Looking for the best AI code-review tool? An AI code-review tool is software that uses machine learning to help you get more done — it can save you hours every week by automating repetitive work. Most options offer a generous free tier, with paid plans unlocking higher limits, faster processing, and team features. Whether you are a beginner or a pro, the right AI code-review tool slots into your workflow and pays for itself fast. This guide breaks down the top picks, their pros and cons, and who each one is best for.
Multi-focus image fusion
Multi-focus image fusion is a multiple image compression technique using input images with different focus depths to make one output image that preserves all information. == Overview == The main idea of image fusion is gathering important and the essential information from the input images into one single image which ideally has all of the information of the input images. The research history of image fusion spans over 30 years and many scientific papers. Image fusion generally has two aspects: image fusion methods and objective evaluation metrics. In visual sensor networks (VSN), sensors are cameras which record images and video sequences. In many applications of VSN, a camera can't give a perfect illustration including all details of the scene. This is because of the limited depth of focus of the optical lens of cameras. Therefore, just the object located in the focal length of camera is focused and clear, and other parts of the image are blurred. VSN captures images with different depths of focus using several cameras. Due to the large amount of data generated by cameras compared to other sensors such as pressure and temperature sensors and some limitations of bandwidth, energy consumption and processing time, it is essential to process the local input images to decrease the amount of transmitted data. == Multi-Focus image fusion in the spatial domain == Huang and Jing have reviewed and applied several focus measurements in the spatial domain for the multi-focus image fusion process, suitable for real-time applications. They mentioned some focus measurements including variance, energy of image gradient (EOG), Tenenbaum's algorithm (Tenengrad), energy of Laplacian (EOL), sum-modified-Laplacian (SML), and spatial frequency (SF). Their experiments showed that EOL gave better results than other methods like variance and spatial frequency. == Multi-Focus image fusion in multi-scale transform and DCT domain == Image fusion based on the multi-scale transform is the most commonly used and promising technique. Laplacian pyramid transform, gradient pyramid-based transform, morphological pyramid transform and the premier ones, discrete wavelet transform, shift-invariant wavelet transform (SIDWT), and discrete cosine harmonic wavelet transform (DCHWT) are some examples of image fusion methods based on multi-scale transform. These methods are complex and have some limitations e.g. processing time and energy consumption. For example, multi-focus image fusion methods based on DWT require a lot of convolution operations, so they take more time and energy to process. Therefore, most methods in multi-scale transform are not suitable for real-time applications. Moreover, these methods are not very successful along edges, due to the wavelet transform process missing the edges of the image. They create ringing artefacts in the output image and reduce its quality. Due to the aforementioned problems in the multi-scale transform methods, researchers are interested in multi-focus image fusion in the DCT domain. DCT-based methods are more efficient in terms of transmission and archiving images coded in Joint Photographic Experts Group (JPEG) standard to the upper node in the VSN agent. A JPEG system consists of a pair of an encoder and a decoder. In the encoder, images are divided into non-overlapping 8×8 blocks, and the DCT coefficients are calculated for each. Since the quantization of DCT coefficients is a lossy process, many of the small-valued DCT coefficients are quantized to zero, which corresponds to high frequencies. DCT-based image fusion algorithms work better when the multi-focus image fusion methods are applied in the compressed domain. In addition, in the spatial-based methods, the input images must be decoded and then transferred to the spatial domain. After implementation of the image fusion operations, the output fused images must again be encoded. DCT domain-based methods do not require complex and time-consuming consecutive decoding and encoding operations. Therefore, the image fusion methods based on DCT domain operate with much less energy and processing time. Recently, a lot of research has been carried out in the DCT domain. DCT+Variance, DCT+Corr_Eng, DCT+EOL, and DCT+VOL are some prominent examples of DCT based methods.
Microsoft To Do
Microsoft To Do (previously styled as Microsoft To-Do) is a cloud-based task management application. It allows users to manage their tasks from a smartphone, tablet and computer. The technology is produced by the team behind Wunderlist, which was acquired by Microsoft, and the stand-alone apps feed into the existing Tasks feature of the Outlook product range. == History == Microsoft To Do was first launched as a preview with basic features in April 2017. Later more features were added including Task list sharing in June 2018. In September 2019, a major update to the app was unveiled, adopting a new user interface with a closer resemblance to Wunderlist. The name was also slightly updated by removing the hyphen from To-Do. In May 2020, Microsoft officially closed the doors on Wunderlist, ending its active service in favor of improving and expanding Microsoft To Do.
