Month: July 2022

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Community Tips

Understanding developer personalities

developer personalities

Personality theories provide a blueprint for understanding why people behave the way they do. In the latest edition of our State of the Developer Nation 22nd Edition – Q1 2022, we incorporated a measure of the widely accepted ‘Big Five’ personality dimensions. We did this in order to better understand the personality traits of software developers. Here, we share some of our findings on developer personalities. Our aim is to discuss how this kind of information can help to support interactions with developers.

Personality measures are a powerful tool for understanding people’s preferences and behaviours. Software teams need diversity not only in terms of skills, experience, and knowledge, but also require a variety of personalities. This will help teams collaborate effectively on complex and challenging projects.

The Ten-Item Personality Inventory

We used the Ten-Item Personality Inventory (TIPI) methodology in order to measure the ‘Big Five’ personality dimensions. These dimensions are: emotional stability, extraversion, openness to experiences, agreeableness, and conscientiousness. The TIPI method is well-suited for situations where short measures are required. The results have been shown to have good alignment with other widely used Big Five measures1. Although more comprehensive and accurate personality measures than TIPI exist, they typically require an entire survey to themselves.

The TIPI method presents respondents with ten pairs of personality traits and asks them to rate how strongly these traits apply to them. Below, we show responses to these items for over 12,000 developers. We find that developers, in general, see themselves as complex and open to new experiences (86% agree or strongly agree that this applies to them), dependable and self-disciplined (79%), calm and emotionally stable (76%), and sympathetic and warm (74%). 

Developer personalities - developers are most likely to agree that they are dependable, self-disciplined, and open to new experiences

Diving deeper into the TIPI data allows us to identify more specific personality types within the general developer population. We collapsed these ten items into five distinct measures, one for each of the Big Five personality dimensions. For example, statements about being ‘sympathetic, warm’ and ‘critical, quarrelsome’ combine to give an overall measure of agreeableness. We then derived a score for each developer on each of the five dimensions. This helped us identify the developer personalities at the polar ends of each dimension, e.g. labelling those who are at the top end of the agreeableness scale as ‘agreeable’ and those at the bottom end as ‘disagreeable’. 

Finally, we segmented all developers into a set of distinct personality types. We did this by using the personality labels that they had been assigned as inputs to our segmentation algorithms.

Approximately 8% of all developers differ from the aforementioned group. They showcase a higher level of openness to experiences – often related to intellectual curiosity. These software developers have personality traits that suggest they are likely to investigate new tools and technologies. They are also more likely to stay up to date with the cutting edge of technology.

The Five Developer Personalities

The following charts show the characteristics of five example developer personalities revealed within our data. A well-rounded, ‘balanced’ personality type accounts for 52% of the developer population. These are developers who sit firmly at the centre of each dimension. They are neither introverted nor extroverted, highly agreeable nor disagreeable, emotionally unstable nor lacking emotion, etc.

5% of developers fit a ‘responsible and cooperative’ personality type. These developers score highly in conscientiousness, openness to experiences, and agreeableness in comparison to the majority of developers. Increased conscientiousness often relates to setting long-term goals and planning routes to achieve them, e.g being career-driven. Higher scores for openness to experiences reflects a preference for creativity and flexibility rather than repetition and routine. Our data backs this up. These developers are more receptive to personal development-related vendor resources. For example, 35% engage with seminars, training courses, and workshops compared to 25% of ‘balanced’ developers. Their high scores for agreeableness also correlate with greater engagement with community offerings. For example 23% attend meetup events compared with 17% of ‘balanced’ developers.

5% of developers conform to an ‘achievement-driven and emotionally stable’ profile. As with the previous personality type, they are conscientious and open to experiences. However, they score much higher in terms of emotional stability but slightly lower in terms of agreeableness. Developers who score high in emotional stability react less emotionally. For example they favour data over opinions. Lower agreeableness can be a useful trait for making objective decisions, free from the obligation of pleasing others.

We also find a segment of developers with an ‘introverted and unreliable’ profile. They indicate that they are less involved in social activities, disorganised, closed to new experiences, and less agreeable than other developers. Fortunately, these developers, who are likely hard to reach and engage in new activities and communities, are a very small minority, at 2% of all developers.

