Thanks to those of you who joined us for our last webinar, How Yahoo! Mail Transformed Its Functional Testing + Continuous Delivery Process with Front End Developer Neil Manvar.
Over the last two years, Neil’s most important contribution to Yahoo! has been developing a modern functional testing framework that is based on open-source technologies, plays well with legacy code, supports many browsers, does not need maintenance, is readable to product managers, and makes writing a pleasure.
In his quest to build this framework, he’s also learned to navigate structural and organizational challenges; most significantly convincing upper management to require each developer to write and run tests on their code as their new standard operating procedure.
Missed the webinar or just want to hear it again? You can listen to the recording HERE, or check out the slides below.
How Yahoo! Mail Transformed Its Functional Testing and Continuous Delivery Process from Sauce Labs
Predictive analytics have proven themselves to be an invaluable resource for countless organizations in many fields. By leveraging this technology, firms can gain better insight that leads to improved decision-making and, consequently, superior results.
The most recent example of the power of predictive analytics surrounds health care. Massachusetts General Hospital now utilizes this technology to make better clinical decisions, leading to more efficient and effective patient care.
MGH is widely acknowledged as one of the nation's leading centers for health care. Frequently, patients are referred to the hospital by doctors who simply don't have the means or experience to effectively treat these individuals themselves. This means that MGH surgeons and clinicians frequently face some of the most challenging, high-risk health care challenges out there.
Speaking to HealthITAnalytics, Dr. David Ting, associate medical director for information systems at the Massachusetts General Physicians Organization, explained that the organization now applies predictive analytics technology to its Queriable Patient Interface Dossier in order to better assess individual patients' risks.
Previously, according to Ting, MGH surgeons would have limited insight into the risks involved in a given operation. They would typically work with referred patients, and therefore did not have a robust, one-on-one experience with those individuals.
"How do you know whether something's appropriate or not when this is a patient that comes to you and you have 15 minutes to go through the chart or talk to the patient?" said Ting, the news source reported. "Well, that's how we use QPID."
The doctor went on to explain that the QPID system delivers insight into the surgical risks of a particular procedure when performed on a patient with a specific set of circumstances and conditions. The system takes into account the entirety of a patient's electronic health record, delivering comprehensive predictive insight concerning the risks of the intended operation.
"The system automates those searches using national guidelines, and then it essentially shows the results in a dashboard with a red, yellow or green risk indicator for the surgeon or proceduralist to see," Ting said, according to HealthITAnalytics.
He went on to note that surgeons can then have much more informed, productive conversations with patients. Rather than relying on guesswork or general trends – for example, the average percentage of people who experience complications from an operation – doctors can offer data-based evidence that a particular procedure has a high risk for a specific patient, based on his or her unique history, and that an alternative approach may be the better option.
Not only does this help to cut down on unwise surgical procedures, but it also empowers patients to make more informed decisions in regard to their own treatment.
In order for this and other health care-related predictive analytics to yield positive results, though, hospitals and other care providers must overcome a number of hurdles. One of the most significant of these is the need to fully integrate with EHR systems. The MGH predictive analytics solution relies entirely on EHRs to accurately gauge the risk for an individual patient, as opposed to the average dangers posed by the operation. The same will likely be true of any organization's health care predictive analytics efforts.
Additionally, care providers must utilize high-quality algorithms to ensure the effectiveness of their predictive analytics systems. Without embeddable, high-performance algorithms that integrate with all relevant apps, organizations are unlikely to optimize the accuracy or usability of their predictive analytics tools. For a health care provider, such shortcomings may not only be frustrating, but actually dangerous.
Our community is made up of 150,000+ testers in 200 countries around the world, the largest of its kind, and our testers have already stretched the definition of what testing ‘in the wild’ can be, by testing countless customers’ apps on their own devices where they live, work and play.
That ‘play’ part of In-the-Wild testing is primed to take up a much larger slice of testers’ time. While we have already seen a taste of it with emerging technologies gradually being introduced into the mobile app mix, there are four major players primed to go mainstream in just a couple of short years. That means you can expect testers to be spending less time pushing buttons testing on mobile apps in their homes and offices…and more time ‘testing’ by jogging and buying socks. Here’s why.Apple Pay
Google Wallet has been out for several years now, but it is widely expected by many (including this guy) that Apple Pay will be the technology that takes mobile payments to the mainstream with its ease-of-use and multiple layers of security.
Of course, it will take more of the little banks and retailers to be on-board for Apple Pay to spread like wildfire, but Apple is banking on an ‘if you build it, they will come’ strategy, and it already seems to be working. Case in point: My little, local credit union in Massachusetts — probably 1/25th the size of a Chase or Citibank — has already previewed that it’s working with Apple to bring Apple Pay to all of its members.
