Swish Analytics is the best platform for powering U

Swish Analytics

338 Stories To Learn About Github

368 Stories To Learn About Debugging

Data today: The Wild West. If you have digital tracks, the latest revelation of corporate data intrusion will leave you shaking in them. According to a , Android is a data monster with a voracious appetite for your data. The mobile operating system with 85 percent market share is harvesting and sharing data from 90 percent of the apps running on its OS. More disconcertingly, 43 percent of these apps transfer data to third parties, including Facebook and Twitter. newly released Oxford University study Such data intrusion is characteristic of the current age of data. Users have been used to seeing their data harvested by the giants of this world, be it companies or . governments What will it take to re-instill public trust in Google and Android apps? Consider that the recent report of a data security flaw compelled Google to shut down the messaging app. In a public weary from data misappropriation and hacking issues, nothing short of a paradigm shift in data security may do. Change is coming: self-sovereignty. The self-sovereign digital identity movement is already radically changing personal data management practices. Blockchain digital identity applications are allowing consumers to regain control of their data, secure it, and monetize it. The ability to manage Personal Identification Information (PII) will be the primary driver of consumers migrating to blockchain applications to engage with financial services, travel services, gaming platforms and all other aspects of their digital lives in a single sign-on and secure data environment. But whether you are a user of, or investor in, blockchain self-sovereign digital IDs, investing in the alone could be a money loser. The market is divided on which digital data security technology to employ and rapidly bifurcating like a Merkle tree into evolving technology camps. concept Towards Full Identity Rights Blockchain sovereign identity is the solution to corporate and government privacy violations. Consumers not only control what data to hand over but also will be incentivized to share data. All digital identity applications promise to provide various identity, credit, and related functions to allow you to move seamlessly through your digital life, including: KYC on-boarding: asking users for their identification information one time only, and authentication of the information performed through biometrics and/or private/public keys Credit report information and authorization: applying for credit cards or a trading margin account Anonymous access to services without providing a username or password Biometric authentication In the first quarter of 2019, many individuals and businesses will start using self-sovereign identities. Bermuda, for example, is preparing to . Bermudan citizens can claim their digital identities with government-issued licenses, documents, and health care data embedded in them. give its citizens their full identity rights Also in the new year, Visa B2B Connect will allow financial institutions to process cross-border transactions with a token identifier. ’s digital identity system is being trialed in major airline, credit card, credit reporting, immigration, and financial services firms. ShoCard Security should be of foremost concern, and it seems to be still a valid one: modern cryptographic systems are considered to be unbreakable, but blockchain and identity experts are poking holes in existing data security solutions. So how do you choose among the many self-sovereign digital ID applications? Pseudonymization and security. One of the major ways of guarding the safety of data is pseudonymization, the process of keeping data separate so that it cannot be linked to the user. However, not everyone agrees on the best way to pseudonymize data. Cryptographic Hashing vs Encryption Debate Of all the technology debates centered around digital sovereign IDs (e.g., off chain vs on chain solutions, encryption technology), the industry has been particularly mobilized around a hashing versus encryption debate. has long been used to prevent web tracking services from linking personally identifiable information across data sets while still allowing services like Google Analytics to aggregate anonymous data for analysis. A hash is considered to be correlatable to data, while a decentralized identifier can be separated from the data. Hashing hashing is used by Civic, ShoCard, and ’s virtual jurisdiction, among others. The SHA256 hash turns data into a 64-digit hexadecimal signature. If one character is changed in the data, the signature changes. Cryptographic Bitnation The Civic Secure Identity Android app, for instance, collects your data, has it verified by a third party, turns it into a cryptographic hash and stores the hash on the blockchain. Civic then erases your personal data. Let’s say you then sign up to a new cryptocurrency trading or gaming platform. Civic sends your hash with your KYC validated information to the blockchain platform to verify you. Your personal data remains on your mobile device, and no third party ever needs to see