Common developer personality profiles
Common developer personality profiles

Developer Personalities, Roles and Content Preferences

Finally, we show how the characteristics of these developer personalities vary, in terms of both associations with developer roles and the kinds of information and content that they consume. Developers in the ‘balanced’ profile are most likely to have ‘programmer/ developer’ job titles. However, those who fit the ‘responsible and cooperative’ profile are disproportionately more likely to occupy creative (e.g UX designer) roles. This aligns with their increased creativity/openness, and senior CIO/CTO/IT manager positions, reflecting their self-discipline and achievement striving.

Those who are ‘achievement-driven and emotionally stable’ are less likely than other personality types to have ‘programmer/developer’ job titles, but disproportionately more likely to be data scientists, machine learning (ML) developers, or data engineers. They tend to deal mainly in facts and data rather than opinions and emotions. Those in the ‘introverted and unreliable’ profile are more likely to have test/QA engineer and system administrator job titles than those in other personality types. 

Developer personalities - achievement-driven developers with high emotional stability are 50% more likely to be data scientists than those with a balanced personality

When it comes to where developers go to find information and stay up to date, perhaps unsurprisingly, the ‘introverted and unreliable’ personality type uses the fewest information sources overall, affirming that they are a difficult group to engage via community-focussed events and groups. However, their use of social media is in line with other personality types, suggesting that this may be a suitable channel for catching the attention of this hard-to-reach group.

Both of the high-conscientiousness and high-openness personality types use the widest range of information sources overall, however, those who are more cooperative are considerably more likely to turn to social media for information about software development (53% of the ‘responsible and cooperative’ type vs. 44% of the ‘achievement-driven and emotionally stable’ type).

‘Intellectually curious’ developers are the most likely to make use of official vendor resources and open source communities. Hence, the audience that vendors reach via these resources may be slightly more keen to experience new products and offerings, than the typical ‘balanced’ developer.

What’s Next with Developer Personalities

We just began to scratch the surface of developers’ personality profiles. The personality types we have shown are indicative of just a few of the differences that exist among developers. By capturing this kind of data, we’ve opened the door for more extensive profiling and persona building, along with a deeper analysis of how the many other developer behaviours and preferences that we track align with personality traits. If you’re interested in learning more about developer personalities and how this can help you to reach out to developers, then we’re very excited to see how our data can support you.

Developer personalities - Achievement-driven developers use more information sources than those with a balanced personality
Categories
Analysis

Are Low/No-Code tools living up to their disruptive promise?

Low/No-Code tools

You may be wondering why software development is a slow and expensive exercise. Its complexity and the need for technical resources may be hard to find or very expensive to hire. Due to this, low/no-code tools have become increasingly popular among developers today. In this article, we explore low/no-code development, the advantages/disadvantages, and try to understand if it is disrupting the software industry today with data-driven facts.

What is low/no-code tools software?

Low/no-code tools are visual software development platforms. Unlike traditional software development, which involves programmers writing lines of code, the low-code/no-code platforms encapsulate all this behind the tool.

As per the State of the Developer Nation 22nd Edition – Q1 2022 report,  46% of professional developers use low/no-code tools for some portion of their development work.

The difference between Low-code and No-code development platforms

Before we proceed further, hope you know the difference between low-code and no-code software.

Low-code platforms require technical knowledge and it helps the developers to code faster. The main benefit is that these platforms have powerful tools that speed up technical software development activities and are built for coders. 

No-code platforms are built for standard business users. There are no options for manually editing code and rather focus on the user experience aspect in creating functionality and abstracting the technical details away from the user. 

Despite some level of automation in low-code platforms, coding is still core to the development process. Openness is a key difference between low-code platforms and no-code ones. As a developer, you can modify existing code or add new ones to change the application. The ability to add code provides flexibility with more use cases and customization possibilities. However, it limits backward compatibility.

Any new version changes to the low-code platform may affect custom code developed and may need a proper review before an upgrade. That means whenever there is a launch of a new version of the low-code platform, customers will need to test if their customized code functionality works well after the upgrade. 

In the case of no-code versions, customers do not have to worry about any functionality or breaking changes due to the platform being a closed system.

Low-code platforms offer easy integration capabilities. Unlike No-code which can lead to users creating programs without proper scrutiny with risks like security concerns, integration, and regulatory challenges besides increasing technical debt.

How do you use low/no-code tools and software?

As a user, you visually select and connect reusable components representing the steps in a process. You then link them to create the desired workflow. The code is very much present behind the steps, which drives the functionality.

