Development

Programming, frameworks, implementation, frontend, backend, and app development

skills in category: 66,450
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Showing 14,233–14,256 of 66,450 skills

TddATest-driven development as a judgement call rather than a doctrine: the red-green-refactor loop and what each step is actually for, the discipline of watching a test fail for the stated reason, step size, and an explicit account of where TDD pays and where test-after or characterisation is the better choice. Use when deciding whether to drive a change with tests, when starting a bug fix, when a design is hard to test and the cause is not obvious, when tests are being written after the fact to...developmentgojavaVotes: 0GitHub stars: 2
Tcp TuningAThe network stack under a JVM service: listen backlog and accept queues, Nagle and delayed ACK, socket buffer sizing against bandwidth-delay product, congestion control choice, keepalive and timeout alignment along the path, and diagnosing retransmissions and queue drops. Use when a small request/response protocol shows a stable ~40 ms latency floor, when a client throws BindException or EADDRNOTAVAIL under burst, when SYNs are dropped at peak, when one core saturates while the others idle on...developmentgojavaVotes: 0GitHub stars: 2
Task Queues And Competing ConsumersADistributing work to a pool of interchangeable workers through a queue: the lease and visibility-timeout model, and why an expired lease can duplicate work instead of failing it; sizing the timeout from processing plus prefetch wait; heartbeats and their failure mode; admission and retention bounds; priority starvation; and age, backlog, arrival and drain rate as autoscaling signals. Use when two workers process one message although nothing retried or failed, when a lease is relied on for mut...developmentrustgoVotes: 0GitHub stars: 2
Tail Latency AnalysisADiagnosing and mitigating end-to-end latency tails: defining the latency population, decomposing stage and queue time with per-request evidence, quantifying fan-out under dependence, attributing correlated JVM/OS/network/dependency events, and selecting bounded tail-tolerance mechanisms such as deadlines, partial results, hedging and load-aware routing. Use when p99/p99.9 regresses, stage percentiles do not explain an end-to-end percentile, deploys create cold tails, wide fan-out amplifies ra...developmentgojavaVotes: 0GitHub stars: 2
Structured LoggingADesigning application logs as governed event schemas: choosing events and fields, correlation and context lifecycle, exception and severity semantics, synchronous versus buffered delivery, overload/drop behavior, injection prevention, data minimization, integrity/retention and measurable cost. Use when logs require regex parsing, correlation is missing or stale across async work, events disappear under load, fields drift between services, failures are duplicated, secrets or untrusted text rea...developmentrustgoVotes: 0GitHub stars: 2
Structured ConcurrencyAStructuredTaskScope as a lifetime guarantee for a fan-out: fork, join, close, and the rule that no subtask thread outlives the block. Covers the API as it stands on each JDK — still a preview API on every released version, renamed between 25 and 26 and changed again in 27 — the Joiner completion policies, scope timeouts, nesting, and what close actually waits for. Use when writing or reviewing a parallel fan-out inside one request, when a sibling task keeps running after another failed, when ...developmenttestingapiVotes: 0GitHub stars: 2
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Streaming Pipeline TopologiesAComposable stage shapes for event-driven pipelines — copier, filter, splitter, sharder, merger — with ordering, semantic parallelism, state, shuffle and recovery boundaries; exactly-once scope across source, state and sinks; bounded joins and windows; watermarks, late-data policy, backlog versus flow control, and reproducible replay. Use when a stage is parallelised, when a join grows state without bound, when a stage re-keys the stream, when late events arrive after a window closed, when a w...developmentjavareactVotes: 0GitHub stars: 2
Stream Processing Runtime PerformanceAOperating Kafka Streams and Apache Flink for predictable throughput, state and recovery: separating their execution models, sizing partitions or operator parallelism, diagnosing backpressure, bounding native state, and relating commits or checkpoints to result visibility. Use when one partition or operator limits a pipeline, checkpoints grow or stall, RocksDB drives RSS outside the heap, exactly-once changes latency, or effective runtime configuration differs from declared settings. Generic t...developmentgojavaVotes: 0GitHub stars: 2
