AI App Jobs

AI App Jobs — independent reviews, comparisons, pricing and step-by-step guides on Aizhi.

  • Open-source software security

    Open-source software security

    Open-source software security is the measure of assurance or guarantee in the freedom from danger and risk inherent to an open-source software system. == Implementation debate == === Benefits === Proprietary software forces the user to accept the level of security that the software vendor is willing to deliver and to accept the rate that patches and updates are released. It is assumed that any compiler that is used creates code that can be trusted, but it has been demonstrated by Ken Thompson that a compiler can be subverted using a compiler backdoor to create faulty executables that are unwittingly produced by a well-intentioned developer. With access to the source code for the compiler, the developer has at least the ability to discover if there is any mal-intention. Kerckhoffs' principle is based on the idea that an enemy can steal a secure military system and not be able to compromise the information. His ideas were the basis for many modern security practices, and followed that security through obscurity is a bad practice. === Drawbacks === Simply making source code available does not guarantee review. An example of this occurring is when Marcus Ranum, an expert on security system design and implementation, released his first public firewall toolkit. At one time, there were over 2,000 sites using his toolkit, but only 10 people gave him any feedback or patches. Having a large amount of eyes reviewing code can "lull a user into a false sense of security". Having many users look at source code does not guarantee that security flaws will be found and fixed. == Metrics and models == There are a variety of models and metrics to measure the security of a system. These are a few methods that can be used to measure the security of software systems. === Number of days between vulnerabilities === It is argued that a system is most vulnerable after a potential vulnerability is discovered, but before a patch is created. By measuring the number of days between the vulnerability and when the vulnerability is fixed, a basis can be determined on the security of the system. There are a few caveats to such an approach: not every vulnerability is equally bad, and fixing a lot of bugs quickly might not be better than only finding a few and taking a little bit longer to fix them, taking into account the operating system, or the effectiveness of the fix. === Poisson process === The Poisson process can be used to measure the rates at which different people find security flaws between open and closed source software. The process can be broken down by the number of volunteers Nv and paid reviewers Np. The rates at which volunteers find a flaw is measured by λv and the rate that paid reviewers find a flaw is measured by λp. The expected time that a volunteer group is expected to find a flaw is 1/(Nv λv) and the expected time that a paid group is expected to find a flaw is 1/(Np λp). === Morningstar model === By comparing a large variety of open source and closed source projects a star system could be used to analyze the security of the project similar to how Morningstar, Inc. rates mutual funds. With a large enough data set, statistics could be used to measure the overall effectiveness of one group over the other. An example of such as system is as follows: 1 Star: Many security vulnerabilities. 2 Stars: Reliability issues. 3 Stars: Follows best security practices. 4 Stars: Documented secure development process. 5 Stars: Passed independent security review. === Coverity scan === Coverity in collaboration with Stanford University has established a new baseline for open-source quality and security. The development is being completed through a contract with the Department of Homeland Security. They are utilizing innovations in automated defect detection to identify critical types of bugs found in software. The level of quality and security is measured in rungs. Rungs do not have a definitive meaning, and can change as Coverity releases new tools. Rungs are based on the progress of fixing issues found by the Coverity Analysis results and the degree of collaboration with Coverity. They start with Rung 0 and currently go up to Rung 2. Rung 0 The project has been analyzed by Coverity's Scan infrastructure, but no representatives from the open-source software have come forward for the results. Rung 1 At rung 1, there is collaboration between Coverity and the development team. The software is analyzed with a subset of the scanning features to prevent the development team from being overwhelmed. Rung 2 There are 11 projects that have been analyzed and upgraded to the status of Rung 2 by reaching zero defects in the first year of the scan. These projects include: AMANDA, ntp, OpenPAM, OpenVPN, Overdose, Perl, PHP, Postfix, Python, Samba, and Tcl.

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  • Floyd–Steinberg dithering

    Floyd–Steinberg dithering

    Floyd–Steinberg dithering is an image dithering algorithm first published in 1976 by Robert W. Floyd and Louis Steinberg. It is commonly used by image manipulation software, for example, when converting an image from a Truecolor 24-bit PNG format into a GIF format, which is restricted to a maximum of 256 colors. == Implementation == The algorithm achieves dithering using error diffusion, meaning it pushes (adds) the residual quantization error of a pixel onto its neighboring pixels, to be quantized after. It spreads the debt out according to the distribution (shown as a map of the neighboring pixels): [ ∗ 7 16 … … 3 16 5 16 1 16 … ] {\displaystyle {\begin{bmatrix}&&&{\frac {\displaystyle 7}{\displaystyle 16}}&\ldots \\\ldots &{\frac {\displaystyle 3}{\displaystyle 16}}&{\frac {\displaystyle 5}{\displaystyle 16}}&{\frac {\displaystyle 1}{\displaystyle 16}}&\ldots \\\end{bmatrix}}} The pixel indicated with a star () indicates the pixel currently being scanned, and the blank pixels are the previously scanned pixels. The specific values (7/16, 3/16, 5/16, 1/16) were originally found by trial-and-error, "guided by the desire to have a region of desired density 0.5 come out as a checkerboard pattern". The algorithm scans the image from left to right, top to bottom, quantizing pixel values one by one. Each time, the quantization error is transferred to the neighboring pixels, while not affecting the pixels that already have been quantized. Hence, if a number of pixels have been rounded downwards, it becomes more likely that the next pixel is rounded upwards, such that on average, the quantization error is close to zero. The diffusion coefficients have the property that if the original pixel values are exactly halfway in between the nearest available colors, the dithered result is a checkerboard pattern. For example, 50% grey data could be dithered as a black-and-white checkerboard pattern. For optimal dithering, the counting of quantization errors should be in sufficient accuracy to prevent rounding errors from affecting the result. For correct results, all values should be linearized first, rather than operating directly on sRGB values as is common for images stored on computers. In some implementations, the horizontal direction of scan alternates between lines; this is called "serpentine scanning" or boustrophedon transform dithering. The algorithm described above is in the following pseudocode. This works for any approximately linear encoding of pixel values, such as 8-bit integers, 16-bit integers or real numbers in the range [0, 1]. for each y from top to bottom do for each x from left to right do oldpixel := pixels[x][y] newpixel := find_closest_palette_color(oldpixel) pixels[x][y] := newpixel quant_error := oldpixel - newpixel pixels[x + 1][y ] := pixels[x + 1][y ] + quant_error × 7 / 16 pixels[x - 1][y + 1] := pixels[x - 1][y + 1] + quant_error × 3 / 16 pixels[x ][y + 1] := pixels[x ][y + 1] + quant_error × 5 / 16 pixels[x + 1][y + 1] := pixels[x + 1][y + 1] + quant_error × 1 / 16 When converting grayscale pixel values from a high to a low bit depth (e.g. 8-bit grayscale to 1-bit black-and-white), find_closest_palette_color() may perform just a simple rounding, for example: find_closest_palette_color(oldpixel) = round(oldpixel / 255) The pseudocode can result in pixel values exceeding the valid values (such as greater than 255 in 8-bit grayscale images). Such values should ideally be handled by the find_closest_palette_color() function, rather than clipping the intermediate values, since a subsequent error may bring the value back into range. However, if fixed-width integers are used, wrapping of intermediate values would cause inversion of black and white, and so should be avoided. The find_closest_palette_color() implementation is nontrivial for a palette that is not evenly distributed, however small inaccuracies in selecting the correct palette color have minimal visual impact due to error being propagated to future pixels. A nearest neighbor search in 3D is frequently used.

