Appresso: Building a World-Class Data Integration Platform
Tags: Enterprise Software, Software Development, Enterprise Technology, Middleware, Data Integration

What enhancements have you added to the development phase?

Azuma:

Overall, our goals with the development phase are to empower our users to be more efficient and produce optimal code for their needs. In this release, we’ve added three major features: Script Version Comparison, Global Custom Logic , and Output Mapper Processing Data Log.

How does the Script Version Comparison feature help?

Azuma:

This allows comparison of two versions of a script to see the differences easily. We use color codes such as green for additions, orange for updates, and gray for deletions to make it easier to understand visually. This improves test efficiency by narrowing down the range to be tested, and identifying the cause when problems occur.

The larger a project is, the more rigorous the management needs to be. For example, if you move an icon slightly and save it, an updated version of the script will be generated. The developer will say, “Since I just changed the position of the icon, the content of the process has not changed, so there’s no need to test it.” But, without that evidence, the project leader has no choice but to say, “Well, since the version number has changed, you’ll need to test it just to make sure.”

If they’d had this new revision comparison feature, it would have been easy for the project leader to see that only the x and y axes of the icon had changed, and so additional testing would be unnecessary. This is one way it makes things more efficient.

How does the Global Custom Logic feature help?

Azuma:

This allows users to define a set of logic once and then use it throughout their project. Then, to make changes, you just update one instance, and all other instances are automatically updated. We had this before, but have greatly enhanced it with the latest update.

Toki:

It’s not always obvious what we should focus our development resources on. For example, our former Local Custom Logic was well received and saved our customers a lot of time. However, we knew there must be scope for making things more efficient. From this, we came up with the scheme for our Global Local Custom Logic functionality for the latest version.

How does the Output Mapper Processing Data Log feature help?

Azuma:

It basically makes it easier to find bugs and fix them quickly. Users can identify the cause when an error occurs in the Mapper and keep track of whether the configuration you set up is behaving as expected.

How about the testing phase?

Azuma:

The DSS product’s evolution over the years has reflected the input we have received directly from developers involved in large integration projects. As a company, we seek to alleviate our customers’ pain. The key is knowing what questions to ask and interpreting their issues into action points that we can undertake to produce solutions. By taking a hard look at customers’ problems, we could come up with solutions and implement them as features.

For example, our customers told us, “Thanks to DSS, our development time has been halved, but we’re still spending many hours on testing.” This helped us reorganize our development priorities for this latest update.

While testing is, of course, critical to the success of any integration project, it can be laborious and inefficient. Our aim is to save our users time while helping them find and resolve issues before deployment.

In the latest version, we introduced a testing framework. It’s not a single function, but rather is a generic term for multiple functions and guidelines that support the testing of scripts developed with DSS. You can automate testing scripts by building tests according to guidelines.

This saves the user a lot of time by sparing them from having to develop their own test methods. We’ve designed it in such a way that the content of the test and its results are reported in an easy-to-understand manner.

You can easily repeat the same test as many times as you need when adjustments are made, or you get change requests. The test results are automatically output as an Excel and can be audited.

It also has a function to check the consistency of data, which helps remove human error.

Toki:

When we talk to Java developers and want to explain how it works, we tell them it’s like JUnit. i.e. It’s a framework that collectively provides various functions supporting the creation of automatic tests and reporting functions.

Overall, our testing features automate processes that would otherwise take many hours to perform manually. This means that if you make changes, you can rerun the same test immediately to ensure quality.

Kim:

We’ve brought our years of experience with software quality assurance (QA) into these tools.