Stateless Service DesignAMaking a service instance disposable so replicas are interchangeable: what stateless actually means — no correctness/routing dependency on one instance's volatile history; the in-process state inventory; and session state as a placement decision between sticky routing, an external store and a signed token. Use when replicas is raised above 1, when a @Scheduled job suddenly runs N times, when a local cache disagrees between instances, when an in-memory rate-limit counter or idempotency map is ...developmentrustjavaVotes: 0GitHub stars: 2
Startup Cds Crac LeydenACutting JVM startup and warm-up while staying on the JVM: CDS and AppCDS, the Leyden AOT cache (JEP 483/514/515), CRaC checkpoint and restore and its constraints, what each mechanism actually accelerates, verifying the cache is really in use, and measuring time-to-first-good-response instead of time-to-port-open. Use when cold start hurts a serverless or autoscaled deployment, when a CI pipeline pays for hundreds of JVM launches, when a CRaC flag fails with Unrecognized VM option, when an App...developmentrustgoVotes: 0GitHub stars: 2
Sql Server PerformanceADiagnosing and tuning SQL Server 2022+ from engine evidence: waits, blocking/deadlocks, RCSI and version store, cardinality and parameter-sensitive plans, memory grants and parallelism, clustered/columnstore storage, statistics and index maintenance, tempdb/files/memory, readable replicas, and mssql-jdbc behavior. Use when the symptom or proposed change depends on SQL Server internals. Not generic single-query tuning, ORM behavior, or HikariCP sizing.developmentjavasqlVotes: 0GitHub stars: 2
Sql Query PerformanceAMaking one SQL statement fast, from its execution plan rather than a guess: reading estimated against actual rows, finding the operation that actually costs, whether a scan is wrong at all, index selectivity and composite column order, covering indexes, and the predicates that quietly disable an index. Use when a query is slow and the plan has not been read, when "add an index" is the proposed fix, when a predicate wraps the column in a function or compares mismatched types, when OFFSET pagin...developmentgosqlVotes: 0GitHub stars: 2
Slo And AlertingAEngineering service-level contracts and actionable alerting: defining user-centered SLIs and SLOs with explicit populations and windows, negotiating error-budget policy, separating request- and time-based semantics, deriving multi-window burn alerts, handling low traffic and missing data, and routing symptoms or predictive hazards by urgency and actionability. Use when an SLO is ambiguous, an SLA lacks operating margin, alert noise is high, resource thresholds page without context, or PromQL ...developmentgojavaVotes: 0GitHub stars: 2
Skill EngineeringADesigning and reviewing agent skills: scope boundaries, the SKILL.md frontmatter contract, progressive disclosure across references and scripts, explicit decision rules, and quality gates. Use when creating a new skill, when reviewing one that is too long or never activates, when deciding what belongs in SKILL.md versus a reference, or when converting an existing prompt into a skill. Does not cover packaging, versioning or distribution, and does not cover writing the domain expertise itself.developmentperformanceVotes: 0GitHub stars: 2
Simd And Vector ApiAVectorisation on the JVM: C2 SuperWord auto-vectorisation and the loop shapes that defeat it, the incubating Vector API (species, lanes, masks, loop bound and tail handling), proving that vector instructions were actually emitted, and portability and non-intrinsic fallback risks. Use when someone proposes rewriting a hot loop with jdk.incubator.vector, when a SIMD rewrite produced no measurable gain, when "the Vector API is stable since JDK 21" appears in a PR or design document, when compila...developmentgojavaVotes: 0GitHub stars: 2
Sidecar PatternAComposing a second container into the same pod to add a capability to a container you cannot or will not modify: the shared network namespace and volumes that make this different from a library, native sidecar containers (an init container with restartPolicy Always) and the startup and shutdown ordering they fix, per-container requests against pod-level QoS, and the failure matrix of a two-container pod. Use when a proxy, TLS terminator, config reloader or log shipper is added beside an appli...developmentjavanodeVotes: 0GitHub stars: 2