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  • WorkingPoint

    WorkingPoint

    WorkingPoint is a web-based application that provides a suite of small business management tools. It is designed to serve as a single point of access for various business operations, featuring a user-friendly interface. WorkingPoint's functionalities include double-entry bookkeeping, contact management, inventory management, invoicing, and bill and expense management. == Company == WorkingPoint, formerly Netbooks Inc, is a privately held corporation based in San Francisco, CA. The company is backed by CMEA Capital, also based in San Francisco. WorkingPoint has about ten employees and is led by CEO Tate Holt and Chairman Tom Proulx. Proulx is a co-founder of Intuit and an original author of that company’s Quicken personal finance software. The company was founded in 2007 under its original name Netbooks by co-creator Ridgely Evers. Evers set out to design a product that was more user-friendly than Intuit’s Quickbooks, which he also co-created. In mid-2009 the company officially rebranded itself and its flagship product “WorkingPoint”. The purpose of the re-branding was to disassociate the company from the product category of small laptops also known as netbooks. == Social Media Presence == WorkingPoint maintains a daily blog geared toward small business owners and managers. Each week the blog is updated with 3 WorkingPoint product feature or “how-to” posts, 2 subscriber company profiles, and 2 small business coaching posts. The company also maintains a Twitter page and a Facebook page. == Product Description (Free Version) == WorkingPoint allows businesses to invoice up to five customers (repeatedly) and provides account access for up to two individual users free of charge. Online Invoicing WorkingPoint allows users to create customized quotes and invoices online. The invoices can be used to bill customers via email or hardcopy post. WorkingPoint compiles the info from these invoices so users can track customer payments, inventory costs, shipping charges, accounts receivable and sales taxes. Users can also manage customer overpayments, provide customer loyalty discounts, and view a customer invoice history. Bill & Expense Management Users can track their bills and expenses by entering info into the WorkingPoint interface. WorkingPoint compiles this info so users can track categorized expenses, accounts paid, accounts payable, and vendor purchase history. The interface also allows users to add to their inventory while entering billing info. Double-Entry Bookeeping WorkingPoint automatically records entries under the double-entry bookkeeping system (also known as debits and credits) when the user completes invoicing and expense forms. Users can view transactions in general ledger format and perform closing entries if necessary. This functionality is designed for users who do not have an accounting background. Business Contact Management WorkingPoint provides an interface for users to manage their customer and vendor contact info. The software automatically tracks the user’s relationship with contacts, so users can track a contact’s sales and purchase history. Contacts can be imported and exported via numerous email clients including Microsoft Outlook, Yahoo! Mail, Google Gmail, and Mac Address Book. Inventory Management The software automatically adjusts inventory quantities after every purchase and sale. Users can track their current inventory quantity, average cost of inventory on-hand, cost of goods sold (COGS) and top-selling products. Users can also make manual adjustments to inventory when necessary. Financial Reporting Users can view a balance sheet, income statement, or cash flow statement pertaining to their business. The software automatically manages accruals to produce the balance sheet and income statement. Users can choose a data range from which to draw any of these reports. Financial reports can be converted to pdf format or exported (with formulas intact) to OpenOffice or Microsoft Excel. Cash Management WorkingPoint enables users to monitor cash balances on their bank accounts. The software automatically tracks cash inflows and outflows when users manage their accounts payable and accounts receivable. Business Dashboard The Business Dashboard visually and graphically displays key real-time business data. Users can customize the Dashboard to display data of their choosing. Online Company Profile Users can create an online company profile in order to have a presence on the Internet and as a basis for participation in WorkingPoint’s small business community features. Public profiles are featured in the WorkingPoint Company Directory and can be viewed externally using the URL format: https://businessname.workingpoint.com. == Product Description (Premium Version) == The premium version of WorkingPoint costs $10 per month. It includes all of the functionalities of the free version, allowing unlimited invoicing and account access. It also offers the following functions: 1099 Tax Reporting, invoice payment collection via PayPal, Email Marketing via VerticalResponse, and the Premium Reports & Accounting Package. 1099 Tax Reporting Users can identify qualifying companies and individuals for IRS Form 1099 or IRS Form 1096 reporting. WorkingPoint automatically tracks payments made to these companies and individuals. Users can then generate 1099 reports for distribution. Premium Reports & Accounting Package This includes: a Daily Operating Report providing users with sales and cash flow information, customizable accounts categorization, and cash flow statements using the indirect method of reporting. Invoice Payment Collection via PayPal Users can collect payment on their invoices via PayPal. Email Marketing via VerticalResponse The WorkingPoint premium package includes 500 email credits with the email marketing firm VerticalResponse.

