AI, or artificial intelligence, is technology that attempts to simulate human cognitive function. AI has made its way into the software development space in a number of ways. Visit the AI article list to expand your AI knowledge.
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Observability is a way for development teams in an organization to view their program state. Failing to provide developers with insight into their tools and processes could lead to unaddressed bugs and even system failures. Read about the latest observability content here
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In the past, the CI/CD pipeline was simply a place to integrate code. Developers would write their code in GitHub, pass it through the pipeline, and then deploy it. The pipeline has become a much more critical piece of the software delivery lifecycle today.
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Modern cloud-native applications, often leverage microservices, containers, APIs, infrastructure-as-code and more to enable speed in app development and deployment
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The Importance of Security Testing
With more development teams today using open-source and third-party components to build out their applications, the biggest area of concern for security teams has become the API. This is where vulnerabilities are likely to arise, as keeping on top of updating those interfaces has lagged.
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Mobile App Testing involves analyzing mobile apps for functionality, usability, visual appeal, and consistency across multiple mobile devices. It helps ensure an optimal user experience, irrespective of the device used to access the app.
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Today’s distributed software environments incorporate a variety of APIs with every interface your software touches, from mobile to microservices. Each API has to be continuously tested and verified to ensure your software functions as it should. Parasoft’s API testing platform makes quick, efficient, and intelligent work of such requirements.
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Ensure your application’s resilience, and make sure your software performs as expected under diverse operating conditions. (sponsored by Parasoft)
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DevSecOps is the DevOps community’s approach to bringing security into the development lifecycle. Businesses want to deliver software, but cannot afford to release unreliable or insecure applications— therefore security needs to be baked in much sooner than it has traditionally been.
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Securing an application is just as important as building it in the first place. As data becomes more valuable, there are more people who want to steal it and use it for their own personal gain. Making sure applications are indeed secure has always been a challenge, as hackers try to stay one step ahead of defenders.
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Secrets are essential for integrating your infrastructure with databases and SaaS services. Doppler‘s developer-first security platform empowers teams to manage, orchestrate, and govern secrets across any environment.
In 2023, there was an 18% decline in the number of open-source projects that are considered to be “actively maintained.” This is according to Sonatype’s Annual State of the Software Supply Chain Report.
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Development Managers need a different type of content than developers… They need to know what platforms, tools, trends, and issues they should be thinking about. SD Times delivers those unique topics here
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Agile software development has been around since the 1990s, but didn’t get the name until the famous meeting of 17 renowned software development thought leaders at Snowbird, Utah resulted in an Agile Manifesto. The idea behind Agile software development is to reduce time to market by enabling faster iterations of smaller segments of software.
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Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of resources, time and assets. It is the practice that truly brings the business side and IT side together as partners in creating value for the organization.
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DevOps is a methodology in the software development and IT industry. Used as a set of practices and tools, DevOps integrates and automates the work of software development and IT operations as a means for improving and shortening the systems development life cycle.
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Gravitee helps organizations manage and secure their entire API lifecycle with solutions for API design, management, security, productization, real-time observability, and more.
AI, or artificial intelligence, is technology that attempts to simulate human cognitive function. AI has made its way into the software development space in a number of ways. Visit the AI article list to expand your AI knowledge.
Learn More
Value stream management involves people in the organization to examine workflows and other processes to ensure they are deriving the maximum value from their efforts while eliminating waste — of resources, time and assets. It is the practice that truly brings the business side and IT side together as partners in creating value for the organization.
Learn More
Claude Sonnet 4.6 features improved skills in coding, computer use, long-context reasoning, agent planning, knowledge work, and design.
It is now the default model in claude.ai and Claude Cowork, has a 1M context window (beta), and is priced the same as Sonnet 4.5, at $3 per million input tokens and $15 per million output tokens.
“Performance that would have previously required reaching for an Opus-class model—including on real-world, economically valuable office tasks—is now available with Sonnet 4.6. The model also shows a major improvement in computer use skills compared to prior Sonnet models,” Anthropic wrote in a post.