This is all well for consumers, but it provides even more of an opportunity for testers — there will be plenty of retailers lined up to make sure the functionality works with their environments, along with retailers needing testers to verify that any in-app functionality is sound when consumers use Apple Pay from the comfort of their own homes. Expect a lot of testers buying socks and sandwiches (not together in the same transaction) as part of their new “testing” routine in the coming months and years.Smartwatches
While I have been in the camp of only wanting a smartwatch if it promises to produce lasers, I know that there are many out there that will be early adopters. And who can resist their stylin’ nature?
Once again, Apple in this technology category has made smartwatches sleek and sexy with a variety of styles and accompanying straps on its soon-to-be-released Apple Watch. While the $349 may be a sticker shock to many, one space that it is expected to take off in is the enterprise amongst executives and employees on the go.
And for testers, smartwatches will open up a whole new era and class of apps more pint-sized than ever…that you can bet will need lots of testing on proper screen rendering and functionality in those board meetings filled with execs.Health & Fitness Wearables
With Google and Apple taking on this realm in its smartphones, and fitness-centric trackers from Nike, Fitbit and Jawbone in the form of armbands, the health and fitness wearable market is one that has already actively had much adoption.
From a tester standpoint, testing fitness devices may be the most ‘out there’ definition of in-the-wild testing. As health and fitness apps and armbands track fitness- and health-specific information such as number of steps taken, heart rate and calories burned, expect a lot more of testers’ routines including a 2-mile jog lumped in with their mobile testing.Automobile In-dash Entertainment
From popular car manufacturers from Ford and Toyota to BMW and Audi, to navigation services like TomTom and Garmin, in-dash entertainment and navigation systems have already taken off in the past year, and that trend is only expected to continue as these packages eventually become standard in automobiles.
And this only opens up more doors for testers. We’ve all heard of texting while driving, but did law enforcement consider ‘testing’ while driving? Testing teams should consider safety first and buddy-up their testers when sending them out to drive for a “testing” assignment.
What do you think? Is the tester’s work environment going to be stretched even more into the wild in the next few years because of these emerging technologies? Are there others you would add to the list such as Google Glass? Will these technologies still just be a shadow in a tester’s daily testing routine? Let us know in the Comments now.
In my last post I introduced the async and await keywords and I showed you what the C# compiler generates from an async method. In this post we will see what the PurePath looks like when we use an async API in our code. Feel free to follow my steps by downloading the free trial […]
The post The Performance Impact of Async – Looking at the PurePath appeared first on Compuware APM Blog.
Upgrading to Mac OS X Yosemite (10.10) may impact your Seapine product installation. There are a couple of issues to be aware of:
- If you use Surround SCM PostgreSQL databases, the Surround SCM Server will not be able to connect to the databases after upgrading Mac OS X. During the upgrade, Mac OS X automatically deletes empty PostgreSQL folders that are required for the PostgreSQL server to run correctly. It’s easy to fix this issue. See this knowledgebase article.
- If you use TestTrack Web, TestTrack Web Server Admin, SoloSubmit, or Seapine License Server Web Admin, users will not be able to log in to the clients after upgrading Mac OS X on the computer hosting the TestTrack Server or Seapine License Server. Mac OS X 10.10 uses Apache 2.4 and the required mod_cgi module is not enabled by default in this version. This one is easy to fix too. See this knowledgebase article.
We haven’t seen any impact on the TestTrack or Surround SCM Clients after upgrading to Mac OS X.
If you have any questions or need help, please contact Seapine Support.Share on Technorati . del.icio.us . Digg . Reddit . Slashdot . Facebook . StumbleUpon
With BugBuster v3 we offer for free right into your account working test plans for two demo applications: a typical corporate web site built with WordPress and an e-Commerce one which is the infamous sample application of Magento.
The ecommerce application has got a test plan that contain some typical functional tests for the critical components of a merchant website such as the shopping cart, the catalogs or the user registration
Please note that these scenarios are fully functional. You can alter and augment them as much as you want or create new scenarios using the Scenario Templates and the Scenario Recorder.
The post BugBuster v3: WordPress and Magento demo applications appeared first on BugBuster.
Sauce Labs Named as One of the San Francisco Business Times’ Top 100 Fastest Growing Private Companies in the Bay Area
SAN FRANCISCO, CA – Oct 22, 2014 – Sauce Labs Inc, the leading provider of cloud-based mobile and web application functional and unit testing infrastructure solutions, today announced it has been ranked as 21 in the Top 100 Fastest-Growing Private Companies in the Bay Area by the San Francisco Business Times. The award is based on net revenue growth from fiscal years 2011-2013. Sauce Labs’ revenue grew by 378.4 percent during that time.
