Pass the Salesforce Developer Plat-Arch-202 Questions and answers with Dumpstech

The correct selection is A, C, D. Inadequate negative tests commonly surface as poorly diagnosed failed Apex runs, unhandled exceptions when external systems return unexpected responses, and repeated manual requests for testers to reproduce failures. Good negative testing deliberately exercises invalid inputs and error paths with explicit assertions. From a testing perspective, the goal is deterministic evidence that the solution behaves correctly under the conditions that matter. Tests should isolate external dependencies, use controlled data, exercise positive and negative paths, and reproduce realistic volume or user behavior where required without making production the first place defects are discovered. The other options are weaker because they sacrifice isolation, realism, or repeatability and therefore make failures harder to reproduce and diagnose across environments. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (A. Developers often have to turn to the debug log for details of the failed Apex executions.; C. An Apex process runs into an un-handled exception when an HTTP callout has an unexpected status code in the response body.; D. Developers constantly ask the testers for a screenshot of the error and the exact steps of reproducing the error.). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Testing — Apex testing; test-data isolation; mocks; regression testing; performance/load testing; sandbox test strategy.

The correct selection is B. A Metadata API-formatted release artifact should be validated and deployed consistently using the Metadata API deployment mechanism. Mixing source-format and mdapi commands introduces needless conversion risk, and because quick deploy is excluded, the normal deployment must run after successful validation. From a deployment perspective, the same release should be reproducible across environments, with dependencies, metadata/data differences, API behavior, and target-org constraints identified before production. Automation is valuable because it turns deployment knowledge into a controlled process rather than relying on memory or manual reconstruction. The alternatives are less reliable because they do not provide the same controlled handling of metadata, data relationships, validation, or environment-specific dependencies. For this scenario, the decisive point is therefore the platform behavior represented by the selected option (B. Authorize to the Full sandbox org; Validate with sfdx:mdapi:deploy On successful validation, deploy with sfdx:mdapi:deploy). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Deploying — Metadata API and Tooling API; deployment validation; package/change-set deployment; data migration; dependency management.

The correct selection is A, C. Metadata deletion through deploy() requires a destructiveChanges.xml manifest identifying the components to delete and a package.xml manifest in the deployment package. purgeOnDelete controls permanent purge behavior but is not required merely to perform a destructive metadata deployment. From a deployment perspective, the same release should be reproducible across environments, with dependencies, metadata/data differences, API behavior, and target-org constraints identified before production. Automation is valuable because it turns deployment knowledge into a controlled process rather than relying on memory or manual reconstruction. The other choices either rely on manual reconstruction, use a deployment mechanism designed for a different scope, or fail to preserve dependencies and repeatability across target environments. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (A. Package.XML file.; C. DestructiveChanges.xml file.). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Deploying — Metadata API and Tooling API; deployment validation; package/change-set deployment; data migration; dependency management.

The correct selection is C, D. Partial Copy and Full sandboxes contain production-derived data and are therefore appropriate for meaningful batch-data validation. Partial Copy provides representative samples, while Full provides the highest-fidelity production dataset and is the standard choice when realistic volume and performance characteristics are required. From a testing perspective, the goal is deterministic evidence that the solution behaves correctly under the conditions that matter. Tests should isolate external dependencies, use controlled data, exercise positive and negative paths, and reproduce realistic volume or user behavior where required without making production the first place defects are discovered. The alternatives do not provide equivalent evidence: they either validate only a narrow implementation detail or depend on conditions outside the test ' s control. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (C. Partial Copy sandbox; D. Full sandbox). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Testing — Apex testing; test-data isolation; mocks; regression testing; performance/load testing; sandbox test strategy.

The correct selection is D. A burndown chart that repeatedly finishes with incomplete sprint work is direct evidence that the team is forecasting more than it can deliver. It provides an empirical record of missed commitments rather than relying on subjective management impressions. From a planning perspective, the architect must reduce uncertainty before execution by defining ownership, governance, environment purpose, prioritization, and measurable acceptance criteria. Decisions should be repeatable and visible across teams so delivery capacity, risk, and stakeholder expectations remain aligned throughout the lifecycle. The rejected options do not resolve the planning problem at its source; they either add process overhead or make assumptions that leave ownership and delivery risk unclear. For this scenario, the decisive point is therefore the platform behavior represented by the selected option (D. A burndown chart showing the team misses their forecast sprint after sprint). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Planning — governance; agile planning; environment strategy; backlog prioritization; sandbox strategy; stakeholder alignment.

