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1. unclesp1d3r

   added this to the v0.1 milestone on Sep 30, 2025
2. unclesp1d3r

   self-assigned this

   on Sep 30, 2025
3. unclesp1d3r

   added

   area:analyzerBinary analyzer functionalityBinary analyzer functionality

   type:enhancementNew feature or requestNew feature or request

   status:backlogTask in backlogTask in backlog

   lang:rustRust implementationRust implementation

   needs:testsNeeds test coverageNeeds test coverage

   on Sep 30, 2025
4. unclesp1d3r

   added a parent issue on Sep 30, 2025

   • Implement String Ranking Engine with Configurable Scoring System #21
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   unclesp1d3r

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   @coderabbitai Enhance this issue body with additional context and a proposed solution. Improve the issue title and assign the proper labels and other metadata.

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7. coderabbitai

   changed the title [-]Semantic Boost Scoring[/-] [+]Implement Semantic Boost Scoring for String Ranking[/+] on Nov 10, 2025
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   🧩 Analysis chain

   🏁 Script executed:

   #!/bin/bash
   # Read the current issue details
   gh issue view 23 --json title,body,labels,assignees,milestone,state
   
   # Search for ranking-related code
   echo "=== Searching for ranking system code ==="
   rg -n --type=rust -C3 "rank|boost|score" -g '!target/**' -g '!**/test/**' | head -100
   
   # Search for tag types
   echo "=== Searching for tag types ==="
   rg -n --type=rust -C3 "Tag|TagType" -g '!target/**' | head -100
   
   # Find semantic-related code
   echo "=== Searching for semantic code ==="
   rg -n --type=rust -C3 "semantic" -g '!target/**' | head -50
   
   # Look for requirements documentation
   echo "=== Searching for requirements ==="
   fd -t f "requirement|spec|design" -e md -e txt
   
   # Check for existing boost or scoring implementations
   echo "=== Searching for boost/scoring implementations ==="
   ast-grep --pattern 'fn $_(boost: $_) {
     $$$
   }'
   

   Length of output: 3228

   ---

   🏁 Script executed:

   #!/bin/bash
   # Get complete Tag enum definition
   echo "=== Complete Tag enum definition ==="
   ast-grep --pattern 'pub enum Tag {
     $$$
   }'
   
   # Search for import/export related code
   echo "=== Searching for import/export code ==="
   rg -n --type=rust -C3 "Import|Export" -g '!target/**'
   
   # Look for StringSource definition
   echo "=== StringSource definition ==="
   ast-grep --pattern 'pub enum StringSource {
     $$$
   }'
   
   # Check for any existing scoring or ranking logic
   echo "=== Searching for scoring logic ==="
   rg -n --type=rust "score\s*=" -g '!target/**' -g '!**/test/**'
   
   # Look for requirements or design documents in the repo
   echo "=== Searching for documentation ==="
   fd -t f . -e md | head -20
   
   # Check README for context
   echo "=== README content ==="
   cat README.md 2>/dev/null || echo "No README.md found"
   

   Length of output: 22021

   ---

   🏁 Script executed:

   #!/bin/bash
   # Read the ranking documentation
   echo "=== Ranking Documentation ==="
   cat docs/src/ranking.md
   
   # Check for requirements or specifications
   echo -e "\n=== Looking for requirements documentation ==="
   cat concept.md
   
   # Check if there's a tasks or implementation plan
   echo -e "\n=== Looking for implementation plan ==="
   fd tasks.md
   cat .kiro/specs/stringy-binary-analyzer/tasks.md 2>/dev/null || echo "No tasks.md found in expected location"
   
   # Check for any existing test files that might give context
   echo -e "\n=== Checking for existing test structure ==="
   fd -t f test -e rs | head -10
   

   Length of output: 27700

   ---

   Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty

   
   This issue focuses on implementing the **SemanticBoost** component, which increases scores for strings that match known patterns indicating high analytical value.
   
   ## Current State
   
   - ✅ Core data types defined (`Tag` enum, `FoundString` struct with `score` field)
   - ✅ Container parsers extract strings with semantic tags
   - ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource
   - ❌ No scoring implementation exists yet
   - ❌ Semantic boost calculation not implemented
   
   ## Proposed Implementation
   
   ### Base Boost Values by Tag Type
   
   Create boost calculation based on tag categories:
   
   | Tag Category | Boost | Tags |
   |-------------|-------|------|
   | Network | +25 | `Url`, `Domain`, `IPv4`, `IPv6` |
   | Identifiers | +20 | `Guid`, `Email` |
   | File System | +15 | `FilePath`, `RegistryPath`, `UserAgent` |
   | Version/Manifest | +12 | `Version`, `Manifest` |
   | Code Artifacts | +10 | `FormatString`, `Base64` |
   | Symbols | +8 | `Import`, `Export` |
   | Resources | +5 | `Resource` |
   
   ### Multi-Tag Bonuses
   
   Strings with multiple semantic tags receive additional boosts with diminishing returns:
   - Additional bonus: `(tags.len() - 1) * 3`
   - Example: String with both `Url` and `Domain` tags gets base boost of 25 + 25 + 3 = 53
   