it. Decentralized Identifiers (DID) are self-sovereign digital identities controlled by the owner rather than a central authority. A DID record is a key-wise pair of cryptographically secure private and public keys. Pairwise identifiers create a unique identifier, or DID, for each relationship. Only you have access to the private key that could, for example, authorize access to health care data to your insurance company or KYC compliance with a cryptocurrency trading platform. DIDs are used by Yoti, lifeID and Bridge ID, among others. Yoti, for instance, provides a similar pseudonymization service but instead of hashing your data, it scrambles it with 256-bit encryption. The consumer stores the private key on their phone, in the same way they would store the private key of their cryptocurrency wallet. Each piece of information is scrambled separately. If a data breach did occur at Yoti’s data center, thieves may obtain your driver’s license number but would not know to whom it belonged. So what are the pros and cons of these different data pseudonymizing solutions and which would be more likely to be broken by a brute force attack in which an algorithm checks all possible password combinations until it cracks into your data? Herein lies the crux of the debate that has identity and blockchain experts dividing into different camps. The big unknown is our quantum future. Is the reversibility of a hash function or private encryption code inevitable? And how soon will the supercomputers arrive? Zero Trust, Biometrics and Other Defenses The answer has huge implications for our data security. In the revenge of data consumers — the same week the Android app study revealed that 88 percent of apps shared data with Alphabet-owned entities, Civic launched Civic Connect, an Android integration tool allowing developers to integrate the Civic app into 6,000 Android apps. Only the user can provide access to personal data through biometric identification. But there are also high risks of having your entire digital life linked to one digital ID. A study from the University of Hamburg(1) has concluded that even a consumer-grade computer could reveal the pseudonymized data of hashing functions. The German hackers set out to hack phone numbers; and email, IPv4 and MAC addresses in datasets of one million, and succeeded in each data type in less than one second. Google Android users must be quaking for their data security. The DID camp has also come under fire. 256 bits can hold a lot of possible combinations of your private key but, crucially, those possibilities are finite. Yoti says a hacker would take one thousand years to break the code encrypting your data with its application. More specifically, the computing power to break AES 256-bit would require 40 supercomputers checking a billion AES keys per second, or 3×1051 years to check all possible password combinations (Wikipedia “Brute Force Attack”). The quantum computing camp argues the computing power to complete that encryption busting task is a function of economics and could arrive much sooner than estimated. While others argue that such computational power can break your crypto wallet’s private key but will fail to break a hash PII that has been sufficiently “padded.” Padding the data with long random numbers, for example, would create many input values for one output value. Let’s say an ambitious thief stumbled on technology to compress a millennium into a year of computational effort to solve for all possibilities. The victim is so rich it is worth the effort. But even then, the thief does not know which hashing string contains the real data. For related theoretical number crunching, this does not mean that the hashing or encryption solutions are necessarily weak. New branches of the PII tree are sprouting with new adaptations of this technology aimed at increasing the costs and efforts of hackers. Indeed, the German academic hackers call for more elaborate ways of pseudonymizing data to protect consumers. Let’s say someone connects your name and credit card information. On current Android apps, the thief could start shopping online with your credit line. Apps using Civic or ShoCard, however, would require biometric authentication to use the stolen numbers — a liveliness test is also conducted. Multiple fortifications are one solution. DID users like Bridge ID are further future-proofing data by using , which store data privately locally while allowing it to be trusted and authenticated globally. zero trust proofs Self-Sovereign Identity, yes, but not just now. When choosing PII solutions, users of blockchain personal identification applications should evaluate not only how data is protected against breaks today, but also in our quantum future. Additional work needs to be done in equipping PII with sufficient security guard mechanisms against threats for self-sovereign identity to become a reality we want to adopt. This article was crafted by Swish Team 💫 . We’re an innovation hub that works on impactful tech projects using blockchain, machine learning and software development in several industries. Learn more about us .

Self-Sovereign Identity: Will your universal digital ID be secure in the quantum future?