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  • DevOps toolchain

    DevOps toolchain

    A DevOps toolchain is a set or combination of tools that aid in the delivery, development, and management of software applications throughout the systems development life cycle, as coordinated by an organization that uses DevOps practices. Generally, DevOps tools fit into one or more activities, which supports specific DevOps initiatives: Plan, Create, Verify, Package, Release, Configure, Monitor, and Version Control. == Toolchains == In software, a toolchain is the set of programming tools that is used to perform a complex software development task or to create a software product, which is typically another computer program or a set of related programs. In general, the tools forming a toolchain are executed consecutively so the output or resulting environment state of each tool becomes the input or starting environment for the next one, but the term is also used when referring to a set of related tools that are not necessarily executed consecutively. As DevOps is a set of practices that emphasizes the collaboration and communication of both software developers and other information technology (IT) professionals, while automating the process of software delivery and infrastructure changes, its implementation can include the definition of the series of tools used at various stages of the lifecycle; because DevOps is a cultural shift and collaboration between development and operations, there is no one product that can be considered a single DevOps tool. Instead a collection of tools, potentially from a variety of vendors, are used in one or more stages of the lifecycle. == Stages of DevOps == === Plan === Plan consists of two elements: "define" and "plan". This activity refers to the business value and application requirements. Specifically "Plan" activities include: Production metrics, objects and feedback Requirements Business metrics Update release metrics Release plan, timing and business case Security policy and requirement A combination of the IT personnel will be involved in these activities: business application owners, software development, software architects, continual release management, security officers and the organization responsible for managing the production of IT infrastructure. === Create === Create consists of the building, coding, and configuring of the software development process. The specific activities are: Design of the software and configuration Coding including code quality and performance Software build and build performance Release candidate Tools and vendors in this category often overlap with other categories. Because DevOps is about breaking down silos, this is reflective in the activities and product solutions. === Verify === Verify is directly associated with ensuring the quality of the software release; activities designed to ensure code quality is maintained and the highest quality is deployed to production. The main activities in this are: Acceptance testing Regression testing Security and vulnerability analysis Performance Configuration testing Solutions for verify-related activities generally fall under four main categories: Test automation, Static analysis, Test Lab, and Security. === Package === Package refers to the activities involved once the release is ready for deployment, often also referred to as staging or Preproduction / "preprod". This often includes tasks and activities such as: Approval/preapprovals Package configuration Triggered releases Release staging and holding === Release === Release related activities include schedule, orchestration, provisioning and deploying software into production and targeted environment. The specific Release activities include: Release coordination Deploying and promoting applications Fallbacks and recovery Scheduled/timed releases Solutions that cover this aspect of the toolchain include application release automation, deployment automation and release management. === Configure === Configure activities fall under the operation side of DevOps. Once software is deployed, there may be additional IT infrastructure provisioning and configuration activities required. Specific activities including: Infrastructure storage, database and network provisioning and configuring Application provision and configuration. The main types of solutions that facilitate these activities are continuous configuration automation, configuration management, and infrastructure as code tools. === Monitor === Monitoring is an important link in a DevOps toolchain. It allows IT organization to identify specific issues of specific releases and to understand the impact on end-users. A summary of Monitor related activities are: Performance of IT infrastructure End-user response and experience Production metrics and statistics Information from monitoring activities often impacts Plan activities required for changes and for new release cycles. === Version Control === Version Control is an important link in a DevOps toolchain and a component of software configuration management. Version Control is the management of changes to documents, computer programs, large web sites, and other collections of information. A summary of Version Control related activities are: Non-linear development Distributed development Compatibility with existent systems and protocols Toolkit-based design Information from Version Control often supports Release activities required for changes and for new release cycles.

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  • Affinity (software)

    Affinity (software)

    Affinity is a graphics editor developed by Serif, a subsidiary of Canva. It is simultaneously a vector graphics editor, a raster graphics editor and a desktop publishing application. It was first released in 2025 as a successor to Serif's Affinity Designer, Affinity Photo and Affinity Publisher, uniting the three editors into one application. While the previous versions competed individually against Adobe's Illustrator, Photoshop, and InDesign, Affinity 3.0 integrates their functionality into a single application. It uses a freemium model monetized by AI features exclusive to Canva Pro subscribers. == Functionality == Affinity is divided into a number of workspaces ("studios"), which are equivalent to the previous suite of Affinity applications: "vector" for vector graphics (Designer), "pixel" for raster editing (Photo), and "layout" for desktop publishing (Publisher). Additionally, it introduces the ability to create custom workspaces. The application supports real-time previews and non-destructive editing, which are based on GPU acceleration. Supported file formats include Adobe Photoshop, InDesign and Illustrator files, PDF, SVG, and TIFF, as well as a custom .af file format. === Vector editing === === Raster editing === Affinity includes photo editing tools including adjustments, masks, blend modes, batch processing, and retouching facilities. Additionally, the application can develop RAW files, similar to Adobe Lightroom. === Desktop publishing === Publishing features include master pages, text styles, and advanced typography. === AI features === The application supports Canva's existing AI features, such as background removal and generative fill. This requires a Canva subscription. == Development == === Background and acquisition (2014–2024) === Serif launched the original Affinity suite starting with Affinity Designer in 2014, followed by Photo (2015) and Publisher (2019). The software gained popularity for its one-time purchase model, contrasting with Adobe's subscription-based Creative Cloud. In November 2022, Serif released Version 2 of the suite, introducing a "Universal License" that covered all three apps across all platforms. In March 2024, Canva acquired Serif for approximately A$580 million (£300 million). Following user backlash regarding a potential shift to subscriptions, Canva and Serif issued a joint "Pledge" committing to four key principles: fair pricing, no mandatory subscriptions, perpetual licenses for existing products, and continued development of Affinity as a standalone suite. === Unified release (2025) === In September 2025, Serif pulled all existing versions of Affinity Designer, Affinity Photo and Affinity Publisher from sale ahead an upcoming announcement on 30 October; also ahead of the announcement, the iPadOS versions of the Affinity suite became free on App Store. During a "Creative Freedom" keynote on 30 October 2025, Canva released a new version now simply branded as "Affinity" (also known as "Affinity by Canva"), and referred to internally as version 3.0. Version 3 drops the separate applications and integrates their functionality into a singular application, and adds the ability to export directly to the Canva platform. It also adds a Canva AI studio, including background removal, "Expand & Edit", and generative fill. As of version 3, Affinity has switched to a freemium model; it is now available at no charge to users, although access to Canva AI features are locked behind the existing Canva Pro subscription service. Serif stated that the perpetually-licensed version 2 will remain available to existing owners, although it will no longer be actively maintained. The new version is currently available for macOS and Windows only, with an iPadOS version to be released soon. == Reception == The change in business model by Canva in 2025 was met with mixed reception, including concerns about its incorporation of AI features. Some users were concerned that their projects would be used for machine learning purposes, or that future versions would suffer from a lack of maintenance or become adware. Additionally, some felt it turned Affinity into fundamentally subscription-based software, given the prevalence of these features in professional contexts. Affinity publicly stated on social media that it would remain "free forever", users' projects would not be used to train AI models, and that "Canva has built a sustainable business model that allows this kind of generosity. And when more professionals use Affinity, Canva can sell more seats into businesses."