   ### Context-Aware Adjustments
   
   Apply contextual multipliers based on string source:
   
   1. **High-value section boost**: +20% for strings in `StringData` or `Resources` sections
   2. **Symbol context boost**: +5 for strings from `ImportName` or `ExportName` sources
   
   ### Implementation Structure
   
   ```rust
   // src/classification/ranking.rs
   
   pub struct RankingEngine {
       config: RankingConfig,
   }
   
   impl RankingEngine {
       /// Calculate semantic boost for a string based on its tags and context
       pub fn calculate_semantic_boost(&self, tags: &[Tag], source: &StringSource) -> i32 {
           let base_boost = self.calculate_base_boost(tags);
           let multi_tag_bonus = self.calculate_multi_tag_bonus(tags);
           let context_boost = self.apply_context_boost(base_boost, source);
           
           base_boost + multi_tag_bonus + context_boost
       }
   
       fn calculate_base_boost(&self, tags: &[Tag]) -> i32 {
           tags.iter().map(|tag| self.get_tag_boost(tag)).sum()
       }
   
       fn calculate_multi_tag_bonus(&self, tags: &[Tag]) -> i32 {
           if tags.len() > 1 {
               (tags.len() as i32 - 1) * 3
           } else {
               0
           }
       }
   
       fn get_tag_boost(&self, tag: &Tag) -> i32 {
           match tag {
               Tag::Url | Tag::Domain | Tag::IPv4 | Tag::IPv6 => 25,
               Tag::Guid | Tag::Email => 20,
               Tag::FilePath | Tag::RegistryPath | Tag::UserAgent => 15,
               Tag::Version | Tag::Manifest => 12,
               Tag::FormatString | Tag::Base64 => 10,
               Tag::Import | Tag::Export => 8,
               Tag::Resource => 5,
           }
       }
   
       fn apply_context_boost(&self, base_boost: i32, source: &StringSource) -> i32 {
           match source {
               StringSource::ImportName | StringSource::ExportName => 5,
               _ => 0,
           }
       }
   }
   

   Acceptance Criteria

   • calculate_semantic_boost() function implemented in src/classification/ranking.rs
   • All 15 tag types have correct boost values assigned
   • Multi-tag bonus calculation works correctly
   • Context-aware boost adjustments applied for import/export sources
   • Unit tests cover all tag types and combinations
   • Unit tests verify multi-tag bonus calculation
   • Unit tests verify context-aware adjustments
   • Edge cases tested: no tags, single tag, multiple tags
   • Documentation added with examples

   Testing Requirements

   Unit Tests

   1. Individual tag boosts: Test each tag type returns correct base value
   2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags
   3. Context adjustments: Test import/export source boosts
   4. Edge cases:
      • Empty tag vector
      • Single tag (no multi-tag bonus)
      • Maximum tag combination
   5. Configurable weights: Test custom boost configurations

   Test Examples

   #[test]
   fn test_url_tag_boost() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url];
       let boost = engine.calculate_base_boost(&tags);
       assert_eq!(boost, 25);
   }
   
   #[test]
   fn test_multi_tag_bonus() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url, Tag::Domain];
       let bonus = engine.calculate_multi_tag_bonus(&tags);
       assert_eq!(bonus, 3); // (2-1) * 3
   }
   
   #[test]
   fn test_import_context_boost() {
       let engine = RankingEngine::default();
       let boost = engine.apply_context_boost(25, &StringSource::ImportName);
       assert_eq!(boost, 5);
   }

   Dependencies

   • Blocked by: Implement Encoding Confidence Scoring and Integrate Section Weights into Ranking System #22 (Ranking System Foundation) - need RankingEngine struct and configuration
   • Related to: Classification module implementation
   • Enables: Complete ranking algorithm implementation

   Technical Notes

   • Boost values are based on analytical value for malware analysis and binary reverse engineering
   • Network indicators (URLs, IPs) receive highest boost as they're often IoCs
   • Symbol names (imports/exports) are valuable for API usage analysis
   • Context-aware boosts help prioritize strings found in high-signal locations

   Requirements

   • 5.2: Semantic boost calculation
   • 5.4: Import/export name boost scoring

   References

   • Ranking Algorithm Documentation
   • Implementation Plan - Task 11.2

   Task-ID

   stringy-analyzer/semantic-boost-scoring
   EOF

   Update the issue

   gh issue edit 23
   --title "$TITLE"
   --body "$BODY"

   echo "Issue #23 updated successfully"

   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Update the issue with enhanced content

   Enhanced title

   TITLE="Implement Semantic Boost Scoring for String Ranking"

   Enhanced body with comprehensive context

   read -r -d '' BODY << 'EOF'

   Summary

   Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings.

   Background

   The ranking algorithm combines multiple factors to produce a relevance score:

   
   Length of output: 92
   
   ---
   
   Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty
   

   This issue focuses on implementing the SemanticBoost component, which increases scores for strings that match known patterns indicating high analytical value.

   Current State

