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The software also includes just about all the controls you need from an image editing software. PhotoEditorX has a reputation for being very user friendly and it is certainly easy to get to grips with the latest version. I understand that I can get a Complete Photo and Image Editing Software Plus 3+ Hours Of Video Training, 3 Bonus Sofware and 200+ Pages of Tutorials for just $297 $27 via instant download.
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Additionally, the definition of risk is incomplete without introduction to mitigation and contingency. Mitigation: Mitigation is the act performed that reduces the possibility to defects to show up.
Contingency: This is the backup plan of action to be performed in case a risk becomes a possibility, and which helps to reduce the impact. Risk-based testing (RBT) is an organizational principle that helps to prioritize testing the features and functions of a software according to the probable risks of failure, the need of the function, etc. As there usually is not enough time to test complete functionality of a product, RBT involves testing the functionality that has the highest probability of failure – and thereby biggest impact. Identifying risks to system quality and guiding the process of planning, preparation and execution of the tests.
Mitigation–testing (that reduces the possibility of high-impact defects) and contingency–testing (that identifies the possible work-arounds for the defects found).
Identify and define all the possible risks for all the functional modules of the application under test (AUT) and assign them to the responsible stakeholders.
As all the critical functions of the application are tested, it improves the overall quality of the product. Planned prioritization helps take care of the business-critical areas which ensures that the product even in case of a risk-impact, does not get impacted much.
Since the problem areas are discovered early, preventive measures can be started immediately – which ends saving a lot of time and costs during production.
In case of limited resources (time or team), it helps as a negotiating tool for prioritization. Continuous monitoring of risks helps focus on the complete testing strategy and goal throughout the testing life cycle. That said, the main objective of risk-based testing is to perform testing in accordance with the best practices in risk management.
At Gallop, we cover all the bases and ensure that effective testing is performed by the right set of experts. The opinions expressed in this blog are author's and don't necessarily represent Gallop's positions, strategies or opinions.
The industry today has awakened to the fact that testing is actually more important than programming. Software Development Engineer in Test (SDETs) are skilled professionals who are adept in the arena of both QA Engineering and Software Development. Though it’s great to have someone with skills and expertise that are high in demand, it also creates a bit of confusion as to what really comprises the duties and responsibilities of SDETs. While the roles of SDETs may seem very similar to those of QA Automation Engineers, with even most of the tools and language expertise required being same (Selenium, Java, and Jenkins), there are certain very obvious and clear differences between the two roles. An SDET, in layman terms, is a developer who instead of working in the product development team, works as part of the test team. On the other hand, QA Engineers are testers who do not need to have any programming experience as they usually are not exposed to the code.
With the need and importance of software testing accepted across the globe, what, when, and how to test are areas that have never stopped evolving. Most of the products and apps today require end-to-end Test Automation – especially in the areas of Functional, Performance, and Security Testing. Armed with specialized testing knowledge of multiple tools, techniques, best practices, and processes, SDETs today have become a crucial part of development ecosystems. In essence, SDETs are Customer Advocates who influence product design by understanding end user expectations. The above stated pithy statement relates very well to the need and importance of testing metrics.
In normal parlance, most organizations follow the well tread path of plan, do, check, act (- better known as PDCA) when beginning any new venture or project.
Do: This is the stage where organizations define and decide upon the multiple measurement variables and metrics. Check: This stage is used to analyse the reasons as to why a product is behaving in the way it is, as also to compare the data before-and-after a fix has been made. Act: As the name implies, this stage involves taking Corrective Actions and fixing the product to come up with a quality product. As seen above, one of the most important link between all the 4 activities – PDCA – is metrics and its measurement. What sort of metrics need to be collected and analysed must be decided in the planning phase. Unless we specify what needs to be measured, we will never really be able to give due attention and focus to completing it to the best of our abilities. That said, what is even more important than measuring metrics is the follow up – what is the actual improvement we have made in the product based on our findings. Zooming in to the top-most priorities and then working against the related metrics will help an organization provide better quality products, reduced go-to-market time and hence improve their ROI. Experts at Gallop can help you understand what needs to be measured and tested to get the optimum outputs. Let us try to understand a a couple of these which are already contributing to an organization’s growth, sustenance and differentiation. Mobile Apps: There’s hardly any industry left today that is untouched by the presence or use of mobiles.
