Software testing is an investigation conducted to provide stakeholders with information about the quality of the software product or service under test.
I was first introduced to TDD almost 9 year ago, and I immediately fell in love with it. Nowadays it's become very popular but, unfortunately, I see that many companies don't use it. Moreover, many developers don't even know what it is exactly or how to use it, mainly beginners.
During my search for a snapshot of a persistent object, I met a feature that I would like to share as it could be useful in some special situations. My trigger was to have a before- and an after-image during unit testing.
In this series of articles, I'd like to present and discuss several possible approaches toward software development with InterSystems technologies and GitLab. I will cover such topics as:
One of the pain points for maintaining HL7 interfaces is the need to run a reliable regression test upon deployment to new environments and after upgrades. The %UnitTest class allows unit tests to be created and packaged alongside interface code. Test data can also be maintained within the unit test class, allowing for quick and easily repeatable smoke-testing and regression testing.
It is with great pleasure that the CIUSSS de l'Estrie - CHUS is sharing the mocking framework it developed and presented at the InterSystems Summit 2017. I will update this post with more detailed instructions in the next few weeks but I wanted to share the code and presentation quickly :
Allow limited durability for demo and development IRIS-Docker-micro-Durability During development of a container based demo I found the need to access a fresh docker an instance of IRIS image (e.g intersystems/iris-community:2020.2.0.199.0) over and over. To bypass loading my code repeatedly I developed this workaround.
However, few people know what technology the agency chose for storing and processing the data collected by Gaia. Two years before the launch, in 2011, the developers were considering a number of candidates (see “Astrostatistics and Data Mining” by Luis Manuel Sarro, Laurent Eyer, William O’Mullane, Joris De Ridder, pp. 111-112):
As a former JAVA developer it has always been a challenge to decide which database was the most suitable for the project we were going to develop, one of the main criteria I used was their performance, as well as their HA configuration capabilities ( high availability). Well, now is the time to put IRIS to the test with respect to some of the most commonly used databases, so I've decided to create a small Java project based on SpringBoot that connects via JDBC with a MySQL database, another of PostgreSQL and finally with IRIS.
It seems like yesterday when we did a small project in Java to test the performance of IRIS, PostgreSQL and MySQL (you can review the article we wrote back in June at the end of this article). If you remember, IRIS was superior to PostgreSQL and clearly superior to MySQL in insertions, with no big difference in queries.
I want to share with you the approach you can use working with Unit Testing which I personally find very convenient and robust.
Will not talk much here about Unit Testing, we have documentation, enough good articles on the topic not only on the Internet but here on Developers Community too, e.g. this one.
How can you manage the Unit Testing of your ZPM module?
This is pretty handy with ZPM. It has a special command "test" which runs all the tests you mentioned in the module. You can execute it as shown below:
zpm:USER>module-name test
And this command runs all the tests you mentioned in module.xml.
There are many applications for working with HL7 V2 messages, but the tools for working with XML in IRIS Management Portal and Cache Studio are limited.
Often solutions with InterSystems IRIS BI can turn into a quite big solution with dozens of pivots and dashboards.
With every new IRIS BI solution release we can add changes that could influence the behavior of existing pivots or dashboards so they stop working. For example if we change the dimension or measure name, forget deploying some cubes or subject areas, conduct refactoring via mass renaming of cubes and its elements etc some widgets could stop functioning.
In this article, I will introduce my application iris-HL7v2Gen .
IRIS-HL7v2Gen is a CSP application that facilitates the dynamic generation of HL7 test messages. This process is essential for testing, debugging, and integrating healthcare data systems. The application allows users to generate a wide variety of HL7 message types, validate their structure against HL7 specifications, explore the message hierarchy, and transmit messages over TCP/IP to production systems. These features are particularly useful in settings where compliance with HL7 standards is mandatory for interoperability between different healthcare organizations or systems.
Application Features
Dynamic HL7 Message Generation: Instantly create HL7 messages for a range of message types, facilitating comprehensive testing.
Message Structure Exploration: Visualize the structure of generated messages based on HL7 specifications.
Value Set Visualization View predefined sets of allowable coded values for specific fields.
Message Validation: Validate messages against HL7 standards to ensure compliance.
TCP/IP Communication: Easily transmit messages to production using TCP/IP settings.