   • ✅ Core data types defined (Tag enum, FoundString struct with score field)
   • ✅ Container parsers extract strings with semantic tags
   • ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource
   • ❌ No scoring implementation exists yet
   • ❌ Semantic boost calculation not implemented

   Proposed Implementation

   Base Boost Values by Tag Type

   Create boost calculation based on tag categories:

   Tag Category	Boost	Tags
   Network	+25	Url, Domain, IPv4, IPv6
   Identifiers	+20	Guid, Email
   File System	+15	FilePath, RegistryPath, UserAgent
   Version/Manifest	+12	Version, Manifest
   Code Artifacts	+10	FormatString, Base64
   Symbols	+8	Import, Export
   Resources	+5	Resource

   Multi-Tag Bonuses

   Strings with multiple semantic tags receive additional boosts with diminishing returns:

   • Additional bonus: (tags.len() - 1) * 3
   • Example: String with both Url and Domain tags gets base boost of 25 + 25 + 3 = 53

   Context-Aware Adjustments

   Apply contextual multipliers based on string source:

   1. High-value section boost: +20% for strings in StringData or Resources sections
   2. Symbol context boost: +5 for strings from ImportName or ExportName sources

   Implementation Structure

   // src/classification/ranking.rs
   
   pub struct RankingEngine {
       config: RankingConfig,
   }
   
   impl RankingEngine {
       /// Calculate semantic boost for a string based on its tags and context
       pub fn calculate_semantic_boost(&self, tags: &[Tag], source: &StringSource) -> i32 {
           let base_boost = self.calculate_base_boost(tags);
           let multi_tag_bonus = self.calculate_multi_tag_bonus(tags);
           let context_boost = self.apply_context_boost(base_boost, source);
           
           base_boost + multi_tag_bonus + context_boost
       }
   
       fn calculate_base_boost(&self, tags: &[Tag]) -> i32 {
           tags.iter().map(|tag| self.get_tag_boost(tag)).sum()
       }
   
       fn calculate_multi_tag_bonus(&self, tags: &[Tag]) -> i32 {
           if tags.len() > 1 {
               (tags.len() as i32 - 1) * 3
           } else {
               0
           }
       }
   
       fn get_tag_boost(&self, tag: &Tag) -> i32 {
           match tag {
               Tag::Url | Tag::Domain | Tag::IPv4 | Tag::IPv6 => 25,
               Tag::Guid | Tag::Email => 20,
               Tag::FilePath | Tag::RegistryPath | Tag::UserAgent => 15,
               Tag::Version | Tag::Manifest => 12,
               Tag::FormatString | Tag::Base64 => 10,
               Tag::Import | Tag::Export => 8,
               Tag::Resource => 5,
           }
       }
   
       fn apply_context_boost(&self, base_boost: i32, source: &StringSource) -> i32 {
           match source {
               StringSource::ImportName | StringSource::ExportName => 5,
               _ => 0,
           }
       }
   }

   Acceptance Criteria

   • calculate_semantic_boost() function implemented in src/classification/ranking.rs
   • All 15 tag types have correct boost values assigned
   • Multi-tag bonus calculation works correctly
   • Context-aware boost adjustments applied for import/export sources
   • Unit tests cover all tag types and combinations
   • Unit tests verify multi-tag bonus calculation
   • Unit tests verify context-aware adjustments
   • Edge cases tested: no tags, single tag, multiple tags
   • Documentation added with examples

   Testing Requirements

   Unit Tests

   1. Individual tag boosts: Test each tag type returns correct base value
   2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags
   3. Context adjustments: Test import/export source boosts
   4. Edge cases:
      • Empty tag vector
      • Single tag (no multi-tag bonus)
      • Maximum tag combination
   5. Configurable weights: Test custom boost configurations

   Test Examples

   #[test]
   fn test_url_tag_boost() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url];
       let boost = engine.calculate_base_boost(&tags);
       assert_eq!(boost, 25);
   }
   
   #[test]
   fn test_multi_tag_bonus() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url, Tag::Domain];
       let bonus = engine.calculate_multi_tag_bonus(&tags);
       assert_eq!(bonus, 3); // (2-1) * 3
   }
   
   #[test]
   fn test_import_context_boost() {
       let engine = RankingEngine::default();
       let boost = engine.apply_context_boost(25, &StringSource::ImportName);
       assert_eq!(boost, 5);
   }

   Dependencies

   • Blocked by: Ranking System Foundation - need RankingEngine struct and configuration
   • Related to: Classification module implementation
   • Enables: Complete ranking algorithm implementation

   Technical Notes

   • Boost values are based on analytical value for malware analysis and binary reverse engineering
   • Network indicators (URLs, IPs) receive highest boost as they're often IoCs
   • Symbol names (imports/exports) are valuable for API usage analysis
   • Context-aware boosts help prioritize strings found in high-signal locations

   Requirements

   • 5.2: Semantic boost calculation
   • 5.4: Import/export name boost scoring

   References

   • Ranking Algorithm Documentation
   • Implementation Plan - Task 11.2

   Task-ID

   stringy-analyzer/semantic-boost-scoring
   ENDOFFILE

   Update the issue with the new title and body

