Dynamic Program Analysis Execution Tracing and Profiling

Lecture 9 of SE602 Software Re-Engineering investigates dynamic program analysis, which extracts behavioral and architectural insights by observing software systems while they execute under specific test workloads. Unlike static analysis, dynamic analysis precisely resolves runtime phenomena such as polymorphic method dispatching, reflection, dynamic class loading, and pointer aliasing. Students study execution tracing techniques, bytecode instrumentation, and CPU/memory profiling tools that record call sequences and heap allocations. The lecture details the software engineering problem of feature location—identifying the exact source code segments responsible for implementing specific business features. Students contrast static call graph over-approximation with dynamic trace under-approximation, establishing how hybrid static-dynamic analyses provide comprehensive understanding of legacy software behavior. Software quality attributes, maintainability index equations, and technical debt principal valuations are evaluated alongside empirical benchmarks. Architectural recovery processes are explored through module dependency analysis, component clustering, and high-level design reconstruction. Database schema normalization, legacy record migration, and automated ETL extraction pipelines are systematically analyzed. Monolithic application decomposition strategies including service-oriented architecture (SOA) and the Strangler Fig pattern are examined in depth. Scholars examine program slicing algorithms, forward and backward dependency slices, and impact assessment for proposed modifications. Automated tool support, bytecode instrumentation, and static code analyzers are evaluated to detect architectural violations across repositories. Risk management frameworks, business case evaluations, and cost estimation models such as COCOMO II are analyzed for migration projects. Legal and ethical constraints surrounding reverse engineering, clean-room design implementations, and software intellectual property rights are reviewed. By engaging with solved past papers by Moaaz and Waqar Siddhu, learners gain actionable insights into recurrent university exam questions. Interactive quiz assessments on VU SIGMA facilitate rapid knowledge verification and retention of critical software re-engineering concepts. Comprehensive coverage of standard academic benchmarks ensures learners communicate with technical precision across software engineering disciplines. Detailed analysis of code smell topologies highlights the imperative of eradicating duplicate logic, long methods, and bloated god classes. Test harness construction including characterization testing and regression suites are contrasted with traditional unit