Digital Transformation: The need to go digital and have a global digital imprint is making organizations resort to a lot of online activities that leave a big scope for hackers to make hay. So how do we create a risk mitigation plan for dealing with the challenges that come packaged when running either of the businesses listed above? In essence, if organizations use either in-house talent, or approach specialized independent testing service providers for performing thorough testing of apps, tools, or devices, they can take care of most of the risks.
Get in touch with us at Gallop to get further guidance on getting your products tested for a better ROI. We all accept that Testing forms an important part of the software development life cycle (SDLC).
Instead of trying to overburden the tester to test for completeness just before launching the product, plan your test related activities.
In essence, if we treat Testing as a process that supports the entire development process – instead of just a single phase – we can ensure products that are far more dependable and robust. Requirements Gathering phase: The main focus of this phase is to gather the business requirements such as who will use what type of data in what manner.
Design phase: The Design phase uses the Requirement Specification document to prepare the layout of the system and software design.
Development phase: As the name suggests, the development phase involves the actual writing of code for the different modules. Deployment phase: The deployment phase usually has two sub-phases – Beta-deployment, and Final Deployment. As seen above, if Testing is implemented across all the phases of SDLC, the end result will be a product that is stable, reliable, and supports features and functions that will grab the attention of the end user.
The term non-functional testing is commonly used to refer to testing the features not specific to functions. In essence, most of these tests help us to understand the quality and reliability of the product. Even though there’s a whole range of tests available for testing the Functionality of a product in terms of how to use it, when related to non-functional testing, it relates to the ease of use of the product and the experience of a consumer, and how happy is someone while using the same. Apart from this, the seamless performance of all the processes also indicate that a lot of thought and planning have been put into the product to make it achieve the required levels of quality. Not checking for the quality of security in either of the aforementioned areas may cause huge (at times not recoverable) losses in terms of finances, credibility, etc. On a different front, the quality of a software with regards to its Speed, Resource Consumption, and Scalability matters a lot while trying to retain and attract new customers. Thus, as can be safely deduced, that in terms of non-functional testing, good quality of a product will always help you gain (and retain) more customers rather than just focussing on testing the features of a product. Gallop’s teams have successfully performed Non-Functional Testing for our numerous clients. Emotional intelligence refers to the understanding of our own emotions, how to use this knowledge to deal effectively with people and problems to reduce anger and hostility, and create an atmosphere of collaboration to produce positive energy. The concept of EI owes its immense popularity to New York Times science journalist, Harvard psychologist, and author Daniel Goleman who wrote the 1995 best-seller, ‘Emotional Intelligence: Why It Can Matter More Than IQ’. According to an older definition of Testing- “To tell somebody that he or she is wrong is called criticism.
Testers essentially are people who like to disrupt and break things so as to find out the true quality of a product. People who have a high level of EI are self-aware (know what they feel and why), self-managed (know how best to manage negative emotions, create positivity), socially aware (know the nuances of how to interact with others), and good at relationship management. All of the above qualities may actually be listed as pre-requisites for someone who wishes to join the band-wagon of testing community at any level. Testing professionals, apart from the inferences from the plethora of tools available today, also trust their intuition a lot.
Professionals in the Testing arena also have to regularly face very highly strung scenarios as they work in very uncertain environments wherein tests may pass or fail.
Naturally, these activities at times lead to fracturing of egos and unnecessary debates and endless hours of unproductive meetings.