   gh issue edit 23
   --title "Implement Semantic Boost Scoring for String Ranking"
   --body-file /tmp/issue_body.md

   echo "✓ Issue title and body updated"

   Add priority:high label if not already present

   gh issue edit 23 --add-label "priority:high"

   echo "✓ Labels updated"

   Show the updated issue

   echo ""
   echo "=== Updated Issue ==="
   gh issue view 23

   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Create enhanced issue body in a temporary file

   cat > /tmp/issue_body.md << 'ENDOFFILE'

   Summary

   Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings.

   Background

   The ranking algorithm combines multiple factors to produce a relevance score:

   
   Length of output: 98
   
   ---
   
   Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty
   

   This issue focuses on implementing the SemanticBoost component, which increases scores for strings that match known patterns indicating high analytical value.

   Current State

   • ✅ Core data types defined (Tag enum, FoundString struct with score field)
   • ✅ Container parsers extract strings with semantic tags
   • ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource
   • ❌ No scoring implementation exists yet
   • ❌ Semantic boost calculation not implemented

   Proposed Implementation

   Base Boost Values by Tag Type

   Create boost calculation based on tag categories:

   Tag Category	Boost	Tags
   Network	+25	Url, Domain, IPv4, IPv6
   Identifiers	+20	Guid, Email
   File System	+15	FilePath, RegistryPath, UserAgent
   Version/Manifest	+12	Version, Manifest
   Code Artifacts	+10	FormatString, Base64
   Symbols	+8	Import, Export
   Resources	+5	Resource

   Multi-Tag Bonuses

   Strings with multiple semantic tags receive additional boosts with diminishing returns:

   • Additional bonus: (tags.len() - 1) * 3
   • Example: String with both Url and Domain tags gets base boost of 25 + 25 + 3 = 53

   Context-Aware Adjustments

   Apply contextual multipliers based on string source:

   1. High-value section boost: +20% for strings in StringData or Resources sections
   2. Symbol context boost: +5 for strings from ImportName or ExportName sources

   Implementation Structure

   // src/classification/ranking.rs
   
   pub struct RankingEngine {
       config: RankingConfig,
   }
   
   impl RankingEngine {
       /// Calculate semantic boost for a string based on its tags and context
       pub fn calculate_semantic_boost(&self, tags: &[Tag], source: &StringSource) -> i32 {
           let base_boost = self.calculate_base_boost(tags);
           let multi_tag_bonus = self.calculate_multi_tag_bonus(tags);
           let context_boost = self.apply_context_boost(base_boost, source);
           
           base_boost + multi_tag_bonus + context_boost
       }
   
       fn calculate_base_boost(&self, tags: &[Tag]) -> i32 {
           tags.iter().map(|tag| self.get_tag_boost(tag)).sum()
       }
   
       fn calculate_multi_tag_bonus(&self, tags: &[Tag]) -> i32 {
           if tags.len() > 1 {
               (tags.len() as i32 - 1) * 3
           } else {
               0
           }
       }
   
       fn get_tag_boost(&self, tag: &Tag) -> i32 {
           match tag {
               Tag::Url | Tag::Domain | Tag::IPv4 | Tag::IPv6 => 25,
               Tag::Guid | Tag::Email => 20,
               Tag::FilePath | Tag::RegistryPath | Tag::UserAgent => 15,
               Tag::Version | Tag::Manifest => 12,
               Tag::FormatString | Tag::Base64 => 10,
               Tag::Import | Tag::Export => 8,
               Tag::Resource => 5,
           }
       }
   
       fn apply_context_boost(&self, base_boost: i32, source: &StringSource) -> i32 {
           match source {
               StringSource::ImportName | StringSource::ExportName => 5,
               _ => 0,
           }
       }
   }

   Acceptance Criteria

   • calculate_semantic_boost() function implemented in src/classification/ranking.rs
   • All 15 tag types have correct boost values assigned
   • Multi-tag bonus calculation works correctly
   • Context-aware boost adjustments applied for import/export sources
   • Unit tests cover all tag types and combinations
   • Unit tests verify multi-tag bonus calculation
   • Unit tests verify context-aware adjustments
   • Edge cases tested: no tags, single tag, multiple tags
   • Documentation added with examples

   Testing Requirements

   Unit Tests

   1. Individual tag boosts: Test each tag type returns correct base value
   2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags
   3. Context adjustments: Test import/export source boosts
   4. Edge cases:
      • Empty tag vector
      • Single tag (no multi-tag bonus)
      • Maximum tag combination
   5. Configurable weights: Test custom boost configurations

   Test Examples

   #[test]
   fn test_url_tag_boost() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url];
       let boost = engine.calculate_base_boost(&tags);
       assert_eq!(boost, 25);
   }
   
   #[test]
   fn test_multi_tag_bonus() {
       let engine = RankingEngine::default();
       let tags = vec![Tag::Url, Tag::Domain];
       let bonus = engine.calculate_multi_tag_bonus(&tags);
       assert_eq!(bonus, 3); // (2-1) * 3
   }
   
   #[test]
   fn test_import_context_boost() {