Low-code/no-code tools enable non-technical staff at workplaces or anyone to develop business workflow applications. Moreover, low-code/no-code platforms allow easy integration with other business applications. For example, a sales staff could use a low-code/no-code application to develop qualified leads or opportunities into a database. They could then set triggers to send out targeted communications based on the occurrence of specified events.

Advantages and disadvantages of low code/no-code software.

Low-code/no-code platforms have both advantages and disadvantages. Here are some of them.

Lower costs & faster development: Time is money, and you can reduce your costs when you create more applications faster that automate and help improve productivity. You save costs on recruiting additional developers as applications that took a few months can be completed in a few days leading to faster availability of business applications.

Integration feasibility & challenges: Today’s application programming interfaces, or APIs, enable a high level of integration between applications. Integration works seamlessly in many cases. However, when we look at scalability and speed, custom integration is preferred for critical enterprise business applications.

Creating APIs is not easy and requires a better understanding of the IT landscape and related applications. Hence creating significant and sizeable applications will require experienced developers rather than non-technical hands-on low code/no-code software.

Time to market gains: As low code/no-code software replaces conventional hard coding with drag and drop functionality, reusable components, ready-to-use templates, and minimal coding, organizations can deliver applications faster to the market. It, therefore, helps organizations gain a competitive edge and improve productivity.

Performance: The standard view on low code/no-code software is that it focuses on saving time and is effective and successful. However, low code/no-code software platforms are not designed for performance and limit the number of functions one can implement. Moreover, adding new features to an application built using low code/no-code software can get challenging.

Privacy and Security Issues: With low-code/no-code software, there are limitations to configuring data protection and privacy aspects. You do not have access to all the source code, making it challenging to detect any security gaps.

The future of software development

Low-code/no-code software platforms offer many advantages in creating business applications faster. There are some disadvantages to its limitations in coding functions and features. What is the ground situation today with low-code/no-code software platforms?

The State of the Developer Nation 22nd Edition – Q1 2022 report has some interesting insights on the actual usage of low-code/no-code software platforms. Here are some findings:

Who is using low-code/no-code tools?

  • 46% of professional developers use low-code/no-code (LCNC) tools for some portion of their development work.
  • Experienced developers, particularly those with more than ten years of experience, are the least likely to use LCNC tools.
  • Most developers that use LCNC tools do so for less than a quarter of their development work.
  • The Greater China area has the highest LCNC tool adoption rate. 69% of developers in this region report using LCNC tools, compared to the global average of 46%.
  • 19% of developers in North America use LCNC products for more than half of their coding work – almost twice the global average of 10%. This provides strong evidence that these tools can supplant traditional development approaches

Wrapping up

Low-code/No-code tools have great potential and disrupt the traditional software industry but at a slower rate. State of the Developer Nation 22nd Edition – Q1 2022 report shows us fascinating insights.

Experienced developers with ten or more years of experience are less likely to use low-code/no-code tools. It could probably be due to the flexibility that coding offers the experienced developers and their comfort with it. It may also have an angle related to the job security of software developers and the risks of automated LCNC tools taking away significant parts of programming activity. Experienced developers work on complex tasks and the low-code tools are more suited for simple programming tasks, which the experienced hands may find easy to do.

On the other hand, North American developers seem to be progressive in using LCNC products for half of their coding (twice the global average of 10%), showing massive potential for LCNC tools to supplement software development activities. A lot of initiative in using LCNC tools also rests with the software organizations leading initiatives and implementing these solutions. Younger developers may find it easier to automate some parts of coding using LCNC tools and speed up their development activities. 

The adapted LCNC approach each programmer takes to code and develop a feature can come from their learning experience. A younger developer may prefer to use LCNC for about 25% of their development work as they are familiar with using the tools and it is a way of working. An experienced developer may shun the tools as he has always been building applications from scratch by coding and no LCNC tools. 

As technology advances, and pressure to have business solutions quicker build up, organizations will need to use the latest LCNC tools. Developing robust functional and secure software solutions faster to get competitive gains will be a mandate amid the rapid pace of digital transformation. Today LCNC tools are progressing successfully in that direction and programmers irrespective of their experience need to adapt LCNC tools where an opportunity to improve productivity exists.

Categories
Analysis

How Developers Generate Revenues

How do developers generate revenues

How businesses and developers as individuals make money from software projects is one of the most important decisions they have to make. Of all the business models and strategies available, companies and freelancers need to pick the ones that best match their market and goals. This post focuses on the popularity of revenue models among professional developers and the companies they work for.