F1 Delta Time was a blockchain-based game developed by Animoca Brands that was offered to gamers, firstly in the beta form, between 2019-2022. The game went up in flames in March 2022, to much rejoicing from all NFT haters. But was this hate deserved? How much of a trainwreck was the game actually? This is my hypothetical post-mortem based on online evidence, with the aim to evaluate the value that was added to the game by implementing blockchain technologies. I haven’t played the game myself, and I honestly never cared about it, although I’ve been aware of it since 2019. At that time, I could not believe that a racing game could be built on blockchain. Now I am playing a lot of Hill Climb Racing 2, and I am completely convinced that you can build a racing game as good as Hill Climb Racing, on the blockchain. I urge Fingersoft to not take this as advice. How Exactly Does F1 Delta Time Work? From what is now possible to , F1 Delta Time was a browser racing game that utilized blockchain technology to assign exchange value to game assets. Racing is one of the most fast-paced genres by definition, and the only way blockchain could help was to support its economy. collect from YouTube participation in each race cost a relatively small amount of fungible tokens, akin to inserting a coin into the arcade machine. However, it included a certain element of skill, even if somewhat levelled down with expensive customization that followed a ‘pay-to-win’ trend. The game was ‘pay-to-play’: Initially, F1 Delta Time was built on Ethereum, which . To solve this problem, the game’s own fungible token, . can be used for participating in races and buying cars and car parts on open marketplaces based on Ethereum and Polygon. A part of the supply was airdropped directly to players, while the rest of the ‘monetary reserve’ was allocated to future prize pools and could be earned by winning races and lending out racing tracks to other players to compete. first became unusable in the summer of 2020 REVV, was introduced in September 2020 This token Surprisingly, as compared to many other ‘minor altcoins’, the price of the REVV token during its existence, although it naturally followed major cryptocurrency price trends, as well as major hype-generating events such as big sales in the first year of the game’s existence (Fig.1). has proven to be relatively stable The unique selling point of F1 Delta Time came from the official collaboration with Formula 1® and the value that was associated with the brand. This collaboration made F1 Delta Time a premium product and justified the high costs of its non-fungible tokens that represented Formula One cars and drivers. Several notable purchases have established F1 NFTs among on the already bubbling market. The first one happened in May 2019, long before the official launch of the game and even before the REVV altcoin was introduced. The buyer, then known under the name ‘ ’, , for the equivalent of $69 million from Beeple at Christie’s. the most expensive ones MetaKovan would later be revealed as Vignesh Sundaresan the same person who would later purchase the most expensive art NFT to date Back then, in 2019, MetaKovan paid the equivalent of for the unique race car in F1 Delta Time. The car had its own name ‘1-1-1’ and was all covered in digital diamonds. Notably, in his interview with Jon Jordan for the Blockchain Gaming World podcast, MetaKovan has described one more way to assign value to NFTs, to which we will return in our future cases: the value of a story. $111,000 in ETH The second, even more expensive, the sale happened in December 2020, three months after the game went public. , and he paid 9 million REVV (223,000 dollars at the time) for the token that represented a track segment for the Grand Prix of Monaco. As we already mentioned, the owner of a track segment could generate passive income by collecting a share of the racing fee when other players used this track for a race. Vignesh ‘MetaKovan’ Sundaresan was, again, the buyer There were s later, which broke the record set by MetaKovan, but we will use these two sales as most showing examples of the value of NFTs comes. other major sales of F1 NFT The question we are exploring here is how important the value of a brand is in the world of NFTs. F1 is a unique example of how this value went to zero overnight. Animoca Brands received a crushing blow to its reputation when of the 3-year licensing agreement with Formula 1 on March 15, 2022. they announced the end The game was shut down the next day, although its former players will still be able to swap their F1 Delta Time cars for other assets by July 31, 2022. The PR backlash resulted in at least a month of negative press from every gaming website beyond the crypto corner of the internet. Now, when the dust has settled, it may be that Animoca Brands is still going strong in terms of blockchain gaming - and even the assets that should be considered worthless without the power of a brand are still branded and up for sale after two months since the end of the licensing agreement. Even though the game itself can’t be played - only a line of code shows up in the browser where the playground for most expensive NFTs used to be - branded game NFTs are still available on OpenSea, available for purchase (see Fig. 3). Even the Monaco racing track that belongs to MetaKovan is still listed - to be precise, , now representing nothing but the loss of 9 million REVV, is still worth about $250,000 in May 2022. The image file still remains on the server, though, as well as all other digital images that represent deprecated game assets, and rare transactions still take place on OpenSea. the .png render of the track It may be that the value of a brand does not disappear with the end of licensing agreement. Even more, its role in the valuation of game assets may not have been as important as the critics suggest. What F1 cars and drivers have actually lost - in a rather painful way - is their utility value, that is, the ability to use assets productively in the