       let engine = RankingEngine::default();
       let boost = engine.apply_context_boost(25, &StringSource::ImportName);
       assert_eq!(boost, 5);
   }

   Dependencies

   • Blocked by: Ranking System Foundation - need RankingEngine struct and configuration
   • Related to: Classification module implementation
   • Enables: Complete ranking algorithm implementation

   Technical Notes

   • Boost values are based on analytical value for malware analysis and binary reverse engineering
   • Network indicators (URLs, IPs) receive highest boost as they're often IoCs
   • Symbol names (imports/exports) are valuable for API usage analysis
   • Context-aware boosts help prioritize strings found in high-signal locations

   Requirements

   • 5.2: Semantic boost calculation
   • 5.4: Import/export name boost scoring

   References

   • Ranking Algorithm Documentation
   • Implementation Plan - Task 11.2

   Task-ID

   stringy-analyzer/semantic-boost-scoring
   """

   Write to temp file

   with open('/tmp/issue_body.txt', 'w') as f:
   f.write(issue_body)

   print("Issue body file created successfully")
   PYTHONEOF

   Now update the issue using the file

   gh issue edit 23
   --title "Implement Semantic Boost Scoring for String Ranking"
   --body-file /tmp/issue_body.txt

   echo ""
   echo "✓ Issue #23 updated with enhanced title and body"

   Add priority:high label

   gh issue edit 23 --add-label "priority:high" 2>/dev/null || echo "Note: priority:high label may not exist or is already applied"

   echo "✓ Attempted to add priority:high label"

   Display the updated issue

   echo ""
   echo "=== Updated Issue Preview ==="
   gh issue view 23 --json title,body,labels,assignees | jq -r '
   "Title: (.title)\n",
   "Labels: (.labels | map(.name) | join(", "))\n",
   "Assignees: (.assignees | map(.login) | join(", "))\n",
   "Body (first 500 chars):\n(.body[0:500])..."
   '

   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Create the enhanced issue body using Python to avoid here-doc issues

   python3 << 'PYTHONEOF'
   import subprocess
   import json

   issue_body = """## Summary

   Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings.

   Background

   The ranking algorithm combines multiple factors to produce a relevance score:

   
   Length of output: 250
   
   ---
   
   Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty
   

   This issue focuses on implementing the SemanticBoost component, which increases scores for strings that match known patterns indicating high analytical value.

   Current State

   • ✅ Core data types defined (Tag enum, FoundString struct with score field)
   • ✅ Container parsers extract strings with semantic tags
   • ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource
   • ❌ No scoring implementation exists yet
   • ❌ Semantic boost calculation not implemented

   Proposed Implementation

   Base Boost Values by Tag Type

   Create boost calculation based on tag categories:

   Tag Category	Boost	Tags
   Network	+25	Url, Domain, IPv4, IPv6
   Identifiers	+20	Guid, Email
   File System	+15	FilePath, RegistryPath, UserAgent
   Version/Manifest	+12	Version, Manifest
   Code Artifacts	+10	FormatString, Base64
   Symbols	+8	Import, Export
   Resources	+5	Resource

   Multi-Tag Bonuses

   Strings with multiple semantic tags receive additional boosts with diminishing returns:

   • Additional bonus: (tags.len() - 1) * 3
   • Example: String with both Url and Domain tags gets base boost of 25 + 25 + 3 = 53

   Context-Aware Adjustments

   Apply contextual multipliers based on string source:

   1. High-value section boost: +20% for strings in StringData or Resources sections
   2. Symbol context boost: +5 for strings from ImportName or ExportName sources

   Implementation Structure

   // src/classification/ranking.rs
   
   pub struct RankingEngine {
       config: RankingConfig,
   }
   
   impl RankingEngine {
       /// Calculate semantic boost for a string based on its tags and context
       pub fn calculate_semantic_boost(&self, tags: &[Tag], source: &StringSource) -> i32 {
           let base_boost = self.calculate_base_boost(tags);
           let multi_tag_bonus = self.calculate_multi_tag_bonus(tags);
           let context_boost = self.apply_context_boost(base_boost, source);
           
           base_boost + multi_tag_bonus + context_boost
       }
   
       fn calculate_base_boost(&self, tags: &[Tag]) -> i32 {
           tags.iter().map(|tag| self.get_tag_boost(tag)).sum()
       }
   
       fn calculate_multi_tag_bonus(&self, tags: &[Tag]) -> i32 {
           if tags.len() > 1 {
               (tags.len() as i32 - 1) * 3
           } else {
               0
           }
       }
   
       fn get_tag_boost(&self, tag: &Tag) -> i32 {
           match tag {
               Tag::Url | Tag::Domain | Tag::IPv4 | Tag::IPv6 => 25,
               Tag::Guid | Tag::Email => 20,
               Tag::FilePath | Tag::RegistryPath | Tag::UserAgent => 15,
               Tag::Version | Tag::Manifest => 12,
               Tag::FormatString | Tag::Base64 => 10,
               Tag::Import | Tag::Export => 8,
               Tag::Resource => 5,
           }
       }
   
       fn apply_context_boost(&self, base_boost: i32, source: &StringSource) -> i32 {
