perfect for little jobs.

The validation and verification process includes well-defined goals at failures.

There isn’t a clear way to get rid of the software flaw.

The approach is ineffective for big projects with a high likelihood of modification.

It is unable to handle many events at the same time.

After a module has entered the testing phase, there is no turning back.

Case Studies

Medical devices and software applications are two types of medical gadgets.

Applications and software initiatives for the government.

Projects and applications in defense.

Commercial applications are available.

Methodology for Rapid Action Development

The testing model is a type of incremental approach that arose from the agile software development process. The core of RAD is prototyping while simultaneously building software components, allowing testers to focus on testing rather than planning and documentation. While each software function is segregated and created as a distinct component, they are combined to build a prototype, which is then used to gather end-user input and make further modifications.

Methodology for Testing

The RAD technique consists of five phases in which system components are simultaneously designed and tested. Each of these phases has a set time limit and must be completed as soon as possible, making it ideal for projects with a tight deadline.

The initial step, known as “Business Modeling,” defines business requirements and establishes the flow of data to various business channels. After the flow has been established, the ‘Data Modeling’ step examines pertinent data in accordance with the business model.

‘Process Modeling,’ the third step, translates data items to create a business information flow. The phase specifies the QA procedure for further modifying data items in response to customer input. This is done with the understanding that the app may go through several iterations over time.

The prototype step is the fourth stage of ‘Application Generation,’ and the models are coded using automated techniques. Finally, in the ‘Testing and Turnover’ phase, each prototype is independently tested, decreasing faults and hazards in the total software program.

Advantages

Simultaneous prototyping and reusability cut down on development and testing time.

The software project’s total risks are reduced by using a time-box be delayed.

Technical skills and resources are quite important.

Costs rise as a result of automation testing, tools, and code

Chatbot Testing In 2023: A/B, Auto, & Manual Testing

Chatbot success is elusive, and claims such as 10 times better ROI compared to email marketing makes sense only if the chatbot is implemented successfully. This article goes into detail about how a combination of pre-launch tests (automated and manual tests) and post-launch A/B testing, customized for chatbots, can help companies build successful chatbots. We will also talk about the other popular testing techniques, such as ad-hoc and speed testing.

What are the tests to complete before launching a chatbot?

Good developers build automated tests for the expected input/output combinations for their code. Similarly, chatbot’s natural understanding capabilities and typical responses need to be tested by the developer. These automated tests ensure that new versions of the chatbot does not introduce new errors.

The three types of tests below (general, domain specific and limit tests) need to be completed and ideally automated before releasing the chatbot. They test the key points of chatbots and would enable a company to pinpoint problems before launching its chatbot. After chatbot launch, they need to be automatically repeated to ensure that the new version does not break existing functionality

General testing

This includes question and answer testing for broad questions that even the simplest chatbot is expected to answer. For example, greeting and welcoming the user are tested.

If the chatbot fails the general test, then other steps of testing wouldn’t make sense. Chatbots are expected to keep the conversation flowing. If they fail at the first stage then, the user will likely to leave the conversation hurting key chatbot metrics such as conversation rate and bounce rate.

Domain-specific testing

The second stage would be testing for the specific product or service group. The language and expressions related to the product will be used to drive the test and ensure that chatbot is able to answer domain specific queries. In case of an e-commerce retailer, that could be queries related to types of shoes for example. An e-commerce chatbot would need to understand that these all lead to the same intent: “cage lady sandal shoe,” “strappy lady sandal shoe,” or “gladiator lady sandal shoe.”

Since it is impossible to capture every specific type of question related to that specific domain, domain specific testing needs to be categorized to ensure that key categories are covered by automated test.

These context related questions will be the ones that drive the consumer to buy the product or the service. Once the greeting part of the conversation is over, the rest of the conversation will be about the service or the product. Therefore, after the initial contact and main conversations, chatbots need to ace this part or attain the maximal correct answer ratio, another key chatbot metric.

Limit testing

The third stage would be testing the limits of our chatbot. For the first two steps, we assumed regular expressions and meaningful sentences. This last step will show us what happens when the user sends irrelevant info and the how the chatbot would handle it. That way, it would be easier to see what happens when the chatbot fails.

Manual testing

Manual tests do not necessarily mean the team spending hours on testing. Amazon’s Mechanical Turk operates a marketplace for work that requires human intelligence. The Mechanical Turk web service enables companies to programmatically access this marketplace and a diverse, on-demand workforce. Developers can leverage this service to build human intelligence directly into their applications. This service can be used for further testing and reach for a higher confidence interval.