“We’re thrilled to be recognized by the San Francisco Business Times as one of the fastest growing private companies in the Bay Area,” said Jim Cerna, Sauce Labs’ president and chief financial officer. “This award highlights the demand for a scalable test automation platform that meets the needs of the agile web and mobile app developer community.”
Sauce Labs’ rapid growth is attributed to the need for a reliable automated testing platform that developers and QA/QE teams use to ensure their applications function properly before they go to market. “With increasing adoption of continuous integration and continuous deployment workflows, automated testing is in great demand,” said Steve Hazel, chief product officer and co-founder. “High reliability is absolutely critical to our customers so that their builds continue to run and their dev teams are not blocked by issues with infrastructure.”
To meet this demand, Sauce Labs has more than doubled its headcount in the span of one year, adding employees across all departments to aggressively scale both its teams and infrastructure in San Francisco, California, and Vancouver, Canada. Sauce Labs plans to focus on building and scaling the organization and its service offering in the coming months, including adding on-demand access to mobile real devices.
About Sauce Labs
Despite tremendous progress in recent years, contagious diseases remain a worldwide challenge. The current Ebola outbreak in western Africa is a powerful reminder of the damage that these pathogens can cause.
In an effort to combat global disease outbreaks, researchers at the University of Liverpool are working to develop the world's most comprehensive disease database, Labmate Online reported. And to achieve this goal, the scientists are turning to data mining solutions.
Data mining diseases
The source explained that the Liverpool University Climate and Infectious Diseases of Animals team aims to describe and map the connections between diseases and their hosts. All of this information will go into the group's Enhanced Infectious Diseases database, known as EID2.
To develop EID2, the researchers are applying advanced data mining techniques to the massive amount of scientific literature and relevant information already existent in disparate databases, the source explained. A significant portion of this data exists in unstructured or semistructured states, which previously made it difficult to collect and utilize in a single, coherent database. By applying big data analytics tools combined with high performance computing, though, the researchers hope to create a useful resource for anyone studying these pathogens.
According to Labmate Online, the Liverpool researchers have and will continue to utilize the data accumulated in EID2 for a variety of purposes. For example, the scientists have worked to examine the history of different human and animal diseases, tracing their spread and development over many years.
Additionally, the research will prove invaluable for predicting the impact climate change will have on numerous diseases. With this insight, researchers can create maps that reveal where certain diseases are more likely to spring up, and where they are most likely to spread.
Finally, the EID2 data can help disease researchers better understand the often-complex relationships between human and animal carriers and hosts. Improved categorization in this area could lead scientists to discover previously hidden connections between pathogens, which in turn could lead to new avenues for cures and treatments.
Data mining health care
While the EID2 project focuses on global health trends, data mining is also being applied to health-related matters on a more granular basis.
For example, Bloomberg Businessweek reported last month that the Carolinas HealthCare hospital chain uses this technology to analyze patient credit card data. By doing so, the organization is able to identify those patients who are most likely to require treatment in the near future and then take preventative steps to minimize the risk.
Michael Dulin, chief clinical officer for analytics and outcomes research at Carolinas HealthCare, told the news source that providers can gain a lot more insight into a patient's health by data mining consumer-related information than through a single appointment at the doctor's office. He stated that his organization aims to assign risk scores to patients and deliver this information to the relevant doctors and nurses. These care professionals can then decide if and when to reach out to the affected individuals to provide lifestyle recommendations or encourage a visit to the hospital if they are at risk.
As more hospitals, clinics, doctor's offices and research facilities pursue data mining strategies, it is important for decision-makers to ensure that the right tools are in place to support such efforts. For example, personnel will need access to comprehensive numerical libraries, which can provide reliable, embeddable algorithms that can be incorporated into the organization's applications easily and effectively. Without such assets, many data mining efforts will yield suboptimal results.
She was programme chair for EuroSTAR twice and is a popular speaker at international conferences. Dot has been on the boards of publications, conferences and qualifications in software testing. She was awarded the European Excellence Award in Software Testing in 1999 and the first ISTQB Excellence Award in 2012. You can visit her at her website.
In this Q&A, uTest spoke with Dot about her experiences in automation, its misconceptions, and some of her favorite stories from her most recent book which she co-authored, ‘Experiences of Test Automation: Case Studies of Software Test Automation.’ Stay tuned at the end of the interview for chapter excerpt previews of the book, along with an exclusive discount code to purchase.
uTest: Could you tell us a little more about the path that brought you to automation?
Dorothy Graham: That’s easy – by accident! My first job was at Bell Labs and I was hired as a programmer (my degrees were in Maths, there weren’t many computer courses back in the 1970s). I was put into a testing team for a system that processed signals from hydrophones, and my job was to write test execution and comparison utilities (as they were called then, not tools).
