Refactor documentation for various filters and indicators to enhance clarity and consistency

- Updated Bessel, Bilateral, Blma, Butter, Conv, Ema, Kama, LSMA, MAMA, MGDI, SSF, USF, ATR, ADL, and ADOSC documentation to use bullet points for key concepts and features.
- Added a new Qodana configuration file for code analysis.
- Removed coverage configuration from Quantower.Tests.csproj to streamline testing setup.

lib/channels/dchannel/dchannel.md

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+# DC: Donchian Channels
+
+## Overview and Purpose
+
+Donchian Channels are a versatile technical analysis tool developed by Richard Donchian in the mid-20th century. This indicator creates a price channel consisting of three lines: an upper band tracking the highest high over a specified period, a lower band tracking the lowest low, and a middle band representing the average of these extremes. Donchian Channels effectively visualize price volatility and potential support/resistance levels by highlighting the range within which prices have fluctuated over the lookback period.
+
+## Core Concepts
+
+* **Range identification:** Donchian Channels excel at defining dynamic support and resistance levels based on actual price extremes rather than statistical measures
+* **Market application:** Particularly effective for breakout trading strategies, trend identification, and volatility assessment across various market conditions
+* **Timeframe suitability:** **Multiple timeframes** work well, with shorter periods (10-20) for short-term trading signals and longer periods (20-55) for identifying significant support/resistance zones
+
+Donchian Channels differ from other volatility-based channels (like Bollinger Bands) by using actual price extremes rather than statistical deviations, making them especially useful for trend-following strategies and breakout systems.
+
+## Common Settings and Parameters
+
+| Parameter | Default | Function | When to Adjust |
+| --------- | ------- | -------- | -------------- |
+| Period | 20 | Controls the lookback window for calculation | Decrease for more sensitivity to recent price action, increase for more stable channels |
+| High Source | High | Data point used for upper band calculation | Change to different price data only for specific, specialized strategies |
+| Low Source | Low | Data point used for lower band calculation | Change to different price data only for specific, specialized strategies |
+
+**Pro Tip:** The "Donchian Channel Breakout" strategy, popularized by the Turtle Traders, traditionally uses a 20-day breakout for entry signals and a 10-day breakout in the opposite direction for exits. This asymmetric application often yields better results than using the same period for both.
+
+## Calculation and Mathematical Foundation
+
+**Simplified explanation:**
+Donchian Channels track the highest high and lowest low over a specified period. For each bar, the indicator identifies the highest high and lowest low over the lookback period, then calculates a middle line as the average of these two extremes.
+
+**Technical formula:**
+Upper Band = Highest High of last n periods
+Lower Band = Lowest Low of last n periods
+Middle Band = (Upper Band + Lower Band) / 2
+
+Where:
+* n is the specified lookback period
+* Highest High is the maximum high price observed during the period
+* Lowest Low is the minimum low price observed during the period
+
+> 🔍 **Technical Note:** The implementation uses monotonic deques with circular buffers for efficient calculation, maintaining O(1) time complexity for each new bar rather than repeatedly scanning the entire lookback period.
+
+## Interpretation Details
+
+Donchian Channels provide multiple trading signals and insights:
+
+* **Breakout trading:** Price breaking above the upper band signals potential bullish momentum, while breaking below the lower band indicates potential bearish momentum
+* **Range identification:** The width of the channel represents market volatility—wider channels indicate higher volatility
+* **Trend strength:** In strong trends, price tends to "walk" along either the upper or lower band
+* **Mean reversion:** The middle band often acts as a magnet for price, especially after extended moves to the outer bands
+
+Traders may also use channel width (difference between upper and lower bands) as a standalone volatility measure to adjust position sizing or identify potential market regime changes.
+
+## Limitations and Considerations
+
+* **Market conditions:** Less effective during sideways, choppy markets where repeated false breakouts may occur
+* **Lag factor:** By definition, the indicator is backward-looking and may not adapt quickly to sudden market changes
+* **False signals:** Brief price spikes can trigger false breakout signals, especially with shorter lookback periods
+* **Complementary tools:** Best combined with volume analysis, momentum indicators, or other confirmation tools to filter potential false signals
+
+## References
+
+* Schwager, J. D. (1989). Market Wizards: Interviews with Top Traders. New York: Harper & Row.
+* Faith, C. (2007). The Original Turtle Trading Rules. Original Turtles.

lib/channels/dchannel/dchannel.pine

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+// The MIT License (MIT)
+// © mihakralj
+//@version=6
+indicator("Donchian Channels (DCHANNEL)", "DCHANNEL", overlay=true)
+
+//@function Calculates the Donchian Channel (DC) efficiently using monotonic deques
+//@param hi Source series for the highest high calculation (usually high)
+//@param lo Source series for the lowest low calculation (usually low)
+//@param p Lookback period (p > 0)
+//@returns Tuple containing [basis, upper_band, lower_band]
+//@optimized Uses monotonic deque for O(1) amortized complexity per bar
+dchannel(series float hi, series float lo, simple int p) =>
+    if p <= 0
+        runtime.error("Period must be > 0")
+    var float[] hbuf = array.new_float(p, na)
+    var float[] lbuf = array.new_float(p, na)
+    var int[] hq = array.new_int()
+    var int[] lq = array.new_int()
+    int idx = bar_index % p
+    array.set(hbuf, idx, hi)
+    array.set(lbuf, idx, lo)
+    while array.size(hq) > 0 and array.get(hq, 0) <= bar_index - p
+        array.shift(hq)
+    while array.size(hq) > 0 and array.get(hbuf, array.get(hq, -1) % p) <= hi
+        array.pop(hq)
+    array.push(hq, bar_index)
+    while array.size(lq) > 0 and array.get(lq, 0) <= bar_index - p
+        array.shift(lq)
+    while array.size(lq) > 0 and array.get(lbuf, array.get(lq, -1) % p) >= lo
+        array.pop(lq)
+    array.push(lq, bar_index)
+    float top = array.get(hbuf, array.get(hq, 0) % p)
+    float bot = array.get(lbuf, array.get(lq, 0) % p)
+    [math.avg(top, bot), top, bot]
+
+// ---------- Main loop ----------
+
+// Inputs
+i_period = input.int(20, "Period", minval=1)
+i_high = input.source(high, "High Source")
+i_low = input.source(low, "Low Source")
+
+// Calculation
+[basis, upper, lower] = dchannel(i_high, i_low, i_period)
+
+// Plot
+plot(basis, "Basis", color=color.yellow, linewidth=2)
+p1 = plot(upper, "Upper", color=color.yellow, linewidth=2)
+p2 = plot(lower, "Lower", color=color.yellow, linewidth=2)
+fill(p1, p2, color=color.new(color.blue, 90), title="Band Fill")