Amygdala is a small, almond-shaped structure at the top of the brainstem that is associated with the human tendency of “fight or flight”. A good EI level helps us control the immediate reactions and makes us more empathetic towards our colleagues, and helps us try to understand why they may be reacting in a particular fashion.
A mature EI level will always help us provide criticism in a manner that is more conducive for mutual growth rather than just for pointing fingers.
The key to creating and managing effective trading systems is to ensure high volume and effectively low latency throughput. Recent innovations such as automated trading, need for 24 hrs continuous trading, market fragmentation, and changes in underlying technologies such as algorithmic trading, have further added to the trading system complexity.


As trading systems need to process vast amounts of data in real time, accuracy of data is primarily crucial to avoid huge losses in terms of money and reputation. The major types of testing trading systems include functional, interface, security, and performance testing. Let us also know about Backtesting that refers to applying a trading system to old data and verify how it behaves to the data during the specified time period.
In recent years, businesses have raised their expectations for development projects, cutting back financial resources and at the same time demanding shorter production cycles. Because of the heightened importance being assigned to quality of applications, it is critical to not just have quality testing teams in place but also to have a defined way of measuring goals & efficiency of the test teams. Software Testing Metrics are useful for evaluating the health, quality, and progress of a software testing effort. Software Testing Metrics had always been an integral part of software testing projects, but the nature and type of metrics collected and shared have changed over time.
Some of the most common software testing metrics that can be used for both automation and for software testing in general are given below. Progress: Deals with the parameters that help identify test progress to be matched against success criteria.
The principle of coverage metrics is to communicate to all stakeholders about what is covered during formal testing. This metric determines how defects are identified and created by evaluating the compliance with agile principles. Test effectiveness needs to be assessed statistically to determine how well the test data has exposed the defects contained in the product. It determines the number of test procedures successfully executed (without defects) versus the number of test procedures. Current Quality Ratio metric provides indications about the amount of functionality that has been demonstrated successfully. At Gallop, we look at software testing as a process that starts from the requirements gathering stage itself, rather than at the end of the development lifecycle.
ETL stands for Extract-Transform-Load and is a typical process of loading data from a source system to the actual data warehouse and other data integration projects. Organizations with already well defined IT practices are at an innovative stage to create the next level of technology transformation, by constructing their own data warehouse to store and monitor real-time data. Data-Centric Testing: Data-centric testing revolves around testing the quality of the data. Data Accuracy Testing: This type of testing ensures that the data is accurately transformed and loaded as expected. Data Completeness Testing: These tests help to verify that all the expected data is loaded in target from the source. Business Testing: This testing ensures that the data fulfills the critical business requirements. Data Transformation Testing: It is done in many cases as it cannot be achieved by writing on source SQL query and comparing the output to the target. Production Validation Testing: This type of testing is done on data that is being moved to production. From the above methods, it is obvious that with the ever changing needs of the business and similar changes in the source systems, it effectively drives continuous change in the data warehouse schema and the data being loaded. ETL testing can be performed either manually, or by using tools like Informatica, QuerySurge etc. I became interested in photo editing because I wanted to create something that I have still yet to finish. Tools and techniques such as equivalence partitioning, state transition tables, decision tables, boundary-value analysis, Path Flow testing, all-pairs testing etc. Come to an agreement on the prioritization, and update the functional requirement document and shared with the stakeholders.
On the other hand, you must keep in mind to test even the low-ranked risks so that they do not become real and cause trouble.
This helps create a product that is properly balanced in terms of quality, features, budget and schedule.
In essence, SDETs are responsible not only for writing code, but are required to test the code as well. This clearly creates a demarcation between the roles and responsibilities of SDETs and QA Engineers. SDETs, with their dual abilities in the areas of code development as well as performing tests (such as those listed) are a great fit in todays’ digital age. Based on their development experience, knowledge of technical architecture and design, and their programming skills SDETs are required to write a code to test the code written by developers.