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  • Co-occurrence matrix

    Co-occurrence matrix

    A co-occurrence matrix or co-occurrence distribution (also referred to as : gray-level co-occurrence matrices GLCMs) is a matrix that is defined over an image to be the distribution of co-occurring pixel values (grayscale values, or colors) at a given offset. It is used as an approach to texture analysis with various applications especially in medical image analysis. == Method == Given a grey-level image I {\displaystyle I} , co-occurrence matrix computes how often pairs of pixels with a specific value and offset occur in the image. The offset, ( Δ x , Δ y ) {\displaystyle (\Delta x,\Delta y)} , is a position operator that can be applied to any pixel in the image (ignoring edge effects): for instance, ( 1 , 2 ) {\displaystyle (1,2)} could indicate "one down, two right". An image with p {\displaystyle p} different pixel values will produce a p × p {\displaystyle p\times p} co-occurrence matrix, for the given offset. The ( i , j ) th {\displaystyle (i,j)^{\text{th}}} value of the co-occurrence matrix gives the number of times in the image that the i th {\displaystyle i^{\text{th}}} and j th {\displaystyle j^{\text{th}}} pixel values occur in the relation given by the offset. For an image with p {\displaystyle p} different pixel values, the p × p {\displaystyle p\times p} co-occurrence matrix C is defined over an n × m {\displaystyle n\times m} image I {\displaystyle I} , parameterized by an offset ( Δ x , Δ y ) {\displaystyle (\Delta x,\Delta y)} , as: C Δ x , Δ y ( i , j ) = ∑ x = 1 n ∑ y = 1 m { 1 , if I ( x , y ) = i and I ( x + Δ x , y + Δ y ) = j 0 , otherwise {\displaystyle C_{\Delta x,\Delta y}(i,j)=\sum _{x=1}^{n}\sum _{y=1}^{m}{\begin{cases}1,&{\text{if }}I(x,y)=i{\text{ and }}I(x+\Delta x,y+\Delta y)=j\\0,&{\text{otherwise}}\end{cases}}} where: i {\displaystyle i} and j {\displaystyle j} are the pixel values; x {\displaystyle x} and y {\displaystyle y} are the spatial positions in the image I; the offsets ( Δ x , Δ y ) {\displaystyle (\Delta x,\Delta y)} define the spatial relation for which this matrix is calculated; and I ( x , y ) {\displaystyle I(x,y)} indicates the pixel value at pixel ( x , y ) {\displaystyle (x,y)} . The 'value' of the image originally referred to the grayscale value of the specified pixel, but could be anything, from a binary on/off value to 32-bit color and beyond. (Note that 32-bit color will yield a 232 × 232 co-occurrence matrix!) Co-occurrence matrices can also be parameterized in terms of a distance, d {\displaystyle d} , and an angle, θ {\displaystyle \theta } , instead of an offset ( Δ x , Δ y ) {\displaystyle (\Delta x,\Delta y)} . Any matrix or pair of matrices can be used to generate a co-occurrence matrix, though their most common application has been in measuring texture in images, so the typical definition, as above, assumes that the matrix is an image. It is also possible to define the matrix across two different images. Such a matrix can then be used for color mapping. == Aliases == Co-occurrence matrices are also referred to as: GLCMs (gray-level co-occurrence matrices) GLCHs (gray-level co-occurrence histograms) spatial dependence matrices == Application to image analysis == Whether considering the intensity or grayscale values of the image or various dimensions of color, the co-occurrence matrix can measure the texture of the image. Because co-occurrence matrices are typically large and sparse, various metrics of the matrix are often taken to get a more useful set of features. Features generated using this technique are usually called Haralick features, after Robert Haralick. Texture analysis is often concerned with detecting aspects of an image that are rotationally invariant. To approximate this, the co-occurrence matrices corresponding to the same relation, but rotated at various regular angles (e.g. 0, 45, 90, and 135 degrees), are often calculated and summed. Texture measures like the co-occurrence matrix, wavelet transforms, and model fitting have found application in medical image analysis in particular. == Other applications == Co-occurrence matrices are also used for words processing in natural language processing (NLP).

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  • GeoNetwork opensource

    GeoNetwork opensource

    The GeoNetwork opensource (GNOS) project is a free and open source (FOSS) cataloging application for spatially referenced resources. It is a catalog of location-oriented information. == Outline == It is a standardized and decentralized spatial information management environment designed to enable access to geo-referenced databases, cartographic products and related metadata from a variety of sources, enhancing the spatial information exchange and sharing between organizations and their audience, using the capacities of the internet. Using the Z39.50 protocol it both accesses remote catalogs and makes its data available to other catalog services. As of 2007, OGC Web Catalog Service are being implemented. Maps, including those derived from satellite imagery, are effective communicational tools and play an important role in the work of decision makers (e.g., sustainable development planners and humanitarian and emergency managers) in need of quick, reliable and up-to-date user-friendly cartographic products as a basis for action and to better plan and monitor their activities; GIS experts in need of exchanging consistent and updated geographical data; and spatial analysts in need of multidisciplinary data to perform preliminary geographical analysis and make reliable forecasts. == Deployment == The software has been deployed to various organizations, the first being FAO GeoNetwork and WFP VAM-SIE-GeoNetwork, both at their headquarters in Rome, Italy. Furthermore, the WHO, CGIAR, BRGM, ESA, FGDC and the Global Change Information and Research Centre (GCIRC) of China are working on GeoNetwork opensource implementations as their spatial information management capacity. It is used for several risk information systems, in particular in the Gambia. Several related tools are packaged with GeoNetwork, including GeoServer. GeoServer stores geographical data, while GeoNetwork catalogs collections of such data.

