All Tags
AWS
ai
algorithm-design
architecture
browser
cloud
cloud-efficiency
cloud-principles
cost-reduction
data-centric
data-compression
data-processing
deployment
design
documentation
edge-computing
email-sharing
energy-efficiency
energy-footprint
enterprise-optimization
green-ai
hardware
libraries
llm
locality
machine-learning
maintainability
management
measured
microservices
migration
mobile
model-optimization
model-training
multi-objective
network-traffic
parameter-tuning
performance
queries
rebuilding
scaling
services
storage-optimization
strategies
tabs
template
testing
workloads
Tactic(s) categorized as "green-software-practice"
- Avoid use of byte-code (SP)
- Batch I/O (SP)
- Code migration (SP)
- Compiler optimization (SP)
- Decrease algorithmic complexity (SP)
- Efficient GUI (SP)
- Free or unmap unneeded memory (SP)
- Keep 3rd party software up-to-date (SP)
- Lazy loading (SP)
- Less frequent or avoiding polling (SP)
- Put application to sleep (SP)
- Reduce data redundancy (SP)
- Reduce memory leaks (SP)
- Reduce QoS dynamically (SP)
- Reduce transparency and abstractions (SP)
- Static GUI (SP)
- Use asynchronous I/O (SP)
- Use efficient queries (SP)
- Use JIT compiler (SP)
- Use low-level programming (SP)
- Follow sustainability driven devops frameworks like susdevops (SP)
- Start considering sustainability dimensons from the beginning of SDLC (SP)
- Static detection of flaky tests (SP)
- Use Cloud Sources Sufficiently (SP)
- Mock highly consuming functions (SP)
- Use energy aware test suite prioritization (SP)
- Automate Code Comments Using AI (SP)
- Automate Test Case Generation Using AI (SP)
- Backends for Frontends
- Caching of Read Requests
- Distribute microservice
- Request Bundle
- Use different proxies