🔬Efficiency Report for Uniswap V3

This report provides an analysis of the efficiency of Uniswap V3, focusing on key metrics such as lost value, gas burned per hour, average gas consumption, gas used variance, gas price variance, and gas used kurtosis. By examining these metrics, users and developers can gain valuable insights into the performance of the smart contract interactions, enabling them to optimize transaction timings and strategies. The report includes visualizations of data spanning a period of five days, highlighting patterns and trends in gas consumption that can help identify inefficiencies or problems in the smart contract interactions.

Lost Value

This metric represents the total amount of ETH that was locked in transactions that eventually failed. A high lost value can indicate various issues, like transaction collisions, excessive gas fees, or issues within the smart contract itself. Monitoring this can help users and developers identify inefficiencies or problems in the smart contract interactions.

Over a 5-day span, the lost value in ETH portrays fluctuating network stability. August 24th sees an upward surge, peaking at 2.62 ETH by 20:00, suggesting potential network congestion. A notable spike on August 25th, 05:00, at 4.60 ETH, hints at an unexpected network anomaly. Following this, values decline, bottoming at 0.334 ETH on August 26th, 08:00, showcasing relative network tranquility.

However, the tranquility is short-lived. Late August 28th records values consistently above 3 ETH, climaxing at a striking 5.93 ETH by midnight on August 29th, alluding to increased network stress. Post this surge, a sharp decline insinuates a return to normalcy.

In essence, while moments of stability exist, notable spikes in lost value emphasize transient network inefficiencies or heightened activities. Such patterns offer crucial insights for optimizing transaction timings and strategies.

Gas Burned Per Hour

This signifies the total ETH spent on gas fees for all transactions related to the smart contracts, irrespective of whether they succeeded or failed, on an hourly basis. A rising trend in this metric can point towards increased activity or, possibly, inefficient contract executions that require more gas.

Between August 24th and August 29th, gas consumption patterns emerge. Mid-day hours (11:00–15:00) show steady consumption with occasional spikes. However, the late afternoon to evening, from 16:00 to 21:00, sees the highest usage, often exceeding 20 units. An unusual spike occurs on August 25th at 05:00 with 34 units. The most pronounced surge is from August 28th, 16:00 to August 29th, 02:00, peaking at 40.9 units, the highest over these days. Early mornings consistently register a drop, with values often below 10 units between 02:00 and 09:00. In essence, consumption is highest in the late afternoon to evening, moderate at mid-day, and lowest in the early morning, with a notable high-consumption period on late August 28th to early August 29th.

Average Gas Consumption

A measure of how much gas, on average, the smart contracts consume for their transactions. This provides a good benchmark for understanding the efficiency of the contracts. Lower average gas consumptions typically indicate optimized contracts that are more cost-effective for users.

Analyzing the average gas usage from August 24th to 29th reveals distinct consumption patterns. Gas usage sees modest fluctuations during mid-day, but generally, it intensifies from late afternoon to early evening. Notably, the period between 16:00 and 21:00 consistently sees heightened usage, peaking on August 28th at 0.00817 units at 18:00. On the other hand, the early mornings (02:00–09:00) typically record the lowest usage, with values often dropping to around 0.002 units. The sharpest spike occurs on August 25th at 05:00, reaching 0.00649 units. From August 28th 14:00 to the early hours of August 29th, there’s a prolonged surge in consumption. This data suggests that demand for gas intensifies in late afternoons and evenings, while early mornings see a lull.

Average gas consumption for a specific function:

execute(bytes,bytes[],uint256)

This narrows down the gas consumption average to a particular function within the smart contracts. By monitoring this, one can identify if this specific function has been optimized for performance or if it is a significant gas consumer compared to other functions.

Gas usage for the execute function gradually increased over time, peaking significantly on the evening of August 28th. Despite fluctuations, an upward trend is evident, with values frequently rising in the late afternoon and evening.

Gas Used Variance

Variance gives a sense of the spread or dispersion of gas used by different transactions. A high variance means that gas consumption across transactions is spread out, suggesting that some transactions are consuming a lot more or less gas than others. Conversely, low variance indicates consistency in gas consumption across transactions.

Analyzing the gas used variance data from 2023–08–24 to 2023–08–29, several patterns emerge. The variance, representative of fluctuations in gas usage, shows significant peaks, particularly during the evening hours. The most substantial spikes in variance were on 2023–08–25 at 19:00, 2023–08–27 at 07:00, 2023–08–28 from 15:00 to 21:00, and notably, an enormous surge on 2023–08–29 at 08:00. Conversely, the period from 2023–08–26 09:00 to 2023–08–26 16:00 displayed relatively low variances, hinting at more consistent gas usage. It is also worth noting that the data presents recurring high variances around specific times, suggesting possible systematic or scheduled activities causing these fluctuations. This cyclical trend could be crucial for anticipatory measures or planning.

Gas Price Variance

This metric indicates the variability in the gas prices users are willing to pay for their transactions to be processed. High variance here might indicate a volatile gas market where prices are fluctuating significantly, whereas low variance suggests a more stable pricing environment.

Between August 24th and August 29th, the gas price variance saw multiple peaks and troughs. The most striking are the dramatic surges on August 27th at 07:00 and on August 28th, notably at 00:00, 08:00, 15:00, and 16:00. These surges often surpassed values of 400 trillion. Conversely, the period had quieter phases too, such as the hours following 13:00 on August 25th and much of August 26th morning, where variances mostly stayed below 20 trillion. The data illustrates a volatile trend over the five days, with significant oscillations indicating potential external influencing factors or anomalies in gas pricing mechanisms during these hours.

Gas Used Kurtosis

Kurtosis is a statistical measure that describes the tails of a distribution. In this context, it tells us about the extremities in gas consumption for the transactions. A high kurtosis value might indicate that there are a few transactions consuming an unusually high or low amount of gas compared to the average, whereas a low kurtosis would suggest that most transactions are close to the average in terms of gas consumption.

From the data on gas used kurtosis spanning several days, notable fluctuations are evident. High kurtosis values, often surpassing 1000, sporadically appear throughout the data set, indicating extreme outlier events. Such events are especially pronounced during early morning hours, such as 05:00 on August 26th with a peak at 2733 and 08:00 on August 28th reaching 3096. Conversely, there are intervals where kurtosis remains consistently below 50, suggesting more regular gas usage patterns. These low kurtosis periods are scattered but can be observed on August 24th from 13:00 to 17:00 and on August 25th from 13:00 to 16:00. Understanding these variations is crucial for optimizing gas distribution and anticipating potential demand spikes.

Conclusion

In conclusion, this report has provided an in-depth analysis of the efficiency of Uniswap V3, highlighting key metrics such as lost value, gas burned per hour, average gas consumption, gas used variance, gas price variance, and gas used kurtosis. The report includes visualizations of data spanning a period of five days, showcasing patterns and trends in gas consumption that can help identify inefficiencies or issues in the smart contract interactions. By examining these metrics, users and developers can gain valuable insights into the performance of the smart contract interactions, enabling them to optimize transaction timings and strategies. Overall, this report serves as a valuable tool for anyone involved in the Uniswap V3 ecosystem, providing crucial information necessary for informed decision-making.

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