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  • RemObjects Software

    RemObjects Software

    RemObjects Software is an American software company founded in 2002 by Alessandro Federici and Marc Hoffman. It develops and offers tools and libraries for software developers on a variety of development platforms, including Embarcadero Delphi, Microsoft .NET, Mono, and Apple's Xcode. == History == RemObjects Software was founded in the summer of 2002. Its first product was RemObjects SDK 1.0 for Delphi, the company's remoting solution which is now in its 6th version. In late 2003 RemObjects expanded its product portfolio to add Data Abstract for Delphi, a multi-tier database framework built on top of the SDK. In 2004, Carlo Kok, who would eventually become Chief Compiler Architect for Oxygene, joined the company, adding the open source Pascal Script library for Delphi to the company's portfolio. Initial development began on Oxygene (which was then named Chrome) based on Carlo's experience from writing the widely used Pascal Script scripting engine. Towards the end of 2004, RemObjects SDK for .NET was released, expanding the remoting framework to its second platform. Chrome 1.0 was released in mid-2005, providing support for .NET 1.1 and .NET 2.0, which was still in beta at the time - making Chrome the first shipping language for .NET that supported features such as generics. It was followed by Chrome 1.5 when .NET 2.0 shipped in November of the same year. 2005 also saw the expansion of Data Abstract to .NET as a second platform. Data Abstract for .NET was the first RemObjects product (besides Oxygene itself) to be written in Oxygene. Hydra 3.0, was released for .NET in December 2006, bringing a paradigm shift to the product, away from a regular plugin framework, and focusing on interoperability between plugins and host applications written in either .NET or Delphi/Win32, essentially enabling the use of both managed and unmanaged code in the same project. In Summer 2007, RemObjects released Chrome 'Joyride' which added official support for .NET 3.0 and 3.5. Chrome once again was the first language to ship release level support for new .NET framework features supported by that runtime - most importantly Sequences and Queries (aka LINQ). Development continued and in May 2008 Oxygene 3.0 was released, dropping the "Chrome" moniker. Oxygene once again brought major language enhancements, including extensive support for concurrency and parallel programming as part of the language syntax. In October 2008, RemObjects Software and Embarcadero Technologies announced plans to collaborate and ship future versions of Oxygene under the Delphi Prism moniker, later changed to Embarcadero Prism. The first of these releases of Prism became available in December 2008. Over the course of 2009, RemObjects software completed the expansion of its Data Abstract and RemObjects SDK product combo to a third development platform - Xcode and Cocoa, for both Mac OS X and iPhone SDK client development. RemObjects SDK for OS X shipped in the spring of 2009, followed by Data Abstract for OS X in the fall. In 2011, Oxygene was expanded to add support for the Java platform, in addition to NET. In 2014, RemObjects introduced a C# compiler which runs as a Visual Studio 2013 plugin, that can output code for iOS, MacOS (Cocoa) and Android, in addition to .NET compatible code. In addition, an IDE called Fire was introduced for macOS which works with their C# and Oxygene compilers. Together, the compiler supporting both Oxygene and C# was rebranded as the Elements Compiler, with CE# having the Code name "Hydrogene". In February 2015, RemObjects introduced a beta version of a Swift compiler called Silver as part of its Elements effort. Silver, too, could create code that will execute on Android, the JVM, .NET platform and also create native Cocoa code. Silver added new features to the Swift language, such as exceptions and has a few differences and limitations compared to Apple's Swift. In February 2020, support for the Go programming language was introduced with RemObjects Gold, including the ability to compile Go language code for all Elements platforms, and a port of the extensive Go Base Library available to all Elements languages. In 2021, Mercury was added to the Elements compiler as the sixth language, providing a future for the Visual Basic .NET language recently deprecated by Microsoft. Mercury supports building and maintaining existing VB.NET projects, as well as using the language for new projects both on .NET and the other platforms. == Commercial products == Elements is a development toolchain that targets .NET runtime, Java/Android virtual machines, the Apple ecosystem (macOS, iOS, tvOS), WebAssembly and native and Windows/Linux/Android NDK processor-native machine code in conjunction with a runtime library that does automatic garbage collection on non-ARC environments and ARC on ARC-based environments, such as iOS and MacOS. Because Java, C#, Swift, and Oxygene all can import each other's APIs, Elements effectively functions as Java bonded together with C# bonded together with Swift bonded together with Oxygene as a confederation of languages cooperating together quite intimately. Oxygene, a unique programming language based on Object Pascal, which can import Java, C#, and Swift APIs from the runtime of the target operating system; RemObjects C#, an implementation of C# programming language, which can import Java, Swift, and Oxygene APIs from the runtime of the target operating system and which is intended as a competitor of Xamarin, but Hydrogene's C# targets JVM bytecode instead of Xamarin's C# compiling to only Common Language Infrastructure byte code and needing the accompanying Mono Common Language Runtime to be present in such JVM-centric environments as Android; Silver, a free implementation of the Swift programming language, which can import Java, C#, and Oxygene APIs from the runtime of the target operating system; Iodine, an implementation of the Java programming language. Gold, an implementation of the Go programming language. Mercury, an implementation of the Visual Basic .NET programming language. Fire an integrated development environment for macOS. Water an integrated development environment for Windows. Data Abstract Remoting SDK, a.k.a. RemObjects SDK Hydra Oxfuscator Oxidizer, an automatic translator from Java, C#, Objective-C, and Delphi to Oxygene, from Java, Objective-C, and C# to Swift, and from Java and Objective-C to C#. == Open source projects == Train is an open-source JavaScript-based tool for building and running build scripts and automation. Internet Pack for .NET is a free, open source library for building network clients and servers using TCP and higher level protocols such as HTTP or FTP, using the .NET or Mono platforms. It includes a range of ready to use protocol implementations, as well as base classes that allow the creation of custom implementations. RemObjects Script for .NET is a fully managed ECMAScript implementation for .NET and Mono. Pascal Script for Delphi is a widely used implementation of Pascal as scripting language. == Involvement of other projects == The Oxygene Compiler Oxygene is a language based on Object Pascal and designed to efficiently target the Microsoft .NET and Mono managed runtimes; it expands Object Pascal with a range of additional language features, such as Aspect Oriented Programming, Class Contracts and support for Parallelism. It integrates with the Microsoft Visual Studio and MonoDevelop IDEs.

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  • Core FTP

    Core FTP

    Core FTP LE is a freeware secure FTP client for Windows, developed by CoreFTP.com. Features include FTP, SSL/TLS, SFTP via SSH, and HTTP/HTTPS support. Secure FTP clients encrypt account information and data transferred across the internet, protecting data from being seen, or sniffed across networks. Core FTP is a traditional FTP client with local files displayed on the left, remote files on the right. Core FTP Server is a secure FTP server for Windows, developed by CoreFTP.com, starting in 2010. == Licensing == CoreFTP LE is free for personal, educational, non-profit, and business use.