Avid Symphony
Avid Symphony is non-linear editing software aimed at professionals in the film and television industry. It is available for Microsoft Windows PCs and Apple Macintosh platforms. Symphony is Avid's high end SD/HD finishing platform for long form work, such as documentary and episodic TV. Its interface is based on the same look and feature set as the Media Composer and Xpress systems, but contains the highest level of features and resolution including secondary color correction, uncompressed HD, and higher real-time performance. == Release history == Symphony is the software component of a tightly integrated package that includes specific hardware audio/video interfaces, storage, and the computer, also sold by Avid. Its release history is therefore tightly related to the release of new Avid interface hardware: Symphony was introduced to the market in 1998. It was based on Avid's Meridien hardware, supporting SD only, and was available first only for the PC and later for the Macintosh platforms. Its last release was 5.0.5 which supported Windows 2000 and Mac OS X v10.2. The next major upgrade was Symphony Nitris in 2005, with a redesigned software and integration with the Nitris DNA hardware (PCI-X). It supported 8 bit and 10 bit SD and HD resolutions in both compressed and uncompressed forms, the MXF format and DNxHD codec, and ran only on Windows PC platforms. Symphony Nitris DX, released in 2008, added support for a range of HD codecs, including HDV, XDCAM-HD, DVCPRO HD, and AVC-I, and brought back Mac OS support for OS X 10.5, as well as Windows Vista. Since the introduction of Symphony 6, it can be used in software-only mode (where a Nitris or Nitris DX BOB used to be required), and at the same time, like Media Composer, Symphony was opened up with "Open I/O", allowing users to have Symphony use their third party hardware from companies like AJA, Matrox, BlueFish, Blackmagic Design and MOTU. The last remaining features that differentiate it from Media Composer are Advanced Color Correction (channels, secondary color correction,), Relational Color Correction (corrections based on common clip name, tape name, program track) and Universal HD Mastering (only with Nitris DX hardware). The latter allows cross-conversions of 23.976p or 24p projects sequences to most any other format during Digital Cut. In 2013, Avid announced it would no longer offer Symphony a standalone product. Starting version 7, Symphony will be sold as an option to Media Composer. This optional package (sold at a premium) will contain all the traditional Symphony-only features to any Media Composer install. == Use in movies == The Celibacy, Director: Horacio Bocaranda Avid Media Composer 6 and Avid Symphony 6 Nitris DX American Hardcore, Director: Paul Rachman Avid Xpress Pro and Symphony Summercamp!, Director: Spike Lee Avid Xpress Pro and Symphony When the Levees Broke Avid Media Composer and Symphony Nitris Superman Returns Edited with Mac-based Film Composer XL, but HD screenings prepped with Symphony
MoltenVK
MoltenVK is a software library which allows Vulkan applications to run on top of Metal on Apple's macOS, iOS, and tvOS operating systems. It is the first software component to be released for the Vulkan Portability Initiative, a project to have a subset of Vulkan run on platforms lacking native Vulkan drivers. There are some limitations compared with a native Vulkan implementation. == History == MoltenVK was first released as a proprietary and commercially licensed product by The Brenwill Workshop on July 27, 2016. On July 31, 2017, Khronos announced the formation of the Vulkan Portability Technical Subgroup. === Open source === On February 26, 2018, Khronos announced that Vulkan became available on macOS and iOS products through the MoltenVK library. Valve announced that Dota 2 will run on macOS using the Vulkan API with the aid of MoltenVK, and that they had made an arrangement with developer The Brenwill Workshop Ltd to release MoltenVK as open-source software under the Apache License version 2.0. On May 30, 2018, Qt was updated with Vulkan for Qt on macOS using MoltenVK. On May 31, 2018, optional Vulkan support for Dota 2 on macOS was released. Benchmarks for the game were available the following day, showing better performance using Vulkan and MoltenVK compared to OpenGL. On July 20, 2018, Wine was updated with Vulkan support on macOS using MoltenVK. On 29 July 2018, the first app using MoltenVK was accepted onto the App Store, after initially being rejected. On 6 August 2018, Google open-sourced Filament, a crossplatform real-time physically based rendering engine with MoltenVK for macOS/iOS. On November 28, 2018, Valve released Artifact, their first Vulkan-only game on macOS using MoltenVK. === Version 1.0 === On 29 January 2019, MoltenVK 1.0.32 was released with early prototype of Vulkan Portability Extensions. RPCS3 and Dolphin emulators were updated with Vulkan support on macOS using MoltenVK. On 13 April 2019, MoltenVK 1.0.34 was released with support for tessellation. On July 30, 2019, MoltenVK 1.0.36 was released targeting Metal 3.0. On July 31, 2020, MoltenVK 1.0.44 was released, adding support for the tvOS platform. On January 23, 2020, MoltenVK was updated to support for some of the new features of Vulkan 1.2, as of Vulkan SDK 1.2.121. === Version 1.1 === On October 1, 2020, MoltenVK 1.1.0 was released, adding full support for Vulkan 1.1, as of Vulkan SDK 1.2.154. On 9 December 2020, MoltenVK 1.1.1 was released, providing support for Vulkan on Apple silicon GPUs and support for the Mac Catalyst platform for porting iOS/iPadOS apps to macOS. === Version 1.2 === On October 18, 2022, MoltenVK 1.2.0 was released, adding full support for Vulkan 1.2 as of Vulkan SDK 1.3.231. In January 2023, MoltenVK 1.2.2 added support for Vulkan as of SDK 1.3.239, while this version of Vulkan SDK fixed some issues with the interconnectivity with Metal API, while version 1.2.3 supported some additional extensions. === Version 1.3 === On May 1, 2025, MoltenVK 1.3 was released with support for Vulkan 1.3. === Version 1.4 === On August 20, 2025, MoltenVK 1.4 was released with support for Vulkan 1.4.