While functional and automation testers will always be required, SDETs may prove to be the all-rounder that most organizations are looking for. When an organization is able to clearly and explicitly define the testing metrics it requires, and then is properly able to analyze them and use the analysis to fix the existing issues, it will invariably be treading on the right path towards success and growth. At a later stage, this also includes testing the product, collecting statistical data, identifying and ascertaining the root causes of the issues being faced, and planning for fixing them. These metrics will help understand the effectiveness of the product as also help measure the quality of the product. This stage requires you to document the observations, inform the team about any changes to the process, and also recommend changes that need to be made. Measuring the correct variable, analysing it correctly, and then performing the required tests will lead to creation of better products and make them more reliable and robust.
Identify your top-most, business-critical priorities, analyse the metrics against them, and then make the fixes required.
If you have a business to run, it will have risks involved, and to survive – and thrive – you will need to face and overcome these risks.
Subjecting these to intense, planned testing is what is needed to ensure the sustained differentiation. It is only obvious the kind of risks this involves – all features of all products must function seamlessly across all types of all mobile devices on all platforms at all times.
More so, in the hands of the wrong people, digital security-related records of governments can pose a big security threat.
This is helping to generate a lot of statistical data that can be utilized for creating a better standard of life. Newer and better versions of automation tools and automated products are hitting the market every day. IoT has also been identified as one of the emerging technologies in IT as noted in Gartner’s IT Hype Cycle. Having a specialized team of experienced testing professionals with experience in each of these testing domains will ensure you leverage industry best practices in Quality Assurance. However, the reason why a lot of organizations fail is the fact that they segregate testing as a single unit – a phase.
While planning the product development phases, identify the types of tests you need to execute for your product.
Thus, it is only common sense to test and confirm (read validate) the basic requirements for the creation of a product before actually starting the development process. If a comprehensive and end-to-end test plan and strategy is thought of and implemented in this phase, it will help build a stable system architecture. As a lot of code is generated in this phase that covers implementation of different features, it makes sense to test the features being developed. It is no surprise that the more a product is liked and appreciated, the better ROI an organization gets.
This includes testing for performance, usability, efficiency, security, the breaking point of the software, and many more. This quality experience is what will put your product on top of the buyers list – thus ensuring higher ROIs for yourself. With so much personal and business critical data at stake in this highly digitized world thorough, end-to-end quality testing of areas such as Application, Data, Network, and Compliance is imperative. The digital world is getting smaller with a lot of apps being used on mobile platforms, tabs, laptops – and customers, with the huge array of choices before them, naturally try to buy the products that give them the best returns for their cost.
It also means that the customers enjoyed using the product so much that they want to re-use the product and do not need to spend time again to learn the basics of the product and can quickly accomplish the desired tasks. Get in touch with us if you are looking to test Non-Functional Aspects of your business applications and we will be glad to do a free assessment for you. They have the inherent need to question things, are persistent in their questioning, and at the same time are also pessimists by nature.
Such a person also knows how to deal with anger, control negative thoughts, process constructive criticism, and deal with conflict. It is but natural in our professional lives as testers to face and undergo a wide range of similar emotions. The test results so achieved may lead to any of the regular emotions that we face, such as amusement, anger, frustration, etc.
A lot of times, it is upon the shoulders of testers to inform about build failures, and also to inform if the code is not written per the best standards. These heated reactions, per EI terminology, are a result of letting the “amygdala hijack” take control.
It usually is what makes us burst out emotionally much before we have really thought through. This genuinely helps create an amicable and friendly atmosphere in any organization – more so where DevOps culture is the need of the hour.
For example, a person having such EI levels will always try to give inputs when alone, or in a mail where no one else is Cc’d.
While trading platforms include the software through which investors and traders can open, close, and manage market positions, trading applications are usually multi-product and cater to multi user options and consist of end-to-end functionality that processes numerous volumes of traffic at extreme speeds. With the activity of traders and money managers around the invention of new strategies, and new methods of electronic price discovery, this paves way for continuous increase in the volume of trades and management of huge amounts of market data.