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  • IRows

    IRows

    iRows was a web-based spreadsheet in beta with a GUI similar to the traditional desktop-based spreadsheet applications, such as Microsoft Excel and OpenOffice.org. It was shut down on December 31, 2006, after it was announced that its two founders had been hired by Google. iRows used Ajax and XML. It was described as an example of a Web 2.0 system. iRows supported conventional spreadsheet features functions, value formatting and charts and added web oriented spreadsheet capabilities like collaboration (multiple people using a shared spreadsheet, sending a spreadsheet as a link instead of an attachment and ability to publish spreadsheets on other web pages (e.g. blogs).

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  • JAUS Tool Set

    JAUS Tool Set

    The JAUS Tool Set (JTS) is a software engineering tool for the design of software services used in a distributed computing environment. JTS provides a graphical user interface (GUI) and supporting tools for the rapid design, documentation, and implementation of service interfaces that adhere to the Society of Automotive Engineers' standard AS5684A, the JAUS Service Interface Design Language (JSIDL). JTS is designed to support the modeling, analysis, implementation, and testing of the protocol for an entire distributed system. == Overview == The JAUS Tool Set (JTS) is a set of open source software specification and development tools accompanied by an open source software framework to develop Joint Architecture for Unmanned Systems (JAUS) designs and compliant interface implementations for simulations and control of robotic components per SAE-AS4 standards. JTS consists of the components: GUI based Service Editor: The Service Editor (referred to as the GUI in this document) provides a user friendly interface with which a system designer can specify and analyze formal specifications of Components and Services defined using the JAUS Service Interface Definition Language (JSIDL). Validator: A syntactic and semantic validator provides on-the-fly validation of specifications entered (or imported) by the user with respect to JSIDL syntax and semantics is integrated into the GUI. Specification Repository: A repository (or database) that is integrated into the GUI that allows for the storage of and encourages the reuse of existing formal specifications. C++ Code Generator: The Code Generator automatically generates C++ code that has a 1:1 mapping to the formal specifications. The generated code includes all aspects of the service, including the implementations of marshallers and unmarshallers for messages, and implementations of finite-state machines for protocol behavior that are effectively decoupled from application behavior. Document Generator: The Document Generator automatically generates documentation for sets of Service Definitions. Documents may be generated in several formats. Software Framework: The software framework implements the transport layer specification AS5669A, and provides the interfaces necessary to integrate the auto-generated C++ code with the transport layer implementation. Present transport options include UDP and TCP in wired or wireless networks, as well as serial connections. The transport layer itself is modular, and allows end-users to add additional support as needed. Wireshark Plugin: The Wireshark plugin implements a plugin to the popular network protocol analyzer called Wireshark. This plugin allows for the live capture and offline analysis of JAUS message-based communication at runtime. A built-in repository facilitates easy reuse of service interfaces and implementations traffic across the wire. The JAUS Tool Set can be downloaded from www.jaustoolset.org User documentation and community forum are also available at the site. == Release history == Following a successful Beta test, Version 1.0 of the JAUS Tool Set was released in July 2010. The initial offering focused on core areas of User Interface, HTML document generation, C++ code generation, and the software framework. The Version 1.1 update was released in October 2010. In addition to bug fixes and UI improvements, this version offered several important upgrades including enhancement to the Validator, Wireshark plug-in, and generated code. The JTS 2.0 release is scheduled for the second quarter of 2011 and further refines the Tool Set functionality: Protocol Validation: Currently, JTS provides validation for message creation, to ensure users cannot create invalid messages specifications. That capability does not currently exist for protocol definitions, but is being added. This will help ensure that users create all necessary elements of a service definition, and reduce user error. C# and Java Code Generation: Currently, JTS generates cross-platform C++ code. However, other languages including Java and C# are seeing a dramatic increase in their use in distributed systems, particularly in the development of graphical clients to embedded services. MS Word Document Generation: HTML and JSIDL output is supported, but native Office-Open-XML (OOXML) based MS Word generation has advantages in terms of output presentation, and ease of use for integration with other documents. Therefore, we plan to integrate MS Word service document generation. In addition, the development team has several additional goals that are not-yet-scheduled for a particular release window: Protocol Verification: This involves converting the JSIDL definition of a service into a PROMELA model, for validation by the SPIN model checking tool. Using PROMELA to model client and server interfaces will allow developers to formally validate JAUS services. End User Experience: We plan to conduct formal User Interface testing. This involves defining a set of tasks and use cases, asking users with various levels of JAUS experience to accomplish those tasks, and measuring performance and collecting feedback, to look for areas where the overall user experience can be improved. Improved Service Re-Use: JSIDL allows for inheritance of protocol descriptions, much like object-oriented programming languages allow child classes to re-use and extend behaviors defined by the parent class. At present, the generated code 'flattens' these state machines into a series of nested states which gives the correct interface behavior, but only if each single leaf (child) service is generated within its own component. This limits service re-use and can lead to a copy-and-paste of the same implementation across multiple components. The team is evaluating other inheritance solutions that would allow for multiple leaf (child) services to share access to a common parent, but at present the approach is sufficient to address the requirements of the JAUS Core Service Set. == Domains and application == The JAUS Tool Set is based on the JAUS Service Interface Definition Language (JSIDL), which was originally developed for application within the unmanned systems, or robotics, communities. As such, JTS has quickly gained acceptance as a tool for generation of services and interfaces compliant with the SAE AS-4 "JAUS" publications. Although usage statistics are not available, the Tool Set has been downloaded by representatives of US Army, Navy, Marines, and numerous defense contractors. It was also used in a commercial product called the JAUS Expansion Module sold by DeVivo AST, Inc. Since the JSIDL schema is independent of the data being exchanged, however, the Tool Set can be used for the design and implementation of a Service Oriented Architecture for any distributed systems environment that uses binary encoded message exchange. JSIDL is built on a two-layered architecture that separates the application layer and the transport layer, effectively decoupling the data being exchanges from the details of how that data moves from component to component. Furthermore, since the schema itself is widely generic, it's possible to define messages for any number of domains including but not limited to industrial control systems, remote monitoring and diagnostics, and web-based applications. == Licensing == JTS is released under the open source BSD license. The JSIDL Standard is available from the SAE. The Jr Middleware on which the Software Framework (Transport Layer) is based is open source under LGPL. Other packages distributed with JTS may have different licenses. == Sponsors == Development of the JAUS Tool Set was sponsored by several United States Department of Defense organizations: Office of Under Secretary of Defense for Acquisition, Technology & Logistics / Unmanned Warfare. Navy Program Executive Officer Littoral and Mine Navy Program Executive Officer Unmanned Aviation and Strike Weapons Office of Naval Research Air Force Research Lab