Of all the revenue models we track in our surveys, contracted development / consulting is the most popular model. As of Q1 2022, 31% of professional developers are using this model, 7 percentage points more than the next closest revenue model – selling apps or software. Contracted development can span months or even years, allowing for developers and companies to properly plan out resources during the project. In addition, professional developers and their companies may find the clients they contract for require additional services, thus leading to additional revenue. Contracted development is tried-and-true as it’s been the most popular revenue model for the past five surveys.

Selling apps/software through an app store or their own portal is the second most popular revenue model, with almost a quarter (24%) of professional developers making money in this way. Furthermore, adoption of this model has been stable over two and a half years, despite “Epic” lawsuits against Apple and Google in 2021, which argued that these app stores had excessive fees and restrictive payment collection processes. App stores and portals are popular now, but other technologies, such as progressive web apps (PWAs), could start to impact the popularity of app stores. PWAs can work across multiple platforms, provide a native experience, and can help developers avoid high commission fees from app stores; all of which are big incentives to embrace the power of the web.

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7% of professional developers are generating revenue from selling data

Interestingly, less than a tenth (7%) of professional developers are generating revenue by selling data. Data has often been referred to as the new gold and data breaches are heavily covered in news articles as well. If data is so valuable, why are so few professional developers using this model? Regulatory measures, such as the EU’s General Data Protection Regulation (GDPR), could be hampering developers’ ability to sell user data based on the “right to be informed” principle. The California Consumer Privacy Act (CCPA) also has multiple restrictions for selling user data including an earnings cap based on a company’s total revenue. These are just a couple of examples of why selling data is difficult, which impacts its popularity as a revenue model.

Next, we will look at how the industries that developers are active in influence their revenue models. Contracted development is the most popular revenue model across all sectors, further emphasising the effectiveness of this model.

Developers active in the software products and services, data analytics, and financial services verticals tend to have the same revenue strategies. Professional developers in all three of these sectors have the same top-three revenue model choices. In addition to contracted development, app stores and selling services/APIs are the more popular methods for generating revenue in these sectors.

In-app purchases break into the top three among developers in the entertainment and media sector. 28% of professional developers in this vertical are using this method, double the percentage of the general developer population. In-app purchases are strongly associated with the freemium strategy where users are able to use/download applications for free with some features restricted to micro-purchases. This strategy has become quite popular in game development for building a base of users and incrementally generating revenue, as long as the quality of production is high. 

Contracted development is the revenue model of choice across all industry verticals

For professional developers working for companies in the marketing and advertising sectors, the advertising revenue model rises to second place, but it’s unable to unseat contracted development as the most used model. Looking across industries, there’s an apparent lack of usage of advertising as a revenue model among most other developers. On average, advertising is ranked eighth among professional developers outside of the marketing and advertising industry, being used about three times less often. Again, privacy protection may be hindering developers’ ability to use this revenue model effectively.

Finally, we evaluate revenue model usage among developers in different-sized companies. Again, contracted development remains the most popular model across every size of company. This strategy is the status quo for developers, and, with such popularity, it’s presumed to be the expectation by customers seeking professional development.

Developers working for micro-businesses are the most likely to report that they generate revenue from contracted development, with over a third (36%) of developers who work in them using this model. Professional developers in micro- businesses are also using multiple revenue models slightly more often than other developers. This indicates that companies of this size are trying to maximise their earning potential while relying heavily on the industry standard of contracted development. That being said, contracts don’t sell themselves, and micro-businesses have only 2-20 employees, so developers in these companies will likely be a close part of sales conversations.

Usage of the advertising revenue model declines as companies grow in size

Developers at large enterprises have a slightly different profile, as they tend to use the contracted development model less often than developers in other company sizes. We also see less use of the multiple revenue model, indicating that companies of this size have a more focused strategy for generating revenue.

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Tips

Git Internals Part 2: How does Git store your data?

How does Git store your data

In this article, we’ll be learning about the basics of the data storage mechanism for git. 

The most fundamental term we know regarding git and data storage is repositories. Let’s first understand what a git repository is and where it stands in terms of data storage in git.

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Repositories

A git repository can be seen as a database containing all the information needed to retain and manage the revisions and history of a project. In git, repositories are used to retain a complete copy of the entire project throughout its lifetime. 