Moreover, as business opportunities continue to change in today’s rapidly evolving marketplace, the result is an increase in data flow and processing loads. In addition, stock markets have inherent complexity in terms of business flows and business rules and testing forms a critical role to ensure effective business delivery. These testing types play an important role as they evaluate the speed, functionality, security and overall trading system performance. This type of testing evaluates simple ideas while forward performance testing, also known as paper trading, provides traders with another set of out of sample data on which to evaluate the system. Contact Gallop’s team of testing experts to know more about the testing of your trading applications. Also, with increasing business and margin pressures, the projects are required to be accomplished in lesser amount of time with fewer people, often leveraging automation.


Without metrics, it would be almost impossible to quantify, explain, or demonstrate software quality. This metrics is collected iteratively over time and measures metrics like Time to fix defects, Time to test, etc. The dimensions include validation points to evaluate application in compliance with the requirements and weigh them by business quality. The dimensions include the number of defects identified in different stages of software cycle and also the number of defects created in different stages of Software cycle.
Pareto Chart is one of the standard analysis techniques, used to identify the main types of defects that have been identified so far. Accordingly, in addition to the above metrics, our test teams use software testing metrics relevant for every stage of testing. It is important to know that independent verification and validation of data is gaining huge market potential. They have realized the need to test this data to ensure data completeness and data integrity. But, certain current strategies being followed are time-consuming, resource-intensive, and inefficient.
ETL testing plays a significant role in verifying, validating, and ensuring that the business information is exact, consistent, and reliable.
The objective of the data-centric testing is to ensure that valid and correct data is in the system. Through this testing, we can identify errors obtained due to truncation of characters, improper mapping of columns, implementation errors in logic etc.
It helps to verify the count of rows in driving table matches with the counts in the target table. In order to achieve effective business decisions, data in the production systems should have valid and correct order. However, much of the ETL testing is done by SQL scripting or eyeballing of data on spreadsheets. The experience I gained from your videos and digital image editing tutorials has been invaluable.
In the software testing arena, a risk may be defined as a potential occurrence (leading to loss) which is a result (usually undesirable) of the presence of an issue or a bug in the product.
Our tool agnostic test automation frameworks ensure accelerated testing so that you get higher productivity and an enviable time to market. They help improve the Code Quality by performing strict and detailed source code reviews along with checking for the Testability of the code. In addition, they are also required to write unit tests and also perform white box testing.
Next generation product and services industry will heavily focus around Social, Mobile, Analytics, Cloud and more importantly, Internet of Things and Virtual Reality. One can only imagine the kind of risks involved in keeping all these activities running smoothly. Just imagine what may happen if the data collected – or analyzed – is incorrect, and the same data is implemented.
When Testing is treated as just another ‘phase’, the implementation of this business-critical task suffers. Then, allocate specific time and resources for performing tests related to the different phases. This ensures that we create what we initially planned to create – and not something else that got created while on the way due to unclear and ambiguous requirements. It also is a good time to implement regression testing on the code generated so far to verify that the software being developed performs correctly even if it is modified or interfaced with other software. This is the time when you can implement tests related to product usage analytics, Real User Monitoring, & Automated smoke tests. They need tools that run the fastest, consume the least data charges or electricity, and are capable of working on any platform, OS, or device – all the while providing all the features seamlessly.
Their basic mind set is that unless they criticize, the quality of the product will not be improved.
Elacts as a tool that guides us how to identify and respond to these (- especially the negative) emotions in the best possible manner that is not counter-productive. On the other hand, when an already overloaded testing team is told that it’s time or resource size is being halved – it leads to further frustration and creates an atmosphere of animosity. This leads to a huge network traffic from various orders being placed and definitely creates an exponential growth rate for market data. Testing of the trading applications involves smoke tests and unit test cases need to be created for each functionality.
