In the context of data management, autocommit is a mode of operation of a database connection. Each individual database interaction (i.e., each SQL statement) submitted through the database connection in autocommit mode will be executed in its own transaction that is implicitly committed. A SQL statement executed in autocommit mode cannot be rolled back. Autocommit mode incurs per-statement transaction overhead and can often lead to undesirable performance or resource utilization impact on the database. Nonetheless, in systems such as Microsoft SQL Server, as well as connection technologies such as ODBC and Microsoft OLE DB, autocommit mode is the default for all statements that change data, in order to ensure that individual statements will conform to the ACID (atomicity-consistency-isolation-durability) properties of transactions. The alternative to autocommit mode (non-autocommit) means that the SQL client application itself is responsible for ending transactions explicitly via the commit or rollback SQL commands. Non-autocommit mode enables grouping of multiple data manipulation SQL commands into a single atomic transaction. Some DBMS (e.g. MariaDB) force autocommit for every DDL statement, even in non-autocommit mode. In this case, before each DDL statement, previous DML statements in transaction are autocommitted. Each DDL statement is executed in its own new autocommit transaction.
List of performance analysis tools
This is a list of performance analysis tools for use in software development. == General purpose, language independent == The following tools work based on log files that can be generated from various systems. time (Unix) - can be used to determine the run time of a program, separately counting user time vs. system time, and CPU time vs. clock time. timem (Unix) - can be used to determine the wall-clock time, CPU time, and CPU utilization similar to time (Unix) but supports numerous extensions. Supports reporting peak resident set size, major and minor page faults, priority and voluntary context switches via getrusage. Supports sampling procfs on supporting systems to report metrics such as page-based resident set size, virtual memory size, read-bytes, and write-bytes, etc. Supports collecting hardware counters when built with PAPI support. == Multiple languages == The following tools work for multiple languages or binaries. == C and C++ == Arm MAP, a performance profiler supporting Linux platforms. AppDynamics, an application performance management service for C/C++ applications via SDK. AQtime Pro, a performance profiler and memory allocation debugger that can be integrated into Microsoft Visual Studio, and Embarcadero RAD Studio, or can run as a stand-alone application. IBM Rational Purify was a memory debugger allowing performance analysis. Instruments (bundled with Xcode) is used to profile an executable's memory allocations, time usage, filesystem activity, GPU activity etc. Intel Parallel Studio contains Intel VTune Amplifier, which tunes both serial and parallel programs. It also includes Intel Advisor and Intel Inspector. Intel Advisor optimizes vectorization (use of SIMD instructions) and prototypes threading implementations. Intel Inspector detects and debugs races, deadlocks and memory errors. Parasoft Insure++ provides a graphical tool that displays and animates memory allocations in real time to expose memory blowout, fragmentation, overuse, bottlenecks and leaks. Visual Studio Team System Profiler, commercial profiler by Microsoft. == Java == inspectIT is an open-source application performance management (APM) service for monitoring and analyzing software applications, available under the Apache License, Version 2.0 (ALv2). JConsole is the profiler which comes with the Java Development Kit JProfiler JRockit Mission Control, a profiler with low overhead. Netbeans Profiler, a profiler integrated into the NetBeans IDE (internally uses jvisualvm profiler) Plumbr, Java application performance monitoring with automated root cause detection. Links memory leaks, GC inefficiency, slow database and external web service calls, locked threads, and other performance problems to the line in source code that causes them. OverOps, Continuous reliability for the modern software supply chain, automatically detect and deliver root cause automation for all errors. VisualVM is a visual tool integrating several commandline JDK tools and lightweight profiling capabilities. It is bundled with the Java Development Kit since version 6, update 7. == JavaScript == The Firefox web browser's developer tools contain a Performance tool, which gives insight into JavaScript performance of a website. Microsoft Visual Studio AJAX Profiling Extensions is a free profiling tool for JavaScript by Microsoft Research. == .NET == CLR Profiler is a free memory profiler provided by Microsoft for CLR applications. GlowCode is a performance and memory profiler for .NET applications using C# and other .NET languages. It identifies time-intensive functions and detects memory leaks and errors in native, managed and mixed Windows x64 and x86 applications. Visual Studio == PHP == BlackFire.io Dbg Xdebug is a PHP extension which provides debugging and profiling capabilities.