           match source {
               StringSource::ImportName | StringSource::ExportName => 5,
               _ => 0,
           }
       }
   }

   Acceptance Criteria

   • calculate_semantic_boost() function implemented in src/classification/ranking.rs
   • All 15 tag types have correct boost values assigned
   • Multi-tag bonus calculation works correctly
   • Context-aware boost adjustments applied for import/export sources
   • Unit tests cover all tag types and combinations
   • Unit tests verify multi-tag bonus calculation
   • Unit tests verify context-aware adjustments
   • Edge cases tested: no tags, single tag, multiple tags
   • Documentation added with examples

   Testing Requirements

   Unit Tests

   1. Individual tag boosts: Test each tag type returns correct base value
   2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags
   3. Context adjustments: Test import/export source boosts
   4. Edge cases: Empty tag vector, Single tag (no multi-tag bonus), Maximum tag combination
   5. Configurable weights: Test custom boost configurations

   Dependencies

   • Blocked by: Ranking System Foundation - need RankingEngine struct and configuration
   • Related to: Classification module implementation
   • Enables: Complete ranking algorithm implementation

   Technical Notes

   • Boost values are based on analytical value for malware analysis and binary reverse engineering
   • Network indicators (URLs, IPs) receive highest boost as they are often IoCs
   • Symbol names (imports/exports) are valuable for API usage analysis
   • Context-aware boosts help prioritize strings found in high-signal locations

   Requirements

   • 5.2: Semantic boost calculation
   • 5.4: Import/export name boost scoring

   References

   • Ranking Algorithm Documentation
   • Implementation Plan - Task 11.2

   Task-ID

   stringy-analyzer/semantic-boost-scoring'

   echo ""
   echo "✓ Issue #23 title and body updated successfully"
   echo ""

   Try to add priority:high label

   gh issue edit 23 --add-label "priority:high" 2>&1 || echo "Note: Could not add priority:high label (may not exist)"

   echo ""
   echo "=== Viewing Updated Issue ==="
   gh issue view 23

   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Write the issue body directly using gh issue edit with --body flag

   gh issue edit 23
   --title "Implement Semantic Boost Scoring for String Ranking"
   --body '## Summary

   Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings.

   Background

   The ranking algorithm combines multiple factors to produce a relevance score:

   
   Length of output: 68
   
   ---
   
   Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty
   

   This issue focuses on implementing the SemanticBoost component, which increases scores for strings that match known patterns indicating high analytical value.

   Current State

   • ✅ Core data types defined (Tag enum, FoundString struct with score field)
   • ✅ Container parsers extract strings with semantic tags
   • ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource
   • ❌ No scoring implementation exists yet
   • ❌ Semantic boost calculation not implemented

   Proposed Implementation

   Base Boost Values by Tag Type

   Create boost calculation based on tag categories:

   Tag Category	Boost	Tags
   Network	+25	Url, Domain, IPv4, IPv6
   Identifiers	+20	Guid, Email
   File System	+15	FilePath, RegistryPath, UserAgent
   Version/Manifest	+12	Version, Manifest
   Code Artifacts	+10	FormatString, Base64
   Symbols	+8	Import, Export
   Resources	+5	Resource

   Multi-Tag Bonuses

   Strings with multiple semantic tags receive additional boosts with diminishing returns:

   • Additional bonus: (tags.len() - 1) * 3
   • Example: String with both Url and Domain tags gets base boost of 25 + 25 + 3 = 53

   Context-Aware Adjustments

   Apply contextual multipliers based on string source:

   1. High-value section boost: +20% for strings in StringData or Resources sections
   2. Symbol context boost: +5 for strings from ImportName or ExportName sources

   Implementation Structure

   Location: src/classification/ranking.rs

   Key methods to implement:

   • calculate_semantic_boost() - Main entry point
   • calculate_base_boost() - Sum boost values for all tags
   • calculate_multi_tag_bonus() - Apply diminishing returns for multiple tags
   • get_tag_boost() - Return boost value for individual tag
   • apply_context_boost() - Apply source-based adjustments

   Acceptance Criteria

   • calculate_semantic_boost() function implemented in src/classification/ranking.rs
   • All 15 tag types have correct boost values assigned
   • Multi-tag bonus calculation works correctly
   • Context-aware boost adjustments applied for import/export sources
   • Unit tests cover all tag types and combinations
   • Unit tests verify multi-tag bonus calculation
   • Unit tests verify context-aware adjustments
   • Edge cases tested: no tags, single tag, multiple tags
   • Documentation added with examples

   Testing Requirements

   Unit Tests Required

   1. Individual tag boosts: Test each tag type returns correct base value
   2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags
   3. Context adjustments: Test import/export source boosts
