feat: generate better report

src/mutahunter/core/controller.py

@@ -26,7 +26,7 @@
 from mutahunter.core.llm_mutation_engine import LLMMutationEngine
 from mutahunter.core.logger import logger
 from mutahunter.core.prompts.mutant_generator import (
-    SYSTEM_PROMPT_MUTANT_ANALYSUS,
+    SYSTEM_PROMPT_MUTANT_ANALYSIS,
     USER_PROMPT_MUTANT_ANALYSIS,
 )
 from mutahunter.core.report import MutantReport
@@ -246,7 +246,7 @@ def run_mutant_analysis(self) -> None:
             with open(k, "r", encoding="utf-8") as f:
                 src_code = f.read()
             prompt = {
-                "system": Template(SYSTEM_PROMPT_MUTANT_ANALYSUS).render(),
+                "system": Template(SYSTEM_PROMPT_MUTANT_ANALYSIS).render(),
                 "user": Template(USER_PROMPT_MUTANT_ANALYSIS).render(
                     source_code=src_code,
                     surviving_mutants=json.dumps(v, indent=2),

src/mutahunter/core/prompts/mutant_generator.py

@@ -96,11 +96,37 @@ class Mutants(BaseModel):
 """
 
 
-SYSTEM_PROMPT_MUTANT_ANALYSUS = """
-You are an AI Agent part of the Software Quality Assurance Team. Your task is to analyze the mutation testing results generated by the mutation testing tool. The tool has identified surviving mutants that were not detected by the existing test cases. Your goal is to provide a detailed analysis of these surviving mutants to improve the test coverage and code quality.
+SYSTEM_PROMPT_MUTANT_ANALYSIS = """
+You are a Senior Software Quality Assurance Analyst specializing in mutation testing. Your task is to analyze surviving mutants from recent mutation tests and produce a concise, professional report.
+
+Objective: Evaluate test coverage gaps and code vulnerabilities based on surviving mutants.
+
+Report Structure:
+1. Executive Summary
+2. Critical Findings
+3. Detailed Analysis
+   a. Vulnerable Code Areas
+   b. Test Coverage Gaps
+4. Recommendations
+   a. Test Suite Enhancements
+   b. Code Refactoring Suggestions
+5. Risk Assessment
+6. Conclusion
+
+Guidelines:
+- Maintain a formal, precise tone throughout the report.
+- Prioritize findings based on potential impact and likelihood.
+- Provide specific, actionable recommendations.
+- Use clear, concise language to ensure accessibility for both technical and non-technical stakeholders.
+- Include relevant code snippets and data to support your analysis.
+- Limit the report to essential information that drives decision-making and action.
+
+Your analysis should enable the development team to efficiently improve code quality and test coverage.
 """
 USER_PROMPT_MUTANT_ANALYSIS = """
-## Related Source Code:
+Analyze the following mutation testing results and produce a concise, professional report:
+
+## Source Code:
 ```
 {{source_code}}
 ```
@@ -109,29 +135,38 @@ class Mutants(BaseModel):
 ```json
 {{surviving_mutants}}
 ```
-
-Based on the mutation testing results only showing the surviving mutants. Please analyze the following aspects:
-## Vulnerable Code Areas:
-1. Identify critical sections in the code that are most susceptible to undetected mutations.
-2. Rank these areas by severity, considering factors such as frequency of occurrence and potential impact on functionality.
-3. For each identified area, cite specific surviving mutant(s) as evidence.
-
-## Test Case Gaps:
-1. Provide concrete examples from the surviving mutants JSON for each identified gap.
-
-## Improvement Recommendations:
-1. Suggest specific new test cases or modifications to existing ones to target each surviving mutant.
-2. Prioritize recommendations based on their potential impact and ease of implementation.
-2. Where applicable, provide pseudo-code or test case outlines to illustrate the suggested improvements.
-
-## Code Refactoring Suggestions:
-1. Based on the surviving mutants, propose any potential code refactoring that could make the code more robust against mutations.
-2. Explain how each refactoring suggestion would help in reducing the number of surviving mutants.
-
-## Format Requirements:
-1. Present the final output in concise bullet points.
-2. Limit the entire analysis to no more than one page.
-3. Ensure each point is supported by specific references to the surviving mutants JSON data.
-4. Focus on the most critical findings and high-impact recommendations.
-5. Output should be in markdown format for easy readability.
+Report Structure:
+1. Executive Summary (50 words)
+Briefly outline key findings and their potential impact on software quality.
+2. Critical Findings (100 words)
+Highlight the most significant vulnerabilities and test gaps discovered.
+3. Detailed Analysis (400 words)
+   a. Vulnerable Code Areas
+      - Identify and rank critical sections susceptible to undetected mutations.
+      - Cite specific surviving mutants as evidence.
+   b. Test Coverage Gaps
+      - Provide concrete examples from the surviving mutants for each gap.
+4. Recommendations (300 words)
+   a. Test Suite Enhancements
+      - Suggest specific new test cases or modifications.
+      - Prioritize based on impact and implementation ease.
+      - Include pseudo-code or test case outlines where applicable.
+   b. Code Refactoring Suggestions
+      - Propose refactoring to improve mutation resistance.
+      - Explain how each suggestion reduces surviving mutants.
+5. Risk Assessment (100 words)
+Evaluate the potential impact of unaddressed vulnerabilities on system integrity and security.
+6. Conclusion (50 words)
+Summarize key actions needed to improve code quality and test coverage.
+
+Format Requirements:
+
+Use markdown for easy readability.
+Limit the report to a maximum of 2 pages (approximately 1000 words).
+Use concise bullet points where appropriate.
+Support each point with specific references to the surviving mutants data.
+Focus on critical findings and high-impact recommendations.
+Maintain a professional tone throughout the report.
+
+Ensure the report provides clear, actionable insights for both technical and non-technical stakeholders.
 """