Linagora
Linagora is a French open source software editor, founded in June 2000 by Alexandre Zapolsky and Michel-Marie Maudet. Located in France, as well as in Belgium, Canada, Vietnam, the United States and Tunisia, the company employs around 200 people. In 2023, Linagora created the OpenLLM France community, alongside other French Artificial Intelligence companies and organizations. In 2025, the company launched Lucie, an opensource Large Language Model. == History == Linagora was founded on June 28, 2000. Its name is a contraction of the words "Linux" and "Agora". The company was founded by Alexandre Zapolsky and Michel-Marie Maudet. Soon after, the two entrepreneurs were joined by Alexandre Zapolsky's wife and brother, who took on the roles of commercial director and administrative and financial director of the SME. In 2007, the company was selected by the French National Assembly to provide the software for Linux computers, replacing Microsoft Windows. Linagora then claimed the position of the leading French open source software company by revenue. In 2015, French Prime Minister Manuel Valls allocated €10.7 million from the "Investments for the Future" fund for a research program aimed at developing a new generation of open source software platforms based on Linagora's offerings. In September 2016, Linagora launched the social network "La Cerise" for the newspaper L'Humanité. This app offered a service and tool for readers and citizens mobilizing for causes. It aimed to share engagement through petitions, discussions, agendas, and contacts. In October 2016, the company won two public contracts for supporting open source software in forty-two French ministries and other administrative entities. In May 2019, Linagora organized a fundraising event in the presence of the French Secretary of State for Digital Affairs, Cédric O, to celebrate its 19th anniversary. The funds were intended for: Supporting parents of hospitalized Polynesian children in France. Equipping primary school students with digital devices (tablets or PCs). Establishing a digital academy "OpenHackademy" in French Polynesia to train unemployed youth in digital skills and help them find jobs. In December 2022, Linagora acquired a property known as "Maison Rocher" and later "Maison Chocolat," located on the Île Saint-Germain in Issy-les-Moulineaux. Renamed "Villa Good Tech" by Linagora, this award-winning architectural work by Éric Daniel-Lacombe became the company's new headquarters, aiming to provide a space for associative actors and companies to develop technologies that contribute to a better world. In July 2023, Linagora launched OpenLLM France, a community initially comprising around twenty actors focused on generative AI. The goal was to develop a sovereign and open source large language model. This initiative, led by co-founder and CEO Michel-Marie Maudet, had more than four hundred French members by early 2024. and announced its expansion to the European sphere during Fosdem 2024. In February 2024, the CNRS and Linagora signed a framework agreement to strengthen their research collaboration. In January 2025, Linagora released Lucie, an open source and sovereign AI that faced ridicule due to tests on an unfinished, uncensored version designed for scientific and experimental use. The platform divided opinions between those who saw it as a technological achievement and those who criticized it as "French bashing" compared to American and Chinese AIs. == Acquisitions == The company acquired: In July 2007, the SME AliaSource, based in Ramonville-Saint-Agne and led by its founder, Pierre Baudracco. In 2008, the open source web hosting company Netaktiv, a member of the GIE Gitoyen, announced during the 2008 Solutions Linux trade show. In 2012, the Toulouse-based company EBM Websourcing, the publisher of the open-source software Petals Link, and took over its development. In 2016, the digital agency Neoma Interactive, specializing in UX design and digital communication strategy. == Locations == In 2017, the company's headquarters was located in Issy-les-Moulineaux, with branches in Lyon, Toulouse, Marseille, and internationally in Brussels, San Francisco, Montreal, Vietnam, and Tunisia. In 2005, the company attempted to establish a presence in Nantes. In 2024, the headquarters was moved to Issy-les-Moulineaux. == Activity == === Software === Twake Workplace One of Linagora's flagship products is Twake Workplace, which stands out as a 100% open-source solution compared with those of the GAFAMs. Twake Workplace is available as a complete platform or module by module. It includes : Twake Mail, a powerful modern messaging solution based on the JMAP protocol and the James email server from the Apache Foundation, for which Linagora provides technical management; Twake Chat, an instant communications solution for businesses developed using the Matrix protocol and compatible with the French government's chat solution, Tchap; Twake Drive, an easy-to-use collaborative platform for group work using