Gemini 3.1 Pro is now available for developers in the Gemini API in Google AI Studio, Gemini CLI, Google Antigravity, and Android Studio. It can also be accessed in Vertex AI, Gemini Enterprise, the Gemini app, and NotebookLM.
“Building on the Gemini 3 series, 3.1 Pro represents a step forward in core reasoning. 3.1 Pro is a smarter, more capable baseline for complex problem-solving. This is reflected in our progress on rigorous benchmarks. On ARC-AGI-2, a benchmark that evaluates a model’s ability to solve entirely new logic patterns, 3.1 Pro achieved a verified score of 77.1%. This is more than double the reasoning performance of 3 Pro,” Google wrote in a post.
These new features are designed to reduce the risk of prompt injection attacks.
Lockdown Mode restricts how ChatGPT is able to interact with external systems, reducing the chance of data exfiltration from a prompt injection attack, while the new Elevated Risk labels will be displayed on certain products to inform users that interacting with a specific feature may introduce additional risk. For example, developers can grant Codex network access so that it can do things like look up documentation online, but this extra access can also be risky. For now, Elevated Risk labels will be displayed in ChatGPT, ChatGPT Atlas, and Codex.
The pre-built agents include Debugger, which uses call stacks, variable state, and diagnostic tools to work through errors; Profiler, which identifies bottlenecks and suggests optimizations; Test, which generates unit tests; and Modernize, which executes framework and dependency upgrades.
“Each preset agent is designed around a specific developer workflow and integrates with Visual Studio’s native tooling in ways that a generic assistant can’t,” Microsoft wrote in a blog post.
Agents can be accessed through the chat panel by using the agent picker or “@”.
Graphwise’s new GraphRAG offering acts as a semantic layer on top of knowledge graphs that LLMs can utilize to provide context-rich and verifiable answers.
According to the company, a typical RAG implementation flattens data into chunks, and with that approach, it can find similar words, but isn’t able to understand complex relationships, hierarchies, or logic connecting business data. On top of that, it is also usually difficult to see how an LLM came to its answer and what sources it used.
Graphwise believes that GraphRAG solves these issues by providing a pipeline where every step can be inspected and answers are backed by documents and graph entities.
It leverages several different search approaches, including retrieval from a knowledge graph, vector search in a specified vector store, and full-text search to enable keyword-driven discovery. It utilizes a knowledge-model-driven input processing approach to understand the user’s intent, allowing it to enrich concepts using the company’s taxonomy or ontology, expand queries using related entities and terms, and build a graph representation of the question.
Agentic AI security provider Checkmarx announced an integration with the AWS Kiro IDE to enable developers working in that platform to identify and deal with security issues as code is written, the company said.
The integration puts Checkmarx Developer Assist directly into Kiro, so developers don’t have to leave the IDE to analyze the code for security.
Once developers activate Developer Assist inside Kiro and it is authenticated, Checkmarx said the tool will analyze source code and dependencies in the active workspace. Further, it said the tool will automatically surface security findings in the IDE, along with contextual data that helps developers fix security issues early in the development cycle. That data can be viewed in the Checkmarx One platform, providing stakeholders with a view of project risks.
The Quest Trusted Data Management Platform unifies data modeling, data cataloging, data governance, data quality, and a data marketplace to enable organizations to deliver AI-ready data throughout their business.
“Building trusted AI-ready data and reusable data products can take up to six months, but your business can’t afford to wait, so teams skip the metadata, bypass governance workflows, and ignore data quality, and every department ends up with their own version of a data product. That results in fragmented, siloed data that isn’t trustworthy,” Quest Software explained in a video.
One of the key capabilities of the platform is the Automated Data Product Factory, which uses generative AI to create data products from natural language prompts, reducing data product design cycles, lowering delivery costs, and enabling business users to create their own data products.
anthropic, Checkmarx, Google, graphwise, Microsoft, OpenAI, Quest Software
Jenna Barron is News Editor of SD Times.
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