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3 Critical Considerations for Technical Due Diligence Technical due diligence is the process of verifying a company’s technical capabilities, quality, and processes. It is typically performed by investors or buyers before a contract. There are many aspects you can investigate, but three are crucial: a code review, security evaluation, and open source components compliance. |
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Comparing Java and Ruby Java and Ruby are both open source languages, and both are ranked in the top 20 of the TIOBE index for most popular programming languages. If you want to learn a new language and are trying to decide between these two, let’s explore common differences in syntax and constructs to discover which may be more useful for you. |
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Comparing Ruby and PHP Ruby and PHP are both open source languages, and both are ranked in the top 20 of the TIOBE index for most popular programming languages. If you want to learn a new language and are trying to decide between these two, let’s explore common differences in syntax and constructs to discover which may be more useful for you. |
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2 Familiar Problems for Software Developers In the quest for writing good code and delivering the right thing to customers, developers have several challenges. But most of them can be boiled down to two main problems: discovering the real scope, and how to do the work. Interestingly, they’re very similar to the problems faced by testers and others in non-dev roles. |
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Software Features to Avoid in a Production Environment When developing an application, it’s best practice not to use certain software features in a production environment. These include features related to programming language, the OS, the database, a framework, a web or application server, or a tool. You have to consider the production setup to avoid bugs or server crashes. |
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Lessons the Software Community Must Take from the Pandemic Due to COVID-19, organizations of all types have had to implement continuity plans within an unreasonably short amount of time. These live experiments in agility have shaken up our industry, but it's also taught us a lot of invaluable lessons about digital transformation, cybersecurity, performance engineering, and more. |
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5 Pitfalls to Avoid When Developing AI Tools Developing a tool that runs on artificial intelligence is mostly about training a machine with data. But you can’t just feed it information and expect AI to wave a magic wand and produce results. The type of data sets you use and how you use them to train the tool are important. Here are five pitfalls to be wary of. |
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Choosing the Right Threat Modeling Methodology Threat modeling has transitioned from a theoretical concept into an IT security best practice. Choosing the right methodology is a combination of finding what works for your SDLC maturity and ensuring it results in the desired outputs. Let’s look at four different methodologies and assess their strengths and weaknesses. |