IDMS
The Integrated Database Management System (IDMS) is a network model (CODASYL) database management system for mainframes. It was first developed at BFGoodrich and later marketed by Cullinane Database Systems (renamed Cullinet in 1983). Since 1989 the product has been owned by Computer Associates (now CA Technologies), who renamed it Advantage CA-IDMS and later simply to CA IDMS. In 2018 Broadcom acquired CA Technologies, renaming it back to IDMS. == History == The roots of IDMS go back to the pioneering database management system called Integrated Data Store (IDS), developed at General Electric by a team led by Charles Bachman and first released in 1964. In the early 1960s IDS was taken from its original form, by the computer group of the BFGoodrich Chemical Division, and re-written in a language called Intermediate System Language (ISL). ISL was designed as a portable system programming language able to produce code for a variety of target machines. Since ISL was actually written in ISL, it was able to be ported to other machine architectures with relative ease, and then to produce code that would execute on them. The Chemical Division computer group had given some thought to selling copies of IDMS to other companies, but was told by management that they were not in the software products business. Eventually, a deal was struck with John Cullinane to buy the rights and market the product. Because Cullinane was required to remit royalties back to B.F. Goodrich, all add-on products were listed and billed as separate products – even if they were mandatory for the core IDMS product to work. This sometimes confused customers. The original platforms were the GE 235 computer and GE DATANET-30 message switching computer: later the product was ported to IBM mainframes and to DEC and ICL hardware. The IBM-ported version runs on IBM mainframe systems (System/360, System/370, System/390, zSeries, System z9). In the mid-1980s, it was claimed that some 2,500 IDMS licenses had been sold. Users included the Strategic Air Command, Ford of Canada, Ford of Europe, Jaguar Cars, Clarks Shoes UK, Axa/PPP, MAPFRE, Royal Insurance, Tesco, Manulife, Hudson's Bay Company, Cleveland Clinic, Bank of Canada, General Electric, Aetna and BT in the UK. A version for use on the Digital Equipment Corporation PDP-11 series of computers was sold to DEC and was marketed as DBMS-11. In 1976 the source code was licensed to ICL, who ported the software to run on their 2900 series mainframes, and subsequently also on the older 1900 range. ICL continued development of the software independently of Cullinane, selling the original ported product under the name ICL 2900 IDMS and an enhanced version as IDMSX. In this form it was used by many large UK users, an example being the Pay-As-You-Earn system operated by Inland Revenue. Many of these IDMSX systems for UK Government were still running in 2013. In the early to mid-1980s, relational database management systems started to become more popular, encouraged by increasing hardware power and the move to minicomputers and client–server architecture. Relational databases offered improved development productivity over CODASYL systems, and the traditional objections based on poor performance were slowly diminishing. Cullinet attempted to continue competing against IBM's DB2 and other relational databases by developing a relational front-end and a range of productivity tools. These included Automatic System Facility (ASF), which made use of a pre-existing IDMS feature called LRF (Logical Record Facility). ASF was a fill-in-the-blanks database generator that would also develop a mini-application to maintain the tables. It is difficult to judge whether such features may have been successful in extending the selling life of the product, but they made little impact in the long term. Those users who stayed with IDMS were primarily interested in its high performance, not in its relational capabilities. It was widely recognized (helped by a high-profile campaign by E. F. Codd, the father of the relational model) that there was a significant difference between a relational database and a network database with a relational veneer. In 1989 Computer Associates continued after Cullinet acquisition with the development and released Release 12.0 with full SQL in 1992–93. CA Technologies continued to market and support the CA IDMS and enhanced IDMS in subsequent releases by TCP/IP support, two phase commit support, XML publishing, zIIP specialty processor support, Web-enabled access in combination with CA IDMS Server, SQL Option and GUI database administration via CA IDMS Visual DBA tool. CA-IDMS systems are today still running businesses worldwide. Many customers have opted to web-enable their applications via the CA-IDMS SQL Option which is part of CA Technologies' Dual Database Strategy. == Integrated Data Dictionary == One of the sophisticated features of IDMS was its built-in Integrated data dictionary (IDD). The IDD was primarily developed to maintain database definitions. It was itself an IDMS database. DBAs (database administrators) and other users interfaced with the IDD using a language called Data Dictionary Definition Language (DDDL). IDD was also used to store definitions and code for other products in the IDMS family such as ADS/Online