Reliability

FURPS+ Requirements Category — How dependably the system operates

Definition

Reliability requirements define how consistently and dependably the system performs its functions. For blockchain systems, this category expands significantly to include safety (the system never does something wrong) and liveness (the system eventually does something right).

Role in the Framework

Reliability requirements are particularly critical in decentralized systems where failures can result in lost funds, consensus splits, or network halts.

Reliability Requirements (including Safety & Liveness)
    ↓
Prose Specification ← documents guarantees and failure modes
    ↓
Executable Specification ← implements recovery logic, state machines
    ↓
Test Fixtures ← generates fault injection tests
    ↓
Conformance Tests ← verifies reliability properties

Core Subcategories

Availability

System uptime and accessibility:

Target availability percentage (e.g., 99.9%)
Planned maintenance windows
Degraded operation modes

Recoverability

Ability to restore correct operation after failures:

State recovery mechanisms
Transaction replay
Checkpoint/restore capabilities

Fault Tolerance

Behavior in presence of failures:

Byzantine fault tolerance thresholds
Network partition handling
Message loss recovery

Data Integrity

Protection against data corruption:

Checksums and verification
Merkle proofs
State consistency guarantees

Blockchain-Critical: Safety and Liveness

Traditional FURPS+ reliability is insufficient for consensus systems. Two properties become paramount:

Safety

“Nothing bad ever happens” — The system never produces incorrect results.

Safety Property	Meaning
Agreement	No two honest nodes finalize conflicting transactions
Validity	Only valid transactions are finalized
Integrity	Finalized state accurately reflects executed transactions

## REL-SAFETY-1: Transaction Finality Safety
 
Once a transaction is finalized:
- REL-SAFETY-1.1: No reorganization SHALL reverse the transaction
- REL-SAFETY-1.2: All honest nodes SHALL agree on the transaction's effects
- REL-SAFETY-1.3: The transaction's state changes SHALL be permanent

Liveness

“Something good eventually happens” — The system makes progress.

Liveness Property	Meaning
Termination	Valid transactions eventually finalize
Progress	The chain continues to grow
Censorship Resistance	Valid transactions cannot be excluded indefinitely

## REL-LIVE-1: Transaction Inclusion Liveness
 
For any valid transaction submitted to the network:
- REL-LIVE-1.1: The transaction SHALL be included within N blocks 
  under normal network conditions
- REL-LIVE-1.2: If network partitions heal, pending transactions 
  SHALL eventually be processed
- REL-LIVE-1.3: No single entity SHALL be able to prevent inclusion
  indefinitely

The Safety-Liveness Tradeoff

The FLP impossibility theorem proves that in asynchronous networks with potential failures, you cannot guarantee both safety and liveness simultaneously. Specifications must document the tradeoff:

## REL-TRADEOFF-1: Consensus Properties Under Partition
 
During network partition:
- REL-TRADEOFF-1.1: The system SHALL prioritize safety over liveness
- REL-TRADEOFF-1.2: Blocks MAY stop being finalized
- REL-TRADEOFF-1.3: When partition heals, liveness SHALL resume
- REL-TRADEOFF-1.4: No conflicting finalization SHALL occur

Relationship to Specifications

Prose Specification

Documents reliability guarantees and failure modes:

## REL-3.1: Message Delivery Guarantees
 
The protocol provides at-least-once delivery semantics:
- REL-3.1.1: Messages MAY be delivered multiple times
- REL-3.1.2: Receivers MUST handle duplicate messages idempotently
- REL-3.1.3: Messages SHALL NOT be silently dropped under normal conditions
- REL-3.1.4: Network partitions MAY cause temporary message loss
 
Failure Modes:
- FM-3.1.1: Network timeout → retry with exponential backoff
- FM-3.1.2: Invalid message → reject and log
- FM-3.1.3: Resource exhaustion → apply backpressure

Executable Specification

Implements recovery logic and state machines:

class MessageHandler:
    """
    Implements REL-3.1: Message Delivery Guarantees
    """
    def __init__(self):
        self.seen_messages: Set[MessageId] = set()
    
    def handle_message(self, msg: Message) -> None:
        # REL-3.1.2: Idempotent handling
        if msg.id in self.seen_messages:
            return  # Duplicate, safe to ignore
        
        self.seen_messages.add(msg.id)
        self.process(msg)
    
    def send_with_retry(self, msg: Message, max_retries: int = 3) -> bool:
        """
        Implements FM-3.1.1: Retry with exponential backoff
        """
        for attempt in range(max_retries):
            try:
                self.transport.send(msg)
                return True
            except Timeout:
                delay = 2 ** attempt  # Exponential backoff
                time.sleep(delay)
        return False

Downstream Dependencies

Downstream Document	What It Derives
Test Fixtures	Fault injection scenarios, partition tests
Conformance Tests	Safety and liveness verification
Operations Guides	Failure mode handling procedures
Architecture Docs	Fault tolerance design rationale
Audit Trails	Reliability incident history

Quality Criteria

Bounded: Failure probabilities are quantified
Recoverable: Every failure mode has a recovery path
Observable: Failures are detectable and diagnosable
Documented: All guarantees and limitations are explicit
Tested: Reliability properties are verified under stress

Best Practices

Explicitly state safety vs. liveness tradeoffs
Document failure modes alongside success paths
Include Byzantine fault scenarios in specifications
Specify recovery procedures in executable form
Test reliability through chaos engineering approaches
Make reliability guarantees version-specific (they may change with upgrades)

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