OnlyOffice. ==== OpenPaaS ==== In 2018, the search engine Qwant announced that its email service Qwantmail would be based on the OpenPaaS product. In 2022, Qwant announced the abandonment of its Qwantmail project due to Linagora's collection of personal email addresses and serious security breaches. The site Next (formerly PC INpact) published an article in January 2020 criticizing the "failures and delays" of the Qwantmail project led by Linagora, which led to the CNIL's intervention regarding Qwant and Linagora. ==== LinTO ==== In 2017, Linagora launched its open source voice assistant project named LinTO. This enterprise voice assistant, described as "GAFAM Free," was presented at CES 2018 in Las Vegas. The LinTO voice framework was developed as part of the eponymous research project funded by Bpifrance (Grands Défis du Numérique instrument). === Services === ==== OSSA (Open Source Software Assurance) ==== One of the company's main activities is OSSA. Through OSSA, Linagora provided support for open source software for 42 ministries and other administrative entities in 2012. == Legal issues == === Dispute with BlueMind === In 2012, a legal dispute arose between BlueMind and Linagora. Linagora accused BlueMind of copyright infringement, unfair competition, and breach of a non-compete clause, leading to several legal actions. Linagora sued BlueMind for copyright infringement and unfair competition in the Bordeaux court, which ruled in Linagora's favor for unfair competition and parasitism but rejected the copyright claim. BlueMind was ordered to pay nearly €170,000 to Linagora. Linagora sued former associates Pierre Baudracco and Pierre Carlier in the Paris Commercial Court for breach of a non-compete clause and violation of a warranty of eviction. The court dismissed Linagora's claims and ordered it to pay €20,000 each to Baudracco and Carlier. Linagora appealed, and the Paris Court of Appeal partially overturned the decision, awarding Linagora €480,000. BlueMind sued Linagora for defamation and public insult in the Toulouse Criminal Court. The court ruled against Linagora, but the decision was overturned by the Court of Cassation in January 2024, and the case was remanded for retrial. === Conviction for wrongful termination and harassment === On June 14, 2017, France 3 reported on a decision by the Versailles Court of Appeal, which ruled that Linagora had wrongfully terminated an employee and subjected them to moral harassment. The court ordered Linagora to pay the employee €22,000 for wrongful termination, €11,000 for notice pay, €6,600 for legal severance pay, €3,200 for conservative suspension, and €3,000 for moral harassment.
Xcon
The R1, internally called XCON (Expert Configurer), program was a production-rule-based system written in OPS5 by John P. McDermott of Carnegie Mellon University in 1978 to assist in the ordering of Digital Equipment Corporation's (DEC) VAX computer systems by automatically selecting the computer system components based on the customer's requirements. == Overview == In developing the system, McDermott made use of experts from both DEC's PDP/11 and VAX computer systems groups. These experts sometimes even disagreed amongst themselves as to an optimal configuration. The resultant "sorting it out" had an additional benefit in terms of the quality of VAX systems delivered. XCON first went into use in 1980 in DEC's plant in Salem, New Hampshire, US. It eventually had about 2500 rules. By 1986, it had processed 80,000 orders, and achieved 95–98% accuracy. It was estimated to be saving DEC $25M a year by reducing the need to give customers free components when technicians made errors, by speeding the assembly process, and by increasing customer satisfaction. Before XCON, when ordering a VAX from DEC, every cable, connection, and bit of software had to be ordered separately. (Computers and peripherals were not sold complete in boxes as they are today.) The sales people were not always very technically expert, so customers would find that they had hardware without the correct cables, printers without the correct drivers, a processor without the correct language chip, and so on. This meant delays and caused a lot of customer dissatisfaction and resultant legal action. XCON interacted with the sales person, asking critical questions before printing out a coherent and workable system specification/order slip. XCON's success led DEC to rewrite XCON as XSEL—a version of XCON intended for use by DEC's salesforce to aid a customer in properly configuring their VAX (so they would not, say, choose a computer too large to fit through their doorway or choose too few cabinets for the components to fit in). Location problems and configuration were handled by yet another expert system, XSITE. McDermott's 1980 paper on R1 won the Association for the Advancement of Artificial Intelligence (AAAI) Classic Paper Award in 1999. Footnote 2 gave a humorous explanation for the name "R1" as "Four years ago I couldn't even say "knowledge engineer", now I ... [are one.]".