The correct selection is B. This is an emergency production defect causing rapid business damage. Pairing the administrator with an architect provides a four-eyes control so the smallest safe corrective change can be reviewed live, documented, verified, and then synchronized back into source control and downstream environments. From an operating perspective, production stability depends on disciplined incident handling, environment synchronization, backup/recovery, observability, and control of configuration drift. Emergency actions can be faster than normal releases, but they still require traceability and must be reconciled back into the managed development baseline. The rejected choices do not provide a sustainable operating control because they fail to preserve traceability and synchronization after the immediate incident or environment change. For this scenario, the decisive point is therefore the platform behavior represented by the selected option (B. Pair with the administrator, and review each change as it happens). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Operating — production governance; environment drift; incident response; backup/recovery; post-refresh controls; hotfix synchronization.

The correct selection is A, C. In package development, the project source and version-control repository represent the package source of truth. Change-set development is org-centric, so the effective application state is the metadata already in the environment plus the specific delta carried by the change set. From an ALM perspective, the controlling principles are a clear source of truth, repeatable change tracking, controlled promotion, testable release artifacts, and traceability from requirement through production. Mature teams separate the lifecycle from any single tool so the process remains consistent even when the deployment mechanism changes. The rejected alternatives either describe a specific tool rather than a lifecycle capability or omit the source-control and traceability needed for repeatable enterprise delivery. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (A. In package development, the source of truth is the metadata in the package project, which makes it easy to integrate to a version control System.; C. In change set development, the source of truth is a combination of the metadata already in the environment and the content of your change Set.). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Application Lifecycle Management — ALM stages; source control; change tracking; package/org development models; CI/CD; release traceability.

The correct selection is C. Major production releases should be avoided during peak commercial periods because unexpected regressions, performance degradation, or integration failures have the greatest business impact then. A release calendar should define blackout windows while retaining a separate hotfix path for genuine emergencies. From a release perspective, approved functionality must be isolated from unfinished work and promoted through a predictable, auditable path. Release calendars, validation, stakeholder approval, rollback planning, and branch discipline reduce the risk that a technically correct change becomes an operational failure during production promotion. The other options do not create a safe production path because they ignore timing, approval, rollback, or branch synchronization requirements. For this scenario, the decisive point is therefore the platform behavior represented by the selected option (C. Avoid releasing near peak business periods.). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Releasing — release management; branching and hotfixes; production readiness; rollback strategy; seasonal releases; approvals.

The correct selection is A, C. Change sets include one flow version rather than every historical version. If an active version exists, that active version is selected; if none is active, the most recent inactive version is included, so flow activation state must be understood before migration. From a deployment perspective, the same release should be reproducible across environments, with dependencies, metadata/data differences, API behavior, and target-org constraints identified before production. Automation is valuable because it turns deployment knowledge into a controlled process rather than relying on memory or manual reconstruction. The rejected alternatives do not meet the deployment requirement because they introduce drift, ignore target-org compatibility, or substitute a convenience tool for a reproducible release artifact. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (A. When a change set with a multiple versioned flow is uploaded, it includes only the active version of the flow.; C. When a change set with a multiple versioned flow is uploaded, and no active version is available, it includes the most recent inactive version of the flow.). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Deploying — Metadata API and Tooling API; deployment validation; package/change-set deployment; data migration; dependency management.

The correct selection is A, D. A deployment rehearsal in a representative sandbox and final validation of the exact deployment package against production are the two strongest techniques for reducing last-minute release risk. They expose dependency, test, sequencing, and target-org issues before the limited go-live window. From a deployment perspective, the same release should be reproducible across environments, with dependencies, metadata/data differences, API behavior, and target-org constraints identified before production. Automation is valuable because it turns deployment knowledge into a controlled process rather than relying on memory or manual reconstruction. The other choices either rely on manual reconstruction, use a deployment mechanism designed for a different scope, or fail to preserve dependencies and repeatability across target environments. For this scenario, the decisive point is therefore the platform behavior represented by the selected options (A. Create a new sandbox and perform a test deployment to that environment.; D. Validate the final deployment package against production prior to go-live). Applying that rule consistently keeps the implementation aligned with Salesforce-supported lifecycle practices and makes the resulting change easier to review, validate, and operate across environments.

Study Guide reference: Deploying — Metadata API and Tooling API; deployment validation; package/change-set deployment; data migration; dependency management.