My programs were written on punched cards in Fortran, and if we were lucky, we got more than one “turn-around” a day on the Univac 1108 mainframe (when the program was run and we got the results – sometimes “didn’t compile”). Things have certainly moved on a lot since then! However, I think I may have written one of the first “shelfware” tools, as I don’t think it was used again after I left (that taught me something about usability)!
uTest: There’s a lot of misconceptions out there amongst management that automation will be a cure-all to many things, including cost-cutting within testing teams. What is the biggest myth you’d want to dispel about test automation?
DG: The biggest misconception is that automated tests are the same as manual tests – they are not! Automated tests are programs that check something – the tool only runs what it has been programmed to run, and doesn’t do any thinking. This misconception leads to many mistakes in automation — for example, trying to automate all — and only — manual tests. Not all manual tests should be automated. See Mike Baxter et al’s chapter (25) in my Experiences book for a good checklist of what to automate.
This misconception also leads to the mistaken idea that tools replace testers (they don’t, they support testers!), not realizing that testing and automating require different skillsets, and not distinguishing good objectives for automation from objectives for testing (e.g. expecting automated regression tests to find lots of bugs). I could go on…
uTest: What are you looking for in an automation candidate that you wouldn’t be looking for in a QA or software tester?
DG: If you are looking for someone to design and construct the automation framework, then software design skills are a must, since the test execution tools are software programs. However, not everyone needs to have programming skills to use automation – every tester should be able to write and run automated tests, but they may need support from someone with those technical skills. But don’t expect a developer to necessarily be good at testing – testing skills are different than development skills.
uTest: You were the first Programme Chair for EuroSTAR, one of the biggest testing events in Europe, back in 1993, and repeated this in 2009. Could you talk about what that entailed and one of the most valuable things you gained out of EuroSTAR’s testing sessions or keynotes?
DG: My two experiences of being Programme Chair for EuroSTAR were very different! SQE in the US made it possible to take the major risk of putting on the very first testing conference in Europe, by financially underwriting the BCS SIGIST (Specialist Group In Software Testing). Organizing this in the days before email and the web was definitely a challenge!
In 2009, the EuroSTAR team, based in Galway, gave tremendous support; everything was organized so well. They were great in the major planning meeting with the Programme Committee, so we could concentrate on content, and they handled everything else. The worst part was having to say no to people who had submitted good abstracts!
I have heard many excellent keynotes and sessions over the years – it’s hard to choose. There are a couple that I found very valuable though: Lee Copeland’s talk on co-dependent behavior, and Isabel Evans’ talk about the parallels with horticulture. Interesting that they were both bringing insights into testing from outside of IT.
uTest: Your recent book deals with test automation actually at work in a wide variety of organizations and projects. Could you describe one of your favorite case studies of automation gone right (or wrong) from the book, and what you learned from the experience?
DG: Ah, that’s difficult – I have many favorites! Every case study in the book is a favorite in some way, and it was great to collect and critique the stories. The “Anecdotes” chapter contains lots of smaller stories, with many interesting and diverse lessons.
The most influential case study for me, which I didn’t realize at the time, was Seretta Gamba’s story of automating “through the back door.” When she read the rest of the book, she was inspired to put together the Test Automation Patterns, which we have now developed into a wiki. We hope this will continue to disseminate good advice about automation, and we are looking for more people to contribute their experiences of automation issues or using some of the patterns.
uTest has arranged for a special discount of 35% off the purchase of ‘Experiences of Test Automation: Case Studies of Software Test Automation’ here by entering the code SWTESTING at checkout (offer expires Dec. 31, 2014).
Additionally, Dot has graciously provided the following exclusive chapter excerpts to preview:
When recruiting software testers many hiring managers often look for the impossible candidate who can do everything. These people don’t exist yet many hiring managers continue to place job adverts that seek out these candidates. What follows are 5 ways that will help you to create effective adverts for recruiting software testers When I … Read More →
The post How to create effective adverts for recruiting software testers appeared first on The Social Tester.
To read more, visit our blog at blog.sonatype.com.
The latest Testing in the Pub podcast continues the discussion on what test managers need to look out for when recruiting testers, and what testers need to do when seeking out a new role in the testing industry.
There’s a lot of practical advice in this edition served over pints at the pub — from the perfect resume/CV length (one page is too short!) to a very candid discussion on questions that are pointless when gauging whether someone is the right fit for your testing team.
Part II of the two-part podcast is available right here for download and streaming, and is also available on YouTube and iTunes. Be sure to check out the entire back catalog of the series as well, and Stephen’s recent interview with uTest.