Transparency in Frontier Artificial Intelligence Act
The Transparency in Frontier Artificial Intelligence Act, also referred to as SB-53, is a 2025 California law which mandates increased transparency for companies building artificial intelligence. SB-53 is primarily focused on assessing and reducing potential catastrophic risks from AI, and is the first bill addressing such risks to be passed into law in America. The bill requires companies to create publicly accessible documents assessing potential "catastrophic risk[s]" from their AI models, as well as publishing documentation on how the model incorporates national and international safety standards. SB-53 also sets up whistleblower protections and procedures for alerting the government to a "critical safety incident". == History == SB-53 was preceded in 2024 by the unsuccessful Safe and Secure Innovation for Frontier Artificial Intelligence Models Act ("SB-1047"), a proposed bill authored by Senator Scott Wiener which was vetoed by Governor Gavin Newsom. Afterwords, Newsom created a "Joint California AI Policy Working Group" to provide recommendations for AI regulation, which guided the drafting of SB-53. Senator Scott Wiener introduced the bill on January 7, 2025, and after a series of amendments, SB-53 passed the Senate 29-8 on September 13. Governor Gavin Newsom approved the bill on September 25, passing it into law. == Provisions == SB-53 applies primarily to companies making at least $500 million in yearly gross revenue. It defines a “frontier model” as any AI trained with over 1026 FLOPS (including fine-tuning), including unreleased internal models. Both the financial and computational thresholds must be met before most of the law is applied, although the threshold can be lowered or otherwise updated by the California Department of Technology in an annual review starting in 2027. Most of the bill's provisions are focused on "catastrophic risks" from AI, which are defined as incidents in which a model contributes to more than 50 deaths or serious injuries, or causes more than one billion dollars ($1,000,000,000) in economic damage from AI-assisted acts (such as cyberattacks or the creation of biological weapons). The bill requires companies to provide publicly accessible safety frameworks for frontier AI models, describing how the company tests for catastrophic risk from its AI, and how it implements protections against such risks. This includes addressing the possibility that the AI may attempt to circumvent internal guardrails or oversight mechanisms. (Certain safety incidents, such as dangerously deceptive model behavior, physical injury, or death, must be reported to California Office of Emergency Services (OES) within 15 days, unless the incident poses imminent physical risk, in which case it must be reported immediately.) The company must follow its published framework, and if any changes are made, the framework should be updated within 30 days, and justification for said changes must also be made public. Additionally, all frontier companies are required to publish basic information about newly released frontier models (such as terms of service, supported languages, and intended use), although only large companies (making over $500 million annually) need to publish full safety frameworks. SB-53 also establishes various whistleblower protections for covered employees. Large companies must have anonymous whistleblowing channels in place which protect employees from retaliation from reporting risks to state or federal authorities if they have reasonable cause to believe that their employer is substantially risking public health and safety.