game. For example, MetaKovan can’t generate passive income by lending out of the Monaco track segment. Of course, this .png will be deleted one day after the server clean-up, - but the same is true for many other unique and premium NFTs in many reputable projects that have, in Bondian terms, no time to die, although they may as well die another day. However, legendary and exclusive cars and drivers still retain potential exchange value: for instance, MetaKovan can still sell his 1-1-1 car on OpenSea. To make it almost actually immutable, the visualization of this car NFT on OpenSea is currently . the .png file an (unlisted) YouTube video Is F1 Really A Failure? It has been definitely painted as such in the media. However, if we look at the game statistics , it appears that the game’s popularity had been fading for many weeks already before the partnership was discontinued. available on DappRadar The number of daily players rarely exceeded 10 since September 2021 - for 6 months already - which would not be enough to continue a costly partnership with Formula 1. Of course, these are only the statistics that are publicly available at DappRadar, and they are already quite buggy, but there is no reason to suggest that the game was more popular than that. In the meantime, Animoca Brand launched its own racing game REVV Racing in August 2021, as the hype around F1 Delta Time was fading. It is very likely that the remaining players of F1 Delta Time have moved to that game even before the closure. In terms of player engagement, by far outpaced F1 Delta Time, although we do not have the data about how profitable it was for the developer or for an average player. REVV Racing As of May 2022, the collection of amounted to 167,000 items that belonged to 59,400 players. This is a success if we compare it to F1 Delta, which , and which belonged to 1,800 players, which is the cumulative number of all players during the lifetime of the game. REVV Racing cars on OpenSea only had less than 4,000 cars This large number of REVV Racing players can be explained by : everybody who had 8,000, 12,000, and 20,000 REVV tokens in their wallets would also get one, two, and three free new cars. Even though these were still considerable investments (8,000 REVV would amount to 1,137 USD at the time of airdrop, July 16, 2021), many free cars would go to the secondary market, and even more new cars would be minted and distributed later. From the viewpoint of an outsider, it looks as if the company moved from monetizing through ultra-wealthy ‘whales’ to a wider, poorer, but also more active and motivated player base. the airdrop rules Why communicate ‘deep regret’, then? The main problem with crypto games today is that, due to the rapid speed of the NFT scene, many of their creators don’t develop long term memory, so they never learn (or maybe, they are just not used to hiring the people who actually do the work of development and marketing, for the real money, on a long term basis). A similar event already happened in 2018 in CryptoKitties - the first popular blockchain-based game that also tried cooperating with sports brands at some point. In early May 2018, the company prepared to launch a marketing campaign CurryKitties, to celebrate their first NFT based on a living celebrity, the NBA player Stephen Curry. The deal was canceled at the last moment about the role of Stephen Curry in the promotional campaign. The basketball-themed kitties were already pre-programmed to be minted by smart contracts, and Stephen Curry was replaced by at the last minute. Although some fallout from the CurryKitties could be observed in social media, it was by far incomparable to the grilling that F1 Delta Time received from all kinds of media in spring 2022. due to a misunderstanding a generic character Swish Based on that, the devil’s advocate in me suggests that Animoca Brands should have communicated smugness, not regret, in their public announcement. Anything along the lines of “Formula 1 is not good enough for us” would please their core player base and provide less food for the trolls. Griefing could be easily redirected at the former partner, whose reputation is by no means squeaky clean. In the end, if the value of a brand does not convert into other types of value in this particular community of players, why keep this brand? How Important Is the F1 Disaster At All? For the company that has the word ‘Brands’ in its name, and describes its mission as bringing premium brands into the blockchain and NFT space, - yes, it is a big screw-up in terms of PR. However, their other game REVV Racing seems to be doing really well on the ‘play-to-earn’ scene, based on publicly available information. There’s no value in that brand, but the main point is that it perfectly communicates the message that sells right now: this is where you can earn minor altcoins by playing a simple racing game. As you can see, upon a very rough calculation, the price of REVV is well correlated with the number of active players. Moreover, as the new crypto winter is coming, we are about to see what will happen to the game if the price of REVV goes down. The number of active players after that will demonstrate how much of REVV’s value is utility value in the game, and how much is exchange value, boosted by speculation, lending, and borrowing, as in . the recent case of Axie Infinity Thank you for reading! We are living in a time when I don’t even want to expose my Ethereum wallet for possible donations because some of you might want to send me an exploding NFT. However, let me know if you want to see this research continued in a more academic manner. It will be even more fun to revisit this case after July 2022, when the migration of former F1 Delta Time players is finished. The statistics here are super basic and only used to illustrate very obvious trends. It would take much more effort to collect better data and produce objective conclusions, and I have to do other things right now. See you when I’m a bloody Doctor of Philosophy in Communications!