Git maintains a set of configuration values within each repository such as the repository user’s name and email address. Unlike the file data or other repository metadata, configuration settings are not propagated from one repository to another during a clone, or fork, or any other duplication operation. Instead of this, git manages and stores configuration settings on a per-site, per-user, and per-repository basis.

Inside a git repository, there are two data structures – the object store and the index. All of this repository data is stored at the root of your working directory inside a hidden folder named .git. You can read more about what’s inside your .git folder here.

As part of the system that allows a fully distributed VCS, the object store is intended to be effectively replicated during a cloning process. The index is temporary data that is private to a repository and may be produced or edited as needed.

Let’s discuss object storage and index in further depth in the next section.

Git Object Types

Object store lies at the heart of the git’s data storage mechanism. It contains your original data files, all the log messages, author information, and other information required to rebuild any version or branch of the project.

Git places the following 4 types of objects in its object store which form the foundation of git’s higher-level data structures:

  1. blobs
  2. trees
  3. commits
  4. tags

Let’s look a bit more about these object types:

Blobs

A blob represents each version of a file. “Blob” is an abbreviation for “binary big object,” a phrase used in computers to refer to a variable or file that may contain any data and whose underlying structure is disregarded by the application.

A blob is considered opaque it contains the data of a file but no metadata or even the file’s name.

Trees

A tree object represents a single level of directory data. It saves blob IDs, pathnames, and some metadata for all files in a directory. It may also recursively reference other (sub)tree objects, allowing it to construct a whole hierarchy of files and subdirectories.

Commits

Each change made into the repository is represented by a commit object, which contains metadata such as the author, commit date, and log message. 

Each commit links to a tree object that records the state of the repository at the moment the commit was executed in a single full snapshot. The initial commit, also known as the root commit, has no parents and the following most of the commits have single parents.

A Directed Acyclic Graph is used to arrange commits. For those who missed it in Data Structures, it simply implies that commits “flow” in one way. This is usually just the trail of history for your repository, which might be very basic or rather complicated if you have branches.

Tags

A tag object gives a given object, generally a commit, an arbitrary but presumably human-readable name such as Ver-1.0-Alpha.

All of the information in the object store evolves and changes over time, monitoring and modeling your project’s updates, additions, and deletions. Git compresses and saves items in pack files, which are also stored in the object store, to make better use of disc space and network traffic.

Index

The index is a transient and dynamic binary file that describes the whole repository’s directory structure. More specifically, the index captures a version of the general structure of the project at some point in time. The state of the project might be represented by a commit and a tree at any point in its history, or it could be a future state toward which you are actively building.

One of the primary characteristics of Git is the ability to change the contents of the index in logical, well-defined phases. The indicator distinguishes between gradual development stages and committal of such improvements.

How does git monitor object history?

The Git object store is organized and implemented as a storage system with content addresses. Specifically, each item in the object store has a unique name that is generated by applying SHA1 to the object’s contents, returning a SHA1 hash value.

Because the whole contents of an object contribute to the hash value, and because the hash value is thought to be functionally unique to that specific content, the SHA1 hash is a suitable index or identifier for that item in the object database. Any little modification to a file causes the SHA1 hash to change, resulting in the new version of the file being indexed separately.

For monitoring history, Git keeps only the contents of the file, not the differences between separate files for each modification. The contents are then referenced by a 40-character SHA1 hash of the contents, which ensures that it is almost certainly unique.

The fact that the SHA1 hash algorithm always computes the same ID for identical material, regardless of where that content resides, is a significant feature. In other words, the same file content in multiple folders or even on separate machines produces the same SHA1 hash ID. As a result, a file’s SHA1 hash ID is a globally unique identifier.

Every object has an SHA, whether it’s a commit, tree, or blob, so get to know them. Fortunately, they are easily identified by the first seven characters, which are generally enough to identify the entire string.

One fantastic benefit of saving only the content is that if you have two or more copies of the same file in your repository, Git will only save one internally.

Conclusion

In this article, we learned about the two primary data structures used by git to enable data storage, management, and tracking history. We also discussed the 4 types of object types and the different roles played by them in git’s data storage mechanism. 