Source: The Register

What are things to pay attention in pre-launch testing?

Important aspects include:

Understanding Intent

Chatbots needs to understand what users want and intent classifier is one of the main modules of a chatbot:

Building a flexible intent understanding system requires leveraging machine learning. Machine learning solutions predict intent mostly correctly for the input set and have the capacity to predict intent for cases they never encountered before. Given this imperfect nature of solution, developers should focus on biggest misunderstanding issues and accept errors in edge cases. Of course, as in any machine learning problem, intent prediction can be improved with a larger volume of ground truths (i.e. manually labelled examples).

Conversation flow

Bot should be flexible enough to jump to different points in the task such as changing the delivery address after that address was input by the user. It should also not introduce unnecessary steps and make use of UX elements such as radio buttons which can enable users to communicate more effectively compared to using text alone.

Error handling

There will inevitably be cases where the bot does not understand the input. Bot’s responses need to be tested so it communicates its lack of understanding clearly and helps the user proceed (e.g. by contacting a live agent).

What are post-launch chatbot testing techniques?

A/B testing is the most flexible way to test various aspects of chatbot functionality once a chatbot has active users.

What is A/B testing?

A/B testing is defined as comparing two versions of a product to see which one performs better. You compare two products by showing the two variants to similar visitors at the same time

Even though it has been used for ages in other fields of marketing. Currently, there are not many A/B testing alternatives available for chatbots.

But basically, it is a way to experiment distinct characteristics of the chatbots, through randomized trials, companies can collect data and decide on which alternative to use. Testing a chatbot is conducted through an automated testing process. This makes it possible to hasten development processes of the chatbot and ensures further quality assurance.

We can dissect the process into two separate test steps of the chatbot design. One is deciding on the visual factors of the chatbot such as the design, color or the location of the chatbot on the web page.

The other factor to decide is the conversational factors, such as the quality and the performance of the algorithm. Those two factors need to be tested for a better user experience.

Conversational Factors

We have previously written an article regarding the key metrics for chatbots. Through A/B testing, the key metrics to follow will likely to remain the same. Retention rates and drop-offs will still be the significant factor in deciding the success of the chatbot. User engagement rates for different chat bot alternatives will still be significant.

One such test is about deciding on how to start the conversation: should the chatbot start with a standard salutation, or use distinct messages such as emoji included messages? This would be the key factor since the customer funnel flows through the first engagement.

If the chatbot is successful in eliciting the desired action which is making the user interact with the chatbot, we are more likely to reach a higher audience and higher conversation flow.

After the initial contact, different alternatives for messaging can be created. This might be achieved through using customer data. Data sources such as user’s search history or location can be a fantastic way to achieve that customization. Different conversational messages can be created, but the order of this message can dramatically affect the hazard rate of the customer.

Since after the first few messages, most chatbots can detect the characteristics and keep the conversation flow. But artificial intelligence can experience problems if the initial contact never occurred.

One such chatbot company is Botanalytics. They provide chatbot analytics tools. Their platform can provide insights and reports such as users’ activity (as a graph and number), conversation activity (as a graph and number), average conversation steps per user, average conversation per user, most common keywords, most active hours, and average session length. Botanalytics provides correlation analysis to bot owners. It is possible to elaborate the details of the test groups and cohorts.

Second is deciding on the formality of the language, the question is to decide on whether using a formal language increases the engagement or not. Depending on the customer or the user profile, this is of crucial importance, multiple responses need to be tested. Therefore, the level of formality will shape the input provided by the user hence making it a rather difficult conversation to process by the artificial intelligence algorithm.

The tradeoff is whether the language of the bot increases and brings a greater return on engagement or not. Since we have the instinct to buy from or engage with the people who share the same characteristics, bot responses will affect this dramatically. Hence the only channel the user experiences the chatbot is through its language. Therefore, return on engagement will be the key metric for that type of A/B testing.

Visual Factors

Design of the chatbot is also important, but this is rather a not-so-technical side of the chatbots. Still, it is a crucial factor for the success of user experience. This can be done by changing the frame color or button color. Basically, this is the part where the firms would utilize the traditional A/B testing procedures.

The effects of visual and conversational factors are needed to be studied further. Currently, there is no data regarding which factor influences more. Separating and deciding on which factor to focus on is still important. But right now, as a whole, A well-structured and engaging UX in messenger chatbots may boost retention rates up to 70%.