   4. Edge cases: Empty tag vector, single tag, maximum tag combination
   5. Configurable weights: Test custom boost configurations

   Example Test Cases

   • URL tag should return boost of 25
   • URL + Domain tags should return 25 + 25 + 3 = 53
   • ImportName source should add +5 context boost
   • Empty tags vector should return 0
   • Single tag should have no multi-tag bonus

   Dependencies

   • Blocked by: Ranking System Foundation - need RankingEngine struct and configuration
   • Related to: Classification module implementation
   • Enables: Complete ranking algorithm implementation

   Technical Notes

   • Boost values are based on analytical value for malware analysis and binary reverse engineering
   • Network indicators (URLs, IPs) receive highest boost as they are often IoCs
   • Symbol names (imports/exports) are valuable for API usage analysis
   • Context-aware boosts help prioritize strings found in high-signal locations

   Requirements

   • 5.2: Semantic boost calculation
   • 5.4: Import/export name boost scoring

   References

   • Ranking Algorithm Documentation: docs/src/ranking.md
   • Implementation Plan: .kiro/specs/stringy-binary-analyzer/tasks.md - Task 11.2

   Task-ID

   stringy-analyzer/semantic-boost-scoring
   EOF

   Update the issue

   gh issue edit 23 --title "Implement Semantic Boost Scoring for String Ranking" --body-file /tmp/issue23.md

   echo "Issue #23 updated successfully!"
   echo ""

   Try to add priority label

   gh issue edit 23 --add-label "priority:high" 2>&1 | grep -v "label.*does not exist" || true

   echo ""
   echo "=== Updated Issue Preview ==="
   gh issue view 23 --json title,labels,assignees,body | jq -r '"Title: " + .title, "Labels: " + (.labels | map(.name) | join(", ")), "Assignees: " + (.assignees | map(.login) | join(", ")), "", "Body preview:", (.body | .[0:600]) + "..."'

   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Create issue body in a file

   cat > /tmp/issue23.md << 'EOF'

   Summary

   Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings.

   Background

   The ranking algorithm combines multiple factors to produce a relevance score:

   
   Length of output: 92
   
   ---
   
   🏁 Script executed:
   

   #!/bin/bash

   Create issue body using multiple echo statements to avoid here-doc issues

   {
   echo "## Summary"
   echo ""
   echo "Implement the semantic boost calculation component of the string ranking algorithm. This scoring system assigns boost values to strings based on their semantic meaning (URLs, file paths, GUIDs, etc.) to help prioritize the most valuable findings."
   echo ""
   echo "## Background"
   echo ""
   echo "The ranking algorithm combines multiple factors to produce a relevance score:"
   echo ""
   echo '' echo "Final Score = SectionWeight + EncodingConfidence + SemanticBoost - NoisePenalty" echo ''
   echo ""
   echo "This issue focuses on implementing the SemanticBoost component, which increases scores for strings that match known patterns indicating high analytical value."
   echo ""
   echo "## Current State"
   echo ""
   echo "- ✅ Core data types defined (Tag enum, FoundString struct with score field)"
   echo "- ✅ Container parsers extract strings with semantic tags"
   echo "- ✅ Tag types defined: Url, Domain, IPv4, IPv6, FilePath, RegistryPath, Guid, Email, Base64, FormatString, UserAgent, Import, Export, Version, Manifest, Resource"
   echo "- ❌ No scoring implementation exists yet"
   echo "- ❌ Semantic boost calculation not implemented"
   echo ""
   echo "## Proposed Implementation"
   echo ""
   echo "### Base Boost Values by Tag Type"
   echo ""
   echo "Create boost calculation based on tag categories:"
   echo ""
   echo "| Tag Category | Boost | Tags |"
   echo "|-------------|-------|------|"
   echo "| Network | +25 | Url, Domain, IPv4, IPv6 |"
   echo "| Identifiers | +20 | Guid, Email |"
   echo "| File System | +15 | FilePath, RegistryPath, UserAgent |"
   echo "| Version/Manifest | +12 | Version, Manifest |"
   echo "| Code Artifacts | +10 | FormatString, Base64 |"
   echo "| Symbols | +8 | Import, Export |"
   echo "| Resources | +5 | Resource |"
   echo ""
   echo "### Multi-Tag Bonuses"
   echo ""
   echo "Strings with multiple semantic tags receive additional boosts with diminishing returns:"
   echo "- Additional bonus: (tags.len() - 1) * 3"
   echo "- Example: String with both Url and Domain tags gets base boost of 25 + 25 + 3 = 53"
   echo ""
   echo "### Context-Aware Adjustments"
   echo ""
   echo "Apply contextual multipliers based on string source:"
   echo ""
   echo "1. High-value section boost: +20% for strings in StringData or Resources sections"
   echo "2. Symbol context boost: +5 for strings from ImportName or ExportName sources"
   echo ""
   echo "### Implementation Structure"
   echo ""
   echo "Location: src/classification/ranking.rs"
   echo ""
   echo "Key methods to implement:"
   echo "- calculate_semantic_boost() - Main entry point"
   echo "- calculate_base_boost() - Sum boost values for all tags"
   echo "- calculate_multi_tag_bonus() - Apply diminishing returns for multiple tags"
   echo "- get_tag_boost() - Return boost value for individual tag"
   echo "- apply_context_boost() - Apply source-based adjustments"
   echo ""
   echo "## Acceptance Criteria"
   echo ""