Broad Message Type Support: Supports 184 different HL7 message types, ensuring versatility for various healthcare integration needs.
ClassMethod: Generate a Test Message by Invoking a Class Method
Version Support: Currently Supports HL7 Version 2.5
A few years ago, I was teaching the basics of our %UnitTest framework during Caché Foundations class (now called Developing Using InterSystems Objects and SQL). A student asked if it was possible to collect performance statistics while running unit tests. A few weeks later, I added some additional code to the %UnitTest examples to answer this question. I’m finally sharing it on the Community.
InterSystems and Intel recently conducted a series of benchmarks combining InterSystems IRIS with 2nd Generation Intel® Xeon® Scalable Processors, also known as “Cascade Lake”, and Intel® Optane™ DC Persistent Memory (DCPMM). The goals of these benchmarks are to demonstrate the performance and scalability capabilities of InterSystems IRIS with Intel’s latest server technologies in various workload settings and server configurations. Along with various benchmark results, three different use-cases of Intel DCPMM with InterSystems IRIS are provided in this report.
This is yet another short post that is intended to simplify developers' life. Now we'll talk about how to make GitHub run unit tests with every push to the repository by adding just one file to the repo. For free. On Github Cloud. Sounds great, isn't it?
It is possible and very easy to do. Credit goes to @Dmitry Maslennikov (and his repo), ZPM Package Manager, and GitHub Actions. Let's see how this all works!
Continuing on with providing some examples of various storage technologies and their performance profiles, this time we looked at the growing trend of leveraging internal commodity-based server storage, specifically the new HPE Cloudline 3150 Gen10 AMD processor-based single socket servers with two 3.2TB Samsung PM1725a NVMe drives.
IRIS Interoperability Productions formerly known as Ensemble are fun to work with. Yes, I really think my work is fun. I have seen File Passthrough Services and File Passthrough Operations come in handy. At one point we placed test messages in files, then we utilized a File Passthrough Service with Inbound File Adapter to send the contents of the file as a Stream to a File Passthrough Operation with Outbound TCP Adapter.
We recently uploaded to OpenExchange a small application that I developed a while ago (and that @Jose-Tomas Salvador improved and refined) that I often use when I need to generate large volumes of HL7 messaging.
In the main software development methodologies there is always a chapter dedicated to testing. It is a mandatory approach to achieving quality in deliveries on an ongoing basis.
In this article, I’m excited to introduce CodeInspector, a tool designed to simplify code validation by applying custom rules tailored to your development requirements. Whether you're managing a large codebase or working in an agile environment, CodeInspector helps ensure code quality by offering flexibility and adaptability to specific project needs.
At hackathons that InterSystems participated and I supported, many students were asking how all their teammates could use the same IRIS database that they spun up in a container. I suggested using ngrok to expose their localhost IRIS and realized we don't have documentation on that. Hence, I thought this would be great to let more people knwo about this powerful technique for enhancing collaboration during development and testing.
Often InterSystems technology architect team is asked about recommended storage arrays or storage technologies. To provide this information to a wider audience as reference, a new series is started to provide some of the results we have encountered with various storage technologies. As a general recommendation, all-flash storage is highly recommended with all InterSystems products to provide the lowest latency and predictable IOPS capabilities.
The first in the series was the most recently tested Netapp AFF A300 storage array. This is middle-tier type storage array with several higher models above it. This specific A300 model is capable of supporting a minimal configuration of only a few drives to hundreds of drives per HA pair, and also capable of being clustered with multiple controller pairs for tens of PB's of disk capacity and hundreds of thousands of IOPS or higher.
Sometimes we need to know for sure if the current environment has sufficient cores, memory, and bandwidth to support the planned number of users and such SLAs as latency, response time, and availability. This is true for databases and backends. This is why it is mandatory for critical applications and databases to simulate the users simultaneous/concurrent requests and collect metrics about performance and availability.
I was working on a DTL but kept getting ERROR #5002... MAXSTRING errors. The problem was that most of the DTL GUI action steps only support the string data type when working with the segments. A %String has a limit of 3,641,144 characters and my OBX5.1 was 5,242,952 characters long as the example provided. Of course PACS admin stated ultra high quality up to and including 4K resolution files were needed, so we could not get the vendor to compress or reformat these files to compressed jpg or something similar.