For the chatbots, the companies can still utilize the methods mentioned in the survey analytics article. The right experimental design will make it possible the construct the right counterfactual and provide objective results. But the most basic steps for deciding on how to implement a chatbot A/B test are as follows;

7 Steps to chatbot A/B testing

Choose the platform to conduct the A/B testing

Analyze the chatbot funnel. Create a list of visual factors to conduct the test.

Do the same for conversational factors, different algorithms, different structures

Decide on the test method to use, control for interactions between the factors to be tested, gather as much data as possible

Compare and analyze the alternatives, if necessary, test for additional factors

Keep testing, keep it as a dynamic process and achieve higher performance

Improve your Chatbot and Enjoy!

What are other chatbot testing approaches? Testing the chatbot’s performance in speed and security

Security is critical in any application and the infinite possibilities enabled by text can complicate testing a bot in terms of security features however these are crucial tests for operational bots.

Ad-hoc testing

Many of the key metrics and key test mentioned in this article are broad test categories. It is possible to test further and generate ad-hoc categories and methods, but it is important to note that chatbots are bots.

No matter how hard the people try, at the current stage, chatbots have limits. So, expecting a human-like performance is expecting a god-like performance from a human. It happens every once in a while but doesn’t happen overnight or all the time.

Agile development is still the key to success. Even after the chatbot is released, the process continues. Feedback is the most essential element to shape the chatbot. Real life performance should be monitored closely to keep the chatbot versatile and robust.

For more on chatbot testing

If you are interested in learning more about chatbots, read:

For a comprehensive guide on how chatbots are using voice to transform businesses:

Finally, if you believe your business would benefit from a chatbot platform, we have a data-driven list of vendors.

We will help you choose the best one for your business:

Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.

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Ultimate Guide To Integration Testing Vs. Unit Testing In 2023

Businesses and developers use various software testing methods to deliver high-quality software.

Finding errors during the testing stage is seven times less expensive than the production stage of software.

Unit testing and integration testing are essential testing practices for software applications. It is important for QA teams to know the differences between the two since each practice uses different methods and is executed at different stages of software testing.

This article aims to compare integration and unit testing and pay attention to their differences, benefits, and when to use them.

What is the key difference between integration testing and unit testing?

The main difference between integration and unit testing is that they are used at different stages of the development process and have different goals. Unit testing focuses on individual code units, while integration testing focuses on how they work together.

What is integration testing?

Integration testing is a method of testing how different units of code work together. The goal of integration testing is to ensure that the integrated system behaves as expected and that there are no conflicts or errors between different code units.

What is unit testing?

Unit testing is a method of testing individual code units, such as functions or practices, in isolation from the rest of the system. Unit testing aims to ensure that each unit of code works as intended and to identify any bugs early in the development process.

See the testing pyramid below (Figure 1) to see the place of integration and unit testing in the levels of software testing.

Figure 1: Testing Pyramid

Source: Medium

Top 6 Benefits of Unit Testing

Early detection of bugs: A unit test can help detect bugs early in the development process before the code is deployed to production, saving time later for integration tests.

Improved code quality: Writing unit tests can help developers write cleaner, more maintainable code and reduce test failures by 20%.

Easier refactoring: Unit tests provide a safety net when making changes to the code, making it easier to refactor code without introducing new bugs.

Increased confidence in code changes: Unit tests provide a way to automatically verify that changes to the code have not introduced new bugs.

Facilitate collaboration: Unit tests help ensure that code changes by different developers do not break existing functionality.

Enables TDD: Unit testing facilitates Test-driven Development (TDD), a software development methodology where you write tests before the actual code.

When should you use unit testing?

Unit testing is typically performed during the development process as soon as a unit of code is written, specifically in the following situations when:

Developing new features: Unit tests should be written to test new code before deployment to production. This is also known as Test-Driven Development (TDD). TDD is a software development methodology where you write tests before writing the actual code; unit testing is an essential part of this methodology.

Refactoring existing code: Unit tests can ensure that changes to the code do not introduce new bugs, so it is best to test when refactoring the code. Unit tests can also help ensure that code changes by different developers do not break existing functionality.

Integrating new libraries or dependencies: Unit tests can be used to ensure that the integration of new libraries and dependencies is working as expected.

Whether to use unit testing depends on the project’s complexity, team size, the nature of the codebase, and the development process.

Read our ‘10 Unit Testing Best Practices’ article to learn more about unit testing.