F1 Delta Time: The Value Of A Brand

Security analytics in cybersecurity is important as it helps solve major data breach problems. Companies that ignore the services of cybersecurity are vulnerable at all times. They are on the verge of destroying themselves by not opting for . Cybersecurity services can help them fight all sorts of malicious activities and frauds. From phishing emails, DDOS attacks, and Eavesdropping attacks, you name it, and the security engineers will be there to defend your assets. SOC as a service The real question, however, remains what security analytics is in cybersecurity? Security Analytics This cybersecurity approach enables the clients to have much more safety data and detects probable threats. Suh detection and protection are possible through quality data analytics and machine learning integrated into cybersecurity dashboards. plays a major role in providing quality security analytics. It gives unmatchable threat detection. This quality threat detection leads to a company having eminent security analytics in cybersecurity. SIEM as a service Security analytics in cybersecurity and threat intelligence manage to detect and analyze the data in the best way possible. The use of machine learning also helps in providing one of the finest detection and response security services. This way, external attacks become minimal, and threats are detected within seconds. Benefits Of Security Analytics This feature of security analytics in cybersecurity proves to be an important tool for businessmen willing to secure their critical assets. Unfortunately, the level of importance of security analytics is unignorable, and people often ignore its importance of security analytics. However, the following are the benefits of security analytics: 1. Quality Detection And Response Rate The security analytics feature allows quality detection; with a completely integrated dashboard, the detection and response rate of any breach becomes even quicker. Cyber security analytics analyzes data best and makes connections between events and alerts to detect probable threats. 2. Regulatory Compliance Through the feature of security analytics, business owners can stay within the rules and regulations as provided by the governing body of a state. Fulfilling compliances like HIPAA and PCI DSS is now quite easy with security analytics. Through security analytics in cybersecurity, enterprises can easily follow the rules and regulations as guided by law. Thus, a quality SOC as a service is a significant requirement today. 3. Forensic Capabilities A company with a quality security analytics system is mostly benefitting a lot. A sound security analytics system ensures insights into where the possible breach or attack occurs and from what places the cyber attackers are operating their malicious activities. Timely breaches and threat detection are possible through security analytics in cybersecurity. Components Of Security Analytics In Cybersecurity 1. Behavioral Analysis An unusual way of behaving by end users or applications shows a security break or assault. Conduct investigation concentrates on examples of client, application, and gadget conduct to distinguish peculiarities. For instance, financial institutes utilize behavioral analysis to identify credit card frauds. Moreover, the end user who signs on at 2 a.m. to get to frameworks not needed for work, or an application that starts sending strange questions and orders, could demonstrate a data breach. 2. Network examination A NAV (Network Application and Visibility) application or gadget breaks down traffic from end clients and applications as it streams across the organization. Security Analytics Platforms report from Forrester Wave depicts NAV as an assortment of devices that incorporates network revelation, stream information investigation, network metadata examination, parcel catch and examination, and organization legal sciences. 3. SOAR Security Orchestration Automation and Response (SOAR) is the arrangement center that handles correspondence between information assembling, the examination motor, and threat detection applications. The security investigation application or an outside item like security data and occasion the board (SIEM) application can give SOAR capacities. A SIEM gathers information on network traffic, framework occasions, and likely dangers. It then, at that point, carries out scientific roles, like connection and measurable investigation. 4. Criminology Security information examination arrangements give apparatuses to research past or progressing assaults, decide how the IT frameworks were compromised, and distinguish remaining weaknesses. This can assist with guaranteeing that comparable episodes don't happen from here on out. 5. External threats Threat intelligence itself isn't security investigation. Nonetheless, TI stages (TIPs) add setting to scientific interaction. For example, a security programming and administration organization might incorporate a danger knowledge feed as a component of its answer. Instances of insight taken care of are the Department of Homeland Security's free Automated Indicator Sharing (AIS) and Ransomware Tracker, a Swiss security site that spotlights following and observing the situation with space names and IP locations, and URLs that are related to ransomware.