This translates into developers and testers leveraging every opportunity to effectively manage the quality of their product or bear the risk of releasing software that fails the user expectations.
Good software testing metrics are specifically important as they encapsulate metrics that measure effectiveness and help gauge the progress, quality, and health of a software testing effort. Metrics also provide a quick insight into the status of software testing efforts, hence resulting in better control through smart decision making. This ensures there are regular checkpoints which monitor, observe and measure the progress vs expected progress. Many organizations and companies are now thinking of implementing ETL and Data warehouse processes as they realize that valid data in production is critical for correct business decision making.
Thus, a well-planned, well defined and effective ETL testing scope guarantees smooth conversion of the project to the final production phase. ETL Testing is data centric testing, which involves comparing large volumes of data across heterogeneous data sources. It ensures that proper ETL processes are applied on source database and transform and load data in the target database.
This test also checks whether data has been moved, copied, or loaded completely and accurately.
ETL and Data Warehouse testing should be followed by impact-analysis and should focus on strong alignment between development, operations, and the business teams. The usage of automated testing tools ensures that only trusted data will be delivered in your production system. Organizations try to club all sorts of tests and try to test their product for all possible areas at the fag-end of the development cycle. This also helps verifying and validating the product, as also drastically reduces the number of bugs that may otherwise be found later.
The output of this phase is a Requirement Specification document that acts as the guideline for the product development. Based on the results of these tests, and the other issues reported, the development team will make the final changes before the final deployment of the product. Typically, trading systems employ a set of complex rules within their matching engines in an attempt to perfectly match and handle buying and selling options on top of handling cancel and replace requests. All these various reasons have led to the emergence of the need for testing trading systems and makes testing inevitable for these trading segments. There is a high importance bound around having a well-tested trading application as it will not fail in real time and gives an edge for client’s options and purchases. For testing the complexity of multiple, real-time order transactions, a smoke test should be implemented. Thus, positive results and good performance can be obtained with effective testing performed on trading systems. Moreover, carefully defined metrics can aid in improving enterprises or organization’s testing process and helps track its status from time to time.
Traditional Software testing metrics dealt with the ones’ based on defects that were used to measure the team’s effectiveness. We ensure software testing metrics measure process output and are linked to your business strategy and corporate goals. This data centric testing helps in achieving high quality data by getting the erroneous processes fixed quickly and effectively. The types of testing that can be achieved with ETL tools include unit, functional, regression, continuous integration, operational monitoring and more.
SDETs usually are professionals who have very strong analytical, technical, and problem solving skills. This naturally is impacted by the looming deadlines of the product launch, as also other pressures due to which the testing is not fool-proof. Performing tests specific to a phase helps save a lot of time and efforts of the developers as the issues found are far easier to fix. Regression testing must also be taken up on a continual basis so as to ensure that the existing functionalities are not affected when a new functionality is introduced into the trading system. Today, it has also become important for test vendors to share metrics that exemplify productivity, efficiency, and effectiveness in conjunction with the business benefits of software projects.
It usually revolved around the number of defects that got leaked to production named as Defect Leakage or the Defects that were missed during a release, reflects the team’s ability and product knowledge.
Coming to the benefits, you can reduce testing time by about 50% to 90% and also reduce resource utilization.
Interface testing is one of the key tests conducted in order to ensure the quality of software products. In trading applications, interface testing focuses on the data accuracy needs of the system and functioning of the interfaces as the test environment should be similar to that of the real time scenario.
These metrics can also be captured at an individual level, but generally are measured at a team level. The two documents that will be used by an ETL tester are ETL mapping sheets and the DB Schema of source and target. Testing needs to be performed around the network and interfaces as the loss incurred by stock exchanges due to data leakage could be huge. Security testing includes threat analysis and vulnerability analysis and threats are identified through security code reviews. Performance testing involves testing of the main trading application, its subsystems and the interfaces connecting these subsystems.



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