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  • Gollum browser

    Gollum browser

    Gollum browser is a discontinued web browser for accessing Wikipedia. Since 2017, Gollum is no longer accessible online. Gollum is designed to browse Wikipedia in an easier way than directly using the web browser. Links external to Wikipedia are opened in the user's regular browser. Gollum is opened from a regular browser and makes a window that puts the Wikipedia search bar on the toolbar. Gollum was created by Harald Hanek in 2005 using PHP and Ajax. According to one blogger, Gollum provides a way to bypass censorship of Wikipedia in China. == Languages == Though the website is available only in English and German, Gollum's GUI is available in more than 32 languages and can browse nearly 50 Wikipedia editions. === Gollum's GUI === === Browsable Wikipedia editions ===

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  • Cumulus (software)

    Cumulus (software)

    Cumulus is a digital asset management software designed for client/server system which is developed by Canto Software. The product makes use of metadata for indexing, organizing, and searching. == History == Cumulus was first released as a Macintosh application in 1992, and was named by Apple Computer as the "Most Innovative Product of 1992". Cumulus introduced search capabilities beyond those available in the Macintosh at the time, particularly relating to thumbnails. Cumulus 1.0 was a single-user product with no network capabilities. Among the main features of Cumulus 1.0, the search function automatically generated previews and contained support for the included AppleTalk – Peer-to-Peer – network. Cumulus 2.5 was available in five different languages and received the 1993 MacUser magazine Eddy award for "Best Publishing & Graphics Utility". In 1995, Canto introduced the scanner software "Cirrus" to focus on the development of Cumulus. Cumulus 3, released in 1996, introduced a server version for the first time and contained the possibility to spread files over the Internet via the "Web Publisher". Since Apple offered Cumulus 3 with its "Workgroup Server" as a bundle, Cumulus became one of the leading digital asset management systems. Cumulus 4 was the first version that was network-ready, and was available for Macintosh, Windows and UNIX operating systems allowing for cross-platform file sharing. Released in 1998, the support of Solaris was discounted later. Cumulus 5 modified the software core to use an open architecture providing an API to external systems and databases. The open architecture of Cumulus 5 also enabled a more functional bridge between Cumulus and the Internet. Cumulus 6 introduced Embedded Java Plugin (EJP) which allowed system integrators to build custom Java plug-ins in order to extend the functionality of the Cumulus client. Cumulus 6.5 marked the end of the Cumulus Single User Edition product, which was licensed to MediaDex for further development and distribution. Cumulus 7 was introduced summer of 2006. Cumulus 8 was released in June 2009, with new indexing capabilities taking advantage of multicore/multiprocessor systems, and ability to manage a wider variety of file formats. Cumulus 8.5 was released in May 2011. Support was added for multilingual metadata, sometimes referred to as "World Metadata." Cumulus Sites was updated to support metadata editing and file uploads. Cumulus 8.6 was released in July 2012, and contains an updated user interface for the administration of Cumulus Sites and additional features for web-based administration of Cumulus. Other additions include features for collaboration links, multi-language support and automated version control. Cumulus 9 was released in September 2013 and introduced a new Web Client User Interface and the Cumulus Video Cloud. The Cumulus Web Client UI was redesigned to provide users with a modern, easy-to-use interface to support and guide the user while addressing modern business needs. The Cumulus Video Cloud extends the Cumulus video handling capabilities to add conversion and global streaming. Cumulus 9 also saw the addition of upload collection links which allow external collaborators to drag and drop files directly into Cumulus without needing a Cumulus account. Cumulus 9.1 was released in May 2014 and introduced the Adobe Drive Adapter for Cumulus which allows users to browse and search digital assets in Cumulus directly from Adobe work environments such as Photoshop, InDesign, Illustrator, Premier and other Adobe applications. Cumulus 10 (Cumulus X) was released July 2015 and introduced two mobile-friendly products: the Cumulus app and Portals. The Cumulus app on iOS was designed to allow users to collaborate either on an iPhone or iPad. Portals is the read-only version of the Cumulus Web Client where users can work with assets that admins allow. Cumulus 10.1 was introduced in January 2016 and included the InDesign Client integration where users can work with Adobe InDesign while accessing their assets from Cumulus. Cumulus 10.2 was introduced in September 2016 and brought the Media Delivery Cloud using Amazon Web Services (AWS). It allows users to manage their media rendition in a single source and distribute media files globally across different channels and devices. Cumulus 10.2.3 was released in February 2017 and came with a "crop and customize photos" feature for Portals and the Web Client. == Product overview == The cataloging of the file via upload into the archive is where Cumulus transfers maximum information about the file from the metadata. For image or photo files, this is typically Exif and IPTC data. The metadata is mainly used to search the archive. The use of embargo data supports license management for copyrighted material. The managed files can be cataloged and their usage can be set. The indexing is based on a predefined taxonomy, which is governed by the internal rules of the organization or by industry standards. You can specify whether files can only be used for specific purposes or only by certain groups of people. The production management system includes version management for files. Via the publication function, the files can be distributed directly via links or e-mails. It's also possible to access from the outside via the Cumulus Portals web interface, which allows a read access to released content from the catalog. There are different variants, starting with the "Workgroup archive server" up to the "Enterprise Business Server" for large companies. Both server and client are extensible through a Java-based plug-in architecture. Since version 7.0, there is a web application based on Ajax with a separate user interface. For access to the Cumulus catalog on mobile, there has been an application for Apple devices based on iOS since 2010. == Miscellaneous == In 2015, Cumulus developer Canto established the first Canto digital asset management (DAM) event. The event is held annually in Berlin. The Henry Stewart team has been hosting DAM conferences since 2006.

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  • SQLBuddy

    SQLBuddy

    SQL Buddy is an open-source web-based application primarily coded in PHP, that allows users to control both MySQL and SQLite database through a web browser. The project was well regarded for its easy installation process and the friendly user interface it offered. The application was further praised for its cross-platform compatibility, meaning users could manage their databases on various operating systems, including Linux, Windows, and macOS. The development of SQL Buddy has stopped, with version 1.3.3 being the final release on January 18, 2011. No further releases are expected.