   echo "- [ ] calculate_semantic_boost() function implemented in src/classification/ranking.rs"
   echo "- [ ] All 15 tag types have correct boost values assigned"
   echo "- [ ] Multi-tag bonus calculation works correctly"
   echo "- [ ] Context-aware boost adjustments applied for import/export sources"
   echo "- [ ] Unit tests cover all tag types and combinations"
   echo "- [ ] Unit tests verify multi-tag bonus calculation"
   echo "- [ ] Unit tests verify context-aware adjustments"
   echo "- [ ] Edge cases tested: no tags, single tag, multiple tags"
   echo "- [ ] Documentation added with examples"
   echo ""
   echo "## Testing Requirements"
   echo ""
   echo "### Unit Tests Required"
   echo ""
   echo "1. Individual tag boosts: Test each tag type returns correct base value"
   echo "2. Multi-tag scenarios: Test combinations of 2, 3, 4+ tags"
   echo "3. Context adjustments: Test import/export source boosts"
   echo "4. Edge cases: Empty tag vector, single tag, maximum tag combination"
   echo "5. Configurable weights: Test custom boost configurations"
   echo ""
   echo "### Example Test Cases"
   echo ""
   echo "- URL tag should return boost of 25"
   echo "- URL + Domain tags should return 25 + 25 + 3 = 53"
   echo "- ImportName source should add +5 context boost"
   echo "- Empty tags vector should return 0"
   echo "- Single tag should have no multi-tag bonus"
   echo ""
   echo "## Dependencies"
   echo ""
   echo "- Blocked by: Ranking System Foundation - need RankingEngine struct and configuration"
   echo "- Related to: Classification module implementation"
   echo "- Enables: Complete ranking algorithm implementation"
   echo ""
   echo "## Technical Notes"
   echo ""
   echo "- Boost values are based on analytical value for malware analysis and binary reverse engineering"
   echo "- Network indicators (URLs, IPs) receive highest boost as they are often IoCs"
   echo "- Symbol names (imports/exports) are valuable for API usage analysis"
   echo "- Context-aware boosts help prioritize strings found in high-signal locations"
   echo ""
   echo "## Requirements"
   echo ""
   echo "- 5.2: Semantic boost calculation"
   echo "- 5.4: Import/export name boost scoring"
   echo ""
   echo "## References"
   echo ""
   echo "- Ranking Algorithm Documentation: docs/src/ranking.md"
   echo "- Implementation Plan: .kiro/specs/stringy-binary-analyzer/tasks.md - Task 11.2"
   echo ""
   echo "## Task-ID"
   echo ""
   echo "stringy-analyzer/semantic-boost-scoring"
   } > /tmp/issue23_body.md

   Update the issue

   gh issue edit 23 --title "Implement Semantic Boost Scoring for String Ranking" --body-file /tmp/issue23_body.md

   echo ""
   echo "✓ Issue #23 updated successfully"
   echo ""

   View the updated issue

   gh issue view 23

   
   Length of output: 4705
   
   ---
   
   
   
   </details>
   
   @unclesp1d3r I've successfully enhanced issue #23 with comprehensive technical details and a proposed solution. Here's what was updated:
   
   ## ✅ Changes Made
   
   ### Title Enhancement
   - **Before**: "Semantic Boost Scoring"
   - **After**: "Implement Semantic Boost Scoring for String Ranking"
   
   ### Body Enhancements
   
   **Added comprehensive context including:**
   
   1. **Background Section** - Explained how semantic boost fits into the overall ranking formula
   2. **Current State Assessment** - Clear checklist of what's done vs. what's needed
   3. **Detailed Boost Values Table** - All 15 tag types organized by category with specific boost values:
      - Network tags: +25 (Url, Domain, IPv4, IPv6)
      - Identifiers: +20 (Guid, Email)
      - File System: +15 (FilePath, RegistryPath, UserAgent)
      - And more...
   
   4. **Multi-Tag Bonus System** - Explained diminishing returns calculation with examples
   5. **Context-Aware Adjustments** - Symbol context boosts for imports/exports
   6. **Implementation Structure** - Specific method signatures and responsibilities
   7. **Clear Acceptance Criteria** - 9 checkboxes for tracking completion
   8. **Comprehensive Testing Requirements** - 5 categories of unit tests with specific examples
   9. **Dependencies & Technical Notes** - Context for the implementation decisions
   
   ### Metadata
   - **Labels**: Already well-configured (area:analyzer, lang:rust, needs:tests, status:backlog, type:enhancement)
   - **Assignee**: unclesp1d3r ✅
   - **Milestone**: v0.1 ✅
   
   **Note**: I attempted to add a `priority:high` label, but it doesn't exist in your repository's label set. If you'd like to prioritize this issue, you may want to create that label or use an existing priority label.
   
   The issue now provides a complete implementation roadmap with specific boost values extracted from your ranking documentation, making it ready for development!
   
9. traycerai commented on Nov 10, 2025

   

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   on Nov 10, 2025 – with traycerai

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11. unclesp1d3r commented on Jul 4, 2026

    

    unclesp1d3r

    on Jul 4, 2026

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    Implemented: semantic boost scoring is part of the src/classification/ ranking pipeline. Closing as completed.
12. unclesp1d3r

    closed this as completedon Jul 4, 2026