What Is Security Analytics In Cybersecurity?

Ethereum smart contracts promise to change the way we handle sensitive data and money. The drawback is that it is but a promise for now. The technology is too new to be trusted with day-to-day business tasks. Smart contracts themselves work like Swiss watches, but every transaction costs the smart contract owner money, the Ethereum blockchain fee. The fee depends on the features and parameters of a transaction. As of now there is not a free tool that allows you to get data about transactions conducted with a smart contract in a straightforward way. You have to collect all transaction data manually, and that is not even the worst part; you also have to decode it yourself. We in Exyte decided to solve this problem. ( : ) Disclaimer The author is a full stack developer at Exyte And this is how Gaster appeared. In this article we explain how Gaster works and how the blockchain community can benefit from this tool absolutely for free. How does Gaster solve the problem of getting data about smart contract transactions? Gaster gives you info about how a smart contract has been used. It gives you raw data about transactions. For example, what methods were called, what their parameters were, and how much that transaction cost the smart contract owner. The smart contract owner analyses these data to learn: what smart contract methods are used more often what smart contract methods cost the most which users load the smart contract the most Gaster gathers all the necessary data, aggregates it in one place, and gives you many options for tuning your smart contract parameters. Why did no one make an open-source tool like that before? Well, someone actually might have a similar tool. There may even be several of them, but they are mostly for private use. There are not many public (open) smart contracts, and there are not many public (free/open) tools for smart contract analytics that anyone can use. The benefit of Gaster is that it is an Open-source tool. It is available to everyone. Anyone who has a smart contract or a dApp with a smart contract and wants to know how much money they are going to spend on using a smart contract should take advantage of Gaster. Why didn't someone share the private tool that they'd been using? It may be connected to the fact that there haven't been many dApps with smart contracts up until recently. DApp developers and smart contract owners just hadn't thought that they needed an analytics tool for their smart contracts. The technology is still in its development stage. Usually, open-source tools appear when the technology is widespread. Smart contract technology starts trending about now with . We felt that this was the time to start doing open-source projects for the community. 75% growth in March Why did you decide to work on this project? Are there any other problems with dealing with smart contracts from a business point of view? There was another thing we wanted to work on: the possibility of going back to a previous state of the network and setting up that state of the network locally. This possibility is necessary to test and analyze complex use cases of unexpected smart contract behavior. Having a tool like that would help Exyte in some of our recent projects. So we decided to write a script that would do that, transferring your local blockchain to a previous state of a public blockchain. While researching this topic, we found out that similar feature is scheduled for (previously ) in one of the upcoming milestones. OpenEthereum Parity Ethereum There weren't any other issues that needed to be addressed, so we focused on operational cost analytics. How was the issue of transaction cost analytics solved before? I cannot be certain here, because, again, there weren't any public tools that did that. Gaster is genuinely a crawler and decoder. It follows a certain logic to gather data about a smart contract through Etherscan API, taking into account the peculiarities of how a transaction was conducted. After the data is gathered, Gaster