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  • Rapid application development

    Rapid application development

    Rapid application development (RAD), also called rapid application building (RAB), is both a general term for adaptive software development approaches, and the name for James Martin's method of rapid development. In general, RAD approaches to software development put less emphasis on planning and more emphasis on an adaptive process. Prototypes are often used in addition to or sometimes even instead of design specifications. RAD is especially well suited for (although not limited to) developing software that is driven by user interface requirements. Graphical user interface builders are often called rapid application development tools. Other approaches to rapid development include the adaptive, agile, spiral, and unified models. == History == Rapid application development was a response to plan-driven waterfall processes, developed in the 1970s and 1980s, such as the Structured Systems Analysis and Design Method (SSADM). One of the problems with these methods is that they were based on a traditional engineering model used to design and build things like bridges and buildings. Software is an inherently different kind of artifact. Software can change the process used to solve a problem. As a result, knowledge gained from the development process itself can feed back to the requirements and design of the solution. Plan-driven approaches attempt to define requirements, the solution, and the implementation plan, and have a process that discourages changes. RAD approaches, on the other hand, recognize that software development is a knowledge intensive process and provide flexible processes that help take advantage of knowledge gained during the project to improve or adapt the solution. The first such RAD alternative was developed by Barry Boehm and was known as the spiral model. Boehm and other subsequent RAD approaches emphasized developing prototypes as well as or instead of rigorous design specifications. Prototypes had several advantages over traditional specifications: Risk reduction. A prototype could test some of the most difficult potential parts of the system early on in the life-cycle. This can provide valuable information as to the feasibility of a design and can prevent the team from pursuing solutions that turn out to be too complex or time-consuming to implement. This benefit of finding problems earlier in the life-cycle rather than later was a key benefit of the RAD approach. The earlier a problem can be found the cheaper it is to address. Users are better at using and reacting than at creating specifications. In the waterfall model it was common for a user to sign off on a set of requirements but then when presented with an implemented system to suddenly realize that a given design lacked some critical features or was too complex. In general most users give much more useful feedback when they can experience a prototype of the running system rather than abstractly define what that system should be. Prototypes can be usable and can evolve into the completed product. One approach used in some RAD methods was to build the system as a series of prototypes that evolve from minimal functionality to moderately useful to the final completed system. The advantage of this besides the two advantages above was that the users could get useful business functionality much earlier in the process. Starting with the ideas of Barry Boehm and others, James Martin developed the rapid application development approach during the 1980s at IBM and finally formalized it by publishing a book in 1991, Rapid Application Development. This has resulted in some confusion over the term RAD even among IT professionals. It is important to distinguish between RAD as a general alternative to the waterfall model and RAD as the specific method created by Martin. The Martin method was tailored toward knowledge intensive and UI intensive business systems. These ideas were further developed and improved upon by RAD pioneers like James Kerr and Richard Hunter, who together wrote the seminal book on the subject, Inside RAD, which followed the journey of a RAD project manager as he drove and refined the RAD Methodology in real-time on an actual RAD project. These practitioners, and those like them, helped RAD gain popularity as an alternative to traditional systems project life cycle approaches. The RAD approach also matured during the period of peak interest in business re-engineering. The idea of business process re-engineering was to radically rethink core business processes such as sales and customer support with the new capabilities of Information Technology in mind. RAD was often an essential part of larger business re engineering programs. The rapid prototyping approach of RAD was a key tool to help users and analysts "think out of the box" about innovative ways that technology might radically reinvent a core business process. Much of James Martin's comfort with RAD stemmed from Dupont's Information Engineering division and its leader Scott Schultz and their respective relationships with John Underwood who headed up a bespoke RAD development company that pioneered many successful RAD projects in Australia and Hong Kong. Successful projects that included ANZ Bank, Lendlease, BHP, Coca-Cola Amatil, Alcan, Hong Kong Jockey Club and numerous others. Success that led to both Scott Shultz and James Martin both spending time in Australia with John Underwood to understand the methods and details of why Australia was disproportionately successful in implementing significant mission critical RAD projects. == James Martin approach == The James Martin approach to RAD divides the process into four distinct phases: Requirements planning phase – combines elements of the system planning and systems analysis phases of the systems development life cycle (SDLC). Users, managers, and IT staff members discuss and agree on business needs, project scope, constraints, and system requirements. It ends when the team agrees on the key issues and obtains management authorization to continue. User design phase – during this phase, users interact with systems analysts and develop models and prototypes that represent all system processes, inputs, and outputs. The RAD groups or subgroups typically use a combination of joint application design (JAD) techniques and CASE tools to translate user needs into working models. User design is a continuous interactive process that allows users to understand, modify, and eventually approve a working model of the system that meets their needs. Construction phase – focuses on program and application development task similar to the SDLC. In RAD, however, users continue to participate and can still suggest changes or improvements as actual screens or reports are developed. Its tasks are programming and application development, coding, unit-integration and system testing. Cutover phase – resembles the final tasks in the SDLC implementation phase, including data conversion, testing, changeover to the new system, and user training. Compared with traditional methods, the entire process is compressed. As a result, the new system is built, delivered, and placed in operation much sooner. == Advantages == In modern Information Technology environments, many systems are now built using some degree of Rapid Application Development (not necessarily the James Martin approach). In addition to Martin's method, agile methods and the Rational Unified Process are often used for RAD development. The purported advantages of RAD include: Better quality. By having users interact with evolving prototypes the business functionality from a RAD project can often be much higher than that achieved via a waterfall model. The software can be more usable and has a better chance to focus on business problems that are critical to end users rather than technical problems of interest to developers. However, this excludes other categories of what are usually known as Non-functional requirements (AKA constraints or quality attributes) including security and portability. Risk control. Although much of the literature on RAD focuses on speed and user involvement a critical feature of RAD done correctly is risk mitigation. It's worth remembering that Boehm initially characterized the spiral model as a risk based approach. A RAD approach can focus in early on the key risk factors and adjust to them based on empirical evidence collected in the early part of the process. E.g., the complexity of prototyping some of the most complex parts of the system. More projects completed on time and within budget. By focusing on the development of incremental units the chances for catastrophic failures that have dogged large waterfall projects is reduced. In the Waterfall model it was common to come to a realization after six months or more of analysis and development that required a radical rethinking of the entire system. With RAD this kind of information can be discovered and acted upon earlier in the proces

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