This was all for this article, I hope you find it helpful. These are the fundamental components of Git as we know it today and use on a regular basis. We’ll be learning more about these Git internal concepts in the upcoming articles.
Keep reading. In case you want to connect with me, follow the links below:

LinkedIn | GitHub | Twitter | Dev

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Community

From Interpreted Basic to Swift UI – Part 2

From Interpreted Basic to Swift UI

Developer Nation Community Stories

Part 2

Check out Deborah’s story as it started out here

Week of WWDC 2022 

Monday – Mapping down the journey

Apple’s WorldWide Developers Conference (WWDC) for 2022 kicked off with the Keynote (1 hour and 48 minutes) where I sat and enjoyed the presentation and did not take any notes. The Platforms State of the Union sessions (1 hour 10 minutes) was next, after an hour for lunch on the West Coast. This also is a session I watch and do not take notes. They also had the Apple Design Awards (18 minutes) and a Day 1 recap (3 minutes).

During the week, I looked over the list of sessions available each day and jotted down the ones that I was most interested in, listed by the days the videos would be available. I figured I would start with those and potentially watch others based on what I learned from the first set and how much energy I had left from the day.

Tuesday – The Swift Cookbook of Navigation 

On June 7, I was ambitiously planning on watching the following sessions, once they because available that day:

  • Build Your First App in Swift Playgrounds
  • Dive into App Intents
  • Get to Know Developer Mode
  • Implement App Shortcuts with App Intents
  • The SwiftUI Cookbook for Navigation
  • What’s New in SwiftUI

I opened a Word document and copied the transcript of each session and any code that was attached and pasted it into the document. I figured it might come in handy to look for terms, ideas, or code snippets someday. 

The first session, Build Your First App in Swift Playgrounds, was interesting, and I do not have a lot of hand-written notes about it, as it did not directly apply to my goal, to learn how to use SwiftUI to update my way-out-of-date-app. 

The second one, Dive into App Intents sounded promising and yet…it was about how to make it easier for a user to RUN your app, not how to describe what I intended it to do for me. I took lots of notes from Implement App Shortcuts with App Intents because I was determined to make them work for me somehow. 

Now, the SwiftUI Cookbook for Navigation was exactly what I needed. It talked about three-column navigation split view, and showed Recipe Categories, Recipe List, and Recipe Detail. This would work fine for me. I need to implement this! Yippee! I found what I came for! 

Now, I just needed to dig deeper and find out how to implement what they were cooking up! It talked about new container types: NavigationStack and NavigationSplitView. 

I did not watch the last session I had planned for Monday. I saved that for Tuesday morning, as the new sessions were not available when I get up early (I live on the East Coast of the United States and Apple and their timeline is based on their West Coast location) and I wanted to have something to do so I wasn’t tempted to log into my full-time job and check on some things. This was my “vacation” week after all. 

Wednesday- Design App Shortcuts & Privacy Nutrition Label

On June 8, I added to the one left-over session with the following choices:

  • Create Your Privacy Nutrition Label
  • Design App Shortcuts

Swift UI & Swift Charts 

I started with What’s New in Swift UI from Monday’s list. It was a list of sessions that talk about the details of new items in SwiftUI, such as The SwiftUI Cookbook for Navigation, which was the last session I watched the previous day, so I congratulated myself on that choice. 

The session also mentioned Swift Charts, and this was not of interest to me because I had no immediate plans to add charts to my app. It then talked about sharing, and since this is broken in my app currently, it peaked my interest until they talked about Mail, Messages, Air Drop, Notes, Add to Photos etc and  not  Facebook or Twitter, that are not not considered sharing now. The session ended with a peek at layout and how a mixed layout can be achieved with Grid, GridRow and GridColumn. 

Create your Privacy Nutrition Label

Next up was Create Your Privacy Nutrition Label. I went into this thinking there was an actual label that would need to be filled out to submit an app to the store. The areas are Data Used to Track You, Data Linked to You, Data Not Linked to You, and Data Not Collected. If the developer selects the last one, the label reads, “This developer does not collect any data from this app” and that applies to my app. So, that was all I really needed from this session.

Thursday – What’s new in Xcode

On June 9, I added just two more to my original list:

  • What’s New in AppStore Connect
  • Writing for Interfaces

I still have not watched either of those sessions. I started the day with What’s New in Xcode which gave me a list of other sessions to take a look at when I have time. Some new code was introduced and hints and tricks were shared to make coding faster by using code completion and using simple icons in a single size instead of needing all the sizes for all the different versions of pixel count now available. 

The new sessions I added to the watch list are:

  • Use XCode to Build a Multiplatform App
  • Meet Swift Package Plans
  • Create Swift Package Plugins
  • Building Global Apps: Localization by Example

Localization do or don’t?