Computer security compromised by hardware failure
Computer security compromised by hardware failure is a branch of computer security applied to hardware. The objective of computer security includes protection of information and property from theft, corruption, or natural disaster, while allowing the information and property to remain accessible and productive to its intended users. Such secret information could be retrieved by different ways. This article focus on the retrieval of data thanks to misused hardware or hardware failure. Hardware could be misused or exploited to get secret data. This article collects main types of attack that can lead to data theft. Computer security can be compromised by devices, such as keyboards, monitors or printers (thanks to electromagnetic or acoustic emanation for example) or by components of the computer, such as the memory, the network card or the processor (thanks to time or temperature analysis for example). == Devices == === Monitor === The monitor is the main device used to access data on a computer. It has been shown that monitors radiate or reflect data on their environment, potentially giving attackers access to information displayed on the monitor. ==== Electromagnetic emanations ==== Video display units radiate: narrowband harmonics of the digital clock signals; broadband harmonics of the various 'random' digital signals such as the video signal. Known as compromising emanations or TEMPEST radiation, a code word for a U.S. government programme aimed at attacking the problem, the electromagnetic broadcast of data has been a significant concern in sensitive computer applications. Eavesdroppers can reconstruct video screen content from radio frequency emanations. Each (radiated) harmonic of the video signal shows a remarkable resemblance to a broadcast TV signal. It is therefore possible to reconstruct the picture displayed on the video display unit from the radiated emission by means of a normal television receiver. If no preventive measures are taken, eavesdropping on a video display unit is possible at distances up to several hundreds of meters, using only a normal black-and-white TV receiver, a directional antenna and an antenna amplifier. It is even possible to pick up information from some types of video display units at a distance of over 1 kilometer. If more sophisticated receiving and decoding equipment is used, the maximum distance can be much greater. ==== Compromising reflections ==== What is displayed by the monitor is reflected on the environment. The time-varying diffuse reflections of the light emitted by a CRT monitor can be exploited to recover the original monitor image. This is an eavesdropping technique for spying at a distance on data that is displayed on an arbitrary computer screen, including the currently prevalent LCD monitors. The technique exploits reflections of the screen's optical emanations in various objects that one commonly finds close to the screen and uses those reflections to recover the original screen content. Such objects include eyeglasses, tea pots, spoons, plastic bottles, and even the eye of the user. This attack can be successfully mounted to spy on even small fonts using inexpensive, off-the-shelf equipment (less than 1500 dollars) from a distance of up to 10 meters. Relying on more expensive equipment allowed to conduct this attack from over 30 meters away, demonstrating that similar attacks are feasible from the other side of the street or from a close by building. Many objects that may be found at a usual workplace can be exploited to retrieve information on a computer's display by an outsider. Particularly good results were obtained from reflections in a user's eyeglasses or a tea pot located on the desk next to the screen. Reflections that stem from the eye of the user also provide good results. However, eyes are harder to spy on at a distance because they are fast-moving objects and require high exposure times. Using more expensive equipment with lower exposure times helps to remedy this problem. The reflections gathered from curved surfaces on close by objects indeed pose a substantial threat to the confidentiality of data displayed on the screen. Fully invalidating this threat without at the same time hiding the screen from the legitimate user seems difficult, without using curtains on the windows or similar forms of strong optical shielding. Most users, however, will not be aware of this risk and may not be willing to close the curtains on a nice day. The reflection of an object, a computer display, in a curved mirror creates a virtual image that is located behind the reflecting surface. For a flat mirror this virtual image has the same size and is located behind the mirror at the same distance as the original object. For curved mirrors, however, the situation is more complex. === Keyboard === ==== Electromagnetic emanations ==== Computer keyboards are often used to transmit confidential data such as passwords. Since they contain electronic components, keyboards emit electromagnetic waves. These emanations could reveal sensitive information such as keystrokes. Electromagnetic emanations have turned out to constitute a security threat to computer equipment. The figure below presents how a keystroke is retrieved and what material is necessary. The approach is to acquire the raw signal directly from the antenna and to process the entire captured electromagnetic spectrum. Thanks to this method, four different kinds of compromising electromagnetic emanations have been