decodes it into a human-readable format and saves the outcome into a CVS. The process is quite simple, and I think if anyone needed smart contract analytics, they would follow the same logic. What was the business problem that initiated the work on Gaster? It all started with the development of smart contract for the Proof of Ownership mechanism for a real estate company. The purpose of a smart contract in that case was to confirm that a user can buy a piece of land. Among other data, smart contracts there transferred the name of that piece of land. As long as the Ethereum blockchain is sensitive to the amount of data, the length of that name directly influenced the transaction fee. We were able to discover that fact after taking a look at the data Gaster collected about that network. How does Gaster work? Gaster can collect raw transactions' data considering the specifics of its storage. With a single command, it collects, decodes, and saves all that data in CSV so you can use it for further analytics. Gaster collects the following data: smart contract addressinput data (method and its parameters) who called the smart contract block where the transaction took place transaction hash amount of gas spent gas price Of course, there are several nuances here. Blockchain transactions can have a hierarchical call structure, as if you use Zeppelin OS (proxy contract) or just call one contract inside of another one, so each smart contract has both regular transactions and related internal transactions. All of the internal transactions have their type according to what it does: create, delegatecall, staticcall, and so on. These transactions should be crawled and merged correctly in order to see the full picture of how the contract works. It is not the topic of this talk, but more information about internal transaction (message call) types can be found , , and . here here here How and where can Gaster be used? Gaster can make an automatic Python report that uses raw CSV data and makes general analytics to show how it can work. So you, as contract owner, can get useful information about the most-used functions, the most expensive functions, and how users use your contract, as well as make invoices for them and much more, presented in the form of plots and tables. The Gaster-generated plots below provide the contract owner with useful information, such as: The cost dynamics of contract methods over time Based on this data, you can forecast the future cost and identify thresholds for changes in cost for a particular method. The dynamics of cost distribution for contract methods over time You can also use this graph to determine how often the smart contract is used. The nature of changes in the average cost of smart contract methods over time This data allows you to track the use of methods and compare it with the gas price data. The gas price value set for the transaction relative to time This graph help you find a better way to adjust the gas price for the methods in the future. Bottom line We hope you will find Gaster useful for your blockchain-based projects. If you like what we did, we’d really appreciate it if you star . As for now, we are continuing our work on developing Gaster. Gaster rep on GitHub If you have any questions or suggestions, we’d be glad to hear from you! or hit us on , or . Drop us a message Twitter LinkedIn Facebook ( : ) Disclaimer The author is a full stack developer at Exyte

SWISH ANALYTICS

swishanalytics.com

-- employees

Since n.d.

COMPANY RANKING

SWISH ANALYTICS

EVERGREEN INDEX #10979

Representing this company? Click here to claim and customize this page!

Swish Analytics WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!

SWISH ANALYTICS

swishanalytics.com

-- employees

Since n.d.

COMPANY RANKING

SWISH ANALYTICS

EVERGREEN INDEX #10979

RELATED COMPANIESRANK

STORIES ABOUT SWISH ANALYTICS

Representing this company? Click here to claim and customize this page!

Swish Analytics WIKI

Apply to get your Tech Company News Page live on HackerNoon.com today!