I decided to watch the last one on that list first, Building Global Apps: Localization by Example. This sounded promising, and I was interested in how well the translation would work for my app. I thought it was  too much AI and not enough about how you will need to hire translators who would take the text you send them and return it in different languages, which you reference in code to use the localized version of the text. 

My small little app is not going to be translated. Not for this next version. 

Custom Layouts and Swift Playground 

Next, I watched the session Compose Custom Layouts with SwiftUI and learned about grids and geometry reader and the layout engine. It was way over my head, and not really relevant to what I was hoping I needed to do. I thought  starting in Swift Playgrounds is where I should turn my attention. I watched Create Engaging Content for Swift Playground only to find out that this was not relevant either since it was about how to write an app for learners.It was interesting though!

Friday  – Having a Design Lab appointment 

I had signed up for a Design Lab appointment so someone from the Apple Design department would take a look at my app currently available and make suggestions on how to improve it and bring it up-to-date. I took lots of notes on what he found when he used the app, and I have a few things to think about when re-designing the app that I hope to incorporate into the final product. Then, as I was looking around for sessions to watch, I noticed that my all-time favorite SwiftUI online instructor, Paul Hudson (@twostraws) had recorded a session at Apple Headquarters in their new developer lab podcast space so I just had to watch it. It was What’s New in SwiftUI for iOS16 and this is the session I took the most notes from and, as usual, after watching his session, I wanted to jump right in and start coding. 

Well, WWDC is over for the year. There are still sessions I would like to watch…you know, that magical time we all have called “someday”. It is time to get the app updated and into the app store before the time runs out and Apple pulls it from the App Store. That story was in part 1 and documents now I spent most of my Saturday after WWDC, all psyched up to get going with this new-found knowledge and enthusiasm for a redesigned version of my personality test app (Which 1 Are You). 

Sunday

After spending way too much time on Saturday downloading the Beta version of Xcode, making sure the app works, and then finding out I can’t submit to the App Store from Beta, and all the other pitfalls I tripped over, I was not too enthusiastic about redesigning the app. So, I reread some of my notes, and remembered that I had had a dream over night about how exactly I could do this.

 I started a new project in XCode, called TestingCode. To use as a proof of concept It has three structs, some state variables, and the body consists of a NavigationSplitView from the Cookbook session and Paul’s podcast. I thought I had understood it, and yet I cannot get it to work. And it’s back to my full-time job, too!

Coming up next : Debugging, NagivationSplitView and more

And that is where this blog ends, for now. Tune in for part 3, where I debug the issue, and learn more about this intriguing NavigationSplitView and how it actually should work. This is where the transcripts and code samples from the sessions I copied should come in handy to see what the pieces of the NavigationSplitView actually should be and how they work together.

Any comments? Suggestions? Email me at FromInterpretedBasicToSwiftUI@gmail.com.

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Tips

Tips for Choosing a Programming Language for your IT Career & Projects

Tips for choosing

Choosing a programming language can be complicated as many aspects need consideration. You might wish it was as easy as choosing between various flavors of ice cream or pizza. Ask any developer or technical manager to understand what drives popular choices in the tech world. In this article, you can learn what drives a choice of programming languages and the data-driven decisions developers should take to safeguard their careers while ensuring success in the projects they deliver.

Technology changes rapidly in today’s digital race, and the chosen language must get future potential to remain in use with strong developer communities, or else organizations can face maintenance and integration issues. Even young developers are keen to know which languages have excellent career potential, so they invest their time wisely.

Young developers may make the mistake of choosing a programming language because it’s trendy and cool. As a young developer, you can avoid these mistakes by referring to various tech forums and authentic sources like Slashdata’s – 22nd edition of The State of the Developer Nation (Q1 2022) that offer insights into popular programming languages and their growth trends.

Choosing a programming language

The choice of a programming language gets intertwined between your career aspirations and work experience. You learn a programming language and need to work on projects to gain relevant industry experience. So as a developer, you need to have a holistic approach to choosing a suitable language.

Choosing a programming language depends on various factors, and you should know all the components to get a better view and then make a choice. A good selection of programming languages will lead to spending less time on scaling, maintenance, and other aspects like security in projects.

Here are some typical questions you must ask when choosing a programming language for a project.