detected, generated by wired and wireless keyboards. These emissions lead to a full or a partial recovery of the keystrokes. The best practical attack fully recovered 95% of the keystrokes of a PS/2 keyboard at a distance up to 20 meters, even through walls. Because each keyboard has a specific fingerprint based on the clock frequency inconsistencies, it can determine the source keyboard of a compromising emanation, even if multiple keyboards from the same model are used at the same time. The four different kinds way of compromising electromagnetic emanations are described below. ===== The Falling Edge Transition Technique ===== When a key is pressed, released or held down, the keyboard sends a packet of information known as a scan code to the computer. The protocol used to transmit these scan codes is a bidirectional serial communication, based on four wires: Vcc (5 volts), ground, data and clock. Clock and data signals are identically generated. Hence, the compromising emanation detected is the combination of both signals. However, the edges of the data and the clock lines are not superposed. Thus, they can be easily separated to obtain independent signals. ===== The Generalized Transition Technique ===== The Falling Edge Transition attack is limited to a partial recovery of the keystrokes. This is a significant limitation. The GTT is a falling edge transition attack improved, which recover almost all keystrokes. Indeed, between two traces, there is exactly one data rising edge. If attackers are able to detect this transition, they can fully recover the keystrokes. ===== The Modulation Technique ===== Harmonics compromising electromagnetic emissions come from unintentional emanations such as radiations emitted by the clock, non-linear elements, crosstalk, ground pollution, etc. Determining theoretically the reasons of these compromising radiations is a very complex task. These harmonics correspond to a carrier of approximately 4 MHz which is very likely the internal clock of the micro-controller inside the keyboard. These harmonics are correlated with both clock and data signals, which describe modulated signals (in amplitude and frequency) and the full state of both clock and data signals. This means that the scan code can be completely recovered from these harmonics. ===== The Matrix Scan Technique ===== Keyboard manufacturers arrange the keys in a matrix. The keyboard controller, often an 8-bit processor, parses columns one-by-one and recovers the state of 8 keys at once. This matrix scan process can be described as 192 keys (some keys may not be used, for instance modern keyboards use 104/105 keys) arranged in 24 columns and 8 rows. These columns are continuously pulsed one-by-one for at least 3μs. Thus, these leads may act as an antenna and generate electromagnetic emanations. If an attacker is able to capture these emanations, he can easily recover the column of the pressed key. Even if this signal does not fully describe the pressed key, it still gives partial information on the transmitted scan code, i.e. the column number. Note that the matrix scan routine loops continuously. When no key is pressed, we still have a signal composed of multiple equidistant peaks. These emanations may be used to remotely detect the presence of powered computers. Concerning wireless keyboards, the wireless data burst transmission can be used as an electromagnetic trigger to detect exactly when a key is pressed, while the matrix s
Public First Action
Public First Action is a 501(c)(4) nonprofit organization focused on United States public policy related to artificial intelligence. Public First Action is a bipartisan group that advocates for AI transparency, safeguards, and export controls on advanced AI chips. The organization is aligned with the political action committees Jobs and Democracy, Defending Our Values and Public First. == History == Public First Action was formed in 2025 by former Congressmen Brad Carson, a Democrat, and Chris Stewart, a Republican, to advocate for federal, state, and local regulations related to AI. The group's formation followed the founding of a super PAC network, Leading the Future, which advocates for deregulation of the AI industry and faster development of the new technology. Public First Action supports measures that would increase transparency at frontier AI companies and impose export controls on advanced AI chips, in addition to opposing the preemption of state-level AI laws. In February 2026, Public First Action received $20 million from the AI company Anthropic. That same month, the group announced plans to support 30 to 50 Democrats and Republicans in state and federal races, with Public First Action and aligned super PACs launching advertisements in Nebraska, Tennessee, and other states. In one ad, Public First Action touted Senator Marsha Blackburn for her work on child online safety. As of 2026, the group plans to raise between $50 and $75 million for public oversight of AI and related reforms. == Organization == === Leadership and funding === Public First Action is led by Carson and Stewart. The group has raised nearly $50 million in funding with a goal of raising $75 million during the 2026 midterms. Anthropic has contributed $20 million to the group. === Structure === Public First Action is aligned with three political action committees: "Jobs and Democracy", which supports Democratic candidates; "Defending Our Values", which supports Republican candidates; and "Public First", which supports both Republicans and Democrats.