and IDMS-DC. IDD's power was that it was extensible and could be used to create definitions of just about anything. Some companies used it to develop in-house documentation. == Overview == === Logical Data Model === The data model offered to users is the CODASYL network model. The main structuring concepts in this model are records and sets. Records essentially follow the COBOL pattern, consisting of fields of different types: this allows complex internal structure such as repeating items and repeating groups. The most distinctive structuring concept in the Codasyl model is the set. Not to be confused with a mathematical set, a Codasyl set represents a one-to-many relationship between records: one owner, many members. The fact that a record can be a member in many different sets is the key factor that distinguishes the network model from the earlier hierarchical model. As with records, each set belongs to a named set type (different set types model different logical relationships). Sets are in fact ordered, and the sequence of records in a set can be used to convey information. A record can participate as an owner and member of any number of sets. Records have identity, the identity being represented by a value known as a database key. In IDMS, as in most other Codasyl implementations, the database key is directly related to the physical address of the record on disk. Database keys are also used as pointers to implement sets in the form of linked lists and trees. This close correspondence between the logical model and the physical implementation (which is not a strictly necessary part of the Codasyl model, but was a characteristic of all successful implementations) is responsible for the efficiency of database retrieval, but also makes operations such as database loading and restructuring rather expensive. Records can be accessed directly by database key, by following set relationships, or by direct access using key values. Initially the only direct access was through hashing, a mechanism known in the Codasyl model as CALC access. In IDMS, CALC access is implemented through an internal set, linking all records that share the same hash value to an owner record that occupies the first few bytes of every disk page. In subsequent years, some versions of IDMS added the ability to access records using BTree-like indexes. === Storage === IDMS organizes its databases as a series of files. These files are mapped and pre-formatted into so-called areas. The areas are subdivided into pages which correspond to physical blocks on the disk. The database records are stored within these blocks. The DBA allocates a fixed number of pages in a file for each area. The DBA then defines which records are to be stored in each area, and details of how they are to be stored. IDMS intersperses special space-allocation pages throughout the database. These pages are used to keep track of the free space available in each page in the database. To reduce I/O requirements, the free space is only tracked for all pages when the free space for the area falls below 30%. Four methods are available for storing records in an IDMS database: Direct, Sequential, CALC, and VIA. The Fujitsu/ICL IDMSX version extends this with two more methods, Page Direct, and Random. In direct mode the target database key is specified by the user and is stored as close as possible to that DB key, with the actual DB key on which the record is stored being returned to the application program. Sequential placement (not to be confused with indexed sequential), simply places each new record at the end of the area. This option is rarely used. CALC uses a hashing algo
Arattai
Arattai Messenger (or simply Arattai) is an encrypted messaging service for instant messaging, voice calls, and video calls, developed by Zoho Corporation. The name Arattai means "chat" or "conversation" in Tamil. The app was soft-launched in January 2021. The app saw a sharp surge in downloads in September 2025, partially fueled by endorsements from Indian government officials. However, the app dropped from the top rankings in October 2025. == History == Arattai was initially tested internally among Zoho employees before being released publicly in early 2021. The launch coincided with a surge in interest for privacy-focused and messaging services, triggered by concerns over WhatsApp's updated terms of service. In September 2025, Arattai experienced a major surge in adoption, with daily sign-ups reportedly increasing 100-fold, from around 3,000 to more than 350,000 in three days. The surge in downloads was attributed to Zoho products being promoted by Indian government officials as part of their Make in India push for homegrown alternatives to foreign‐owned apps, amid deteriorating India–US relations. The growth temporarily strained Zoho's infrastructure, prompting rapid scaling of servers and capacity expansion. During the same period, the app reached the top position in Apple's App Store charts for the "Social Networking" category in India. The app dropped from the top ranking in late October 2025. == Reception == At launch, Arattai was positioned as a potential domestic rival to WhatsApp in India, but analysts noted that it faced challenges with encryption, ecosystem, and network effect. Critics pointed to occasional sync delays.