  • Does the programming language have proper community ecosystem support? Is it going to work over the long term? Is vendor support available?
  • What is the type of environment for the project – web solution, mobile, cross-platform, etc.?
  • Are there any infrastructure considerations like new hardware or particular deployment needs?
  • What do the clients prefer?
  • Are there any specific requirements for the programming language’s libraries, tools, or features?
  • Are experienced developers available for the programming language?
  • Are there any performance considerations, and can the language accommodate this performance?
  • Is there a security consideration or requirement for any third-party tool?

It would help if you remembered that irrespective of the chosen programming language, you can write good or bad code with any language. Besides the typical questions above, it’s advisable to consider a few critical factors in-depth before choosing a programming language. In programming, adherence to widely accepted design principles and philosophies is essential.

Some critical considerations driving the choice of a language include the following:

1. Type of application

The type of application varies from complicated embedded firmware to web and mobile. Common programming languages like Java, Python, JavaScript and C# can build different types of applications on various platforms. There are also situations where specific languages work better. With the rise in mobile apps, for example, you would choose Java for building a native Android app or a C and C++ combination for an embedded firmware project.

2. Complexity of applications

Identifying the application’s size and complexity helps determine the choice of programming language. The smaller and simple applications like marketing websites or webforms can use content management systems (CMS) like WordPress that may need minimal programing. On the other hand, complex applications like e-commerce websites or enterprise applications or emerging technology applications like IoT devices or AI-based applications may require Java or C#. As a technical manager, you can be an expert in gauging complexity with various experiences.

3. Organization culture

The choice of Open source technologies vs. proprietary software tends to rest with the organization’s culture and a direction often set by management. All programming languages have a trade-off, and some companies may choose one that is scalable, while others may pick one that has a shorter learning curve and is easy for the developers. Whatever the culture, the priority should be on choosing a language that optimally addresses the project needs. You can easily understand an organization’s choice once you start working on their technology stack.

4. Time to market:

Businesses rely on getting their product to the market early for competitive gains. Choosing new programming technologies and languages is better for a project with longer timelines. You can complete your project faster by leveraging the developers’ existing skills. For example, if you already have an AWS-based cloud environment and relevant team expertise, it will be quicker to work on it than move to another technology environment.

5. Maintainability

Technology stacks have their library ecosystems and vendor support. Choose a programming language with regular update releases that will stay current for some time. Maintaining the codebase is essential, and maintenance costs depend on the availability of developers. For example, as per today’s trends hiring Java, C#, Python, or PHP developers is easy and cost-effective. Organizations can make a data-driven decision by looking at the size of programming language communities from various industry reports from Slashdata.

6. Scalability, performance, and security:

The performance of the application depends on your choice of programming languages. It becomes essential when the development environment has limitations on scaling. Some popular tech stacks with great scalability include Ruby on Rails (RoR), .NET, Java Spring, LAMP, and MEAN.

It would be best if you protected applications from cyber threats. Following the security guidelines are crucial before choosing any programming language for your application. For example, a financial application needs PCI compliance, while healthcare-related applications need HIPAA compliance. Your choice of programming languages must be able to deliver application compliance.

Insights – Slashdata – 22nd edition of The State of the Developer Nation (Q1 2022)

You know the factors that drive the choice of programming languages. Let us look at findings from the Slashdata – 22nd edition of The State of the Developer Nation (Q1 2022). It offers exciting statistics that can help you as a developer know if your skills are up to date or need an upgrade.

JavaScript remains the most prominent language community, with close to 17.5M developers worldwide using it.

Python has remained the second most widely adopted language behind JavaScript, with the gap between the two largest communities gradually closing. Python now counts 15.7M users after adding 3.3M net new developers in the past six months alone.

The rise of data science and machine learning (ML) is an apparent factor in Python’s growing popularity. About 70% of ML developers and data scientists report using Python versus only 17% using R.

Java is one of the most critical general-purpose languages and the cornerstone of the Android app ecosystem. Although it has been around for over two decades, it is experiencing strong and steady growth. Nearly 5M developers have joined the Java community since 2021. 

Data shows that Java’s growth gets fueled by the usual suspects, i.e., backend and mobile development, and its rising adoption in AR/VR projects.

Wrapping up

We hope you have more clarity and data-driven insights in choosing programming languages for your career and projects. We encourage you to regularly read the whole SlashData – 22nd edition of The State of the Developer Nation (Q1 2022) report and stay updated on trending technologies.