Sharding And PartitioningAWhether to split data across owners at all, and on which key: what sharding buys — write capacity, locality, data volume and isolation — against distributed transactions/indexes, non-local query routing, rebalancing as standing work, and a shard map that is itself a distributed system; the alternatives and their selection conditions; the shard-key scorecard and classic wrong keys. Use when sharding is proposed for future scale with no measured growth curve, when a table is called too big befo...developmentgojavaVotes: 0GitHub stars: 2
Session State StrategiesAPlacing the state that spans several requests of one conversation: client session state, server session state and database session state, plus signed tokens and external stores. Use when a multi-step wizard loses its data on the second replica, when HttpSession holds an object graph, when sticky sessions are added to keep an application working, when a rolling deploy logs everyone out, when a JWT carries mutable state or cannot be revoked, when session data is pushed into Redis without decidi...developmentrustgoVotes: 0GitHub stars: 2
Service Layer DesignADesigning the layer that fronts business logic: what an application service owns (transaction boundary, authorisation, orchestration, translation) and what it must not absorb, the difference between application and domain services, and whether the layer is warranted at all. Use when every service method is a single repository call, when a service has become where all rules accumulate, when two services call each other and transactions nest, when authorisation is spread between controller and ...developmentrustgoVotes: 0GitHub stars: 2
Serialization PerformanceAEngineering serialization cost as a system budget across encode/decode CPU, allocation and retention, wire/storage bytes, copies, buffers, compression, schema evolution, compatibility, security, and rollout. Covers format/library selection by workload and contract, streaming versus materialization, buffer ownership/backpressure, representative JMH/component/load experiments, production attribution, and mixed-version failure tests. Use when serialization is measured hot, a new wire/cache/topic...developmentrustgoVotes: 0GitHub stars: 2
Scoped ValuesAScopedValue as one-way, immutable, lexically bounded context: where/run/call, rebinding in a nested scope, inheritance by StructuredTaskScope subtasks and by nothing else, and the cases where ThreadLocal is still the right answer. Final in JDK 25 (JEP 506) after four preview rounds, with callWhere and runWhere removed along the way. Use when a ThreadLocal carries per-request context under virtual threads, when context is empty inside a forked subtask or a pool thread, when a ThreadLocal is ne...developmentjavaspringVotes: 0GitHub stars: 2
Schema Evolution And CompatibilityAWhether a given schema change is safe, in which deploy order, and what breaks when it is not: the writer/reader pair, the compatibility levels and who upgrades first, the per-format rules for Avro, Protobuf and JSON Schema, registry configuration, and catching a break in CI. Use when AvroTypeException reports a missing required field, when "Can't get the number of an unknown enum value" is thrown, when UnrecognizedPropertyException exposes an unexpected mapper policy, when auto.register.schem...developmentgojavaVotes: 0GitHub stars: 2
Scatter GatherAFanning one request out to N workers and combining answers: order-statistic latency, choosing N against tail exposure, all-of-N/first-of-N/k-of-N completion, safe hedging, partial-result completeness and watermarks, deadline propagation, and cancelling losers. Use when a keyless query fans out to every shard, when leaf dashboards are green but user-facing p99 is not, when more leaves made the request slower, when a fan-out gives no way to tell no-data from no-answer, when a hedge is proposed,...developmentjavanodeVotes: 0GitHub stars: 2
SafepointsAThe HotSpot safepoint mechanism on JDK 25: thread-local polling words and where the JIT emits polls, loop strip mining, global safepoints versus thread-local handshakes, the VM operations other than GC that stop the world, time-to-safepoint versus operation time, and reading `-Xlog:safepoint`. Use when measured p99 or p99.9 is far worse than the GC log explains, when GC logs look clean but latency does not match, when a stop-the-world pause has no GC event behind it, when JNI critical regions...developmentgojavaVotes: 0GitHub stars: 2