Data Structures and Algorithms
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📈 Análisis del canal de Telegram Data Structures and Algorithms
El canal Data Structures and Algorithms (@mastersindsa) en el segmento lingüístico de Inglés es un actor destacado. Actualmente la comunidad reúne a 13 126 suscriptores, ocupando la posición 3 874 en la categoría Ventas.
📊 Métricas de audiencia y dinámica
Desde su creación el невідомо, el proyecto ha mostrado un crecimiento acelerado, reuniendo a 13 126 suscriptores.
Según los últimos datos del 02 julio, 2025, el canal mantiene una actividad estable. En los últimos 30 días la variación de miembros fue de -162, y en las últimas 24 horas de 0, conservando un alto alcance.
- Estado de verificación: No verificado
- Tasa de interacción (ER): El promedio de interacción de la audiencia es 0%. Durante las primeras 24 horas tras publicar, el contenido suele obtener N/A% de reacciones respecto al total de suscriptores.
- Alcance de las publicaciones: Cada publicación recibe en promedio 0 visualizaciones. En el primer día suele acumular 0 visualizaciones.
- Reacciones e interacción: La audiencia responde de forma activa: el promedio de reacciones por publicación es 0.
📝 Descripción y política de contenido
No se ha proporcionado la descripción del canal.
Gracias a la alta frecuencia de actualizaciones (últimos datos recibidos el 03 julio, 2025), el canal mantiene la vigencia y un amplio alcance. La analítica demuestra que la audiencia interactúa activamente con el contenido, lo que lo convierte en un punto de referencia dentro de la categoría Ventas.
13 126
Suscriptores
Sin datos24 horas
-347 días
-16230 días
Archivo de publicaciones
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>Some rules for big-oh:
1. Ignore the lower order terms.
2. Ignore the coefficients of the highest-order term.
3. NO need to specify the base of logarithm
If T1(N)=O f(N) & T2(N)=O g(N)
T1(N)+T2(N) = max( O(f(N)), O(g(N)) )
T1(N)*T2(N) = O(f(N)* g(N))
NOTE:- ⚡Bounds are for the algorithms rather than programs or problems
Different Approaches :-
1. Empirical:- run an implemented system on real-word data. Notion of benchmarks.
2. Simulation:- run an implemented system on simulated data.
3. Analytical:- use theoretic-model data with a theoretical model system.
Machine Model Assumed:
1. Instructions are executed one after another, with no concurrent operations, Not parallel computers.
2. All operations execute in one unit of time(not the case in real computers)
3. We assume we have infinite memory and hence do not worry about page faulting.
4. Our model has fixed size(say 32 bit) integers and no fancy operations like matrix inversion, sorting.
5. One disk read counts same as addition even though addition is several orders of magnitude faster.
Factors affecting the running time:
*Computer
*Compiler
*Algorithm used
*Input to the Algorithm
*Analyzing an Algorithm*
- Predicting the resources that the algorithm reset.
- Resources include :
- >Memory
- >Communication bandwidth
- >Computational time(usually most important)
What is Algorithm?
A clearly specified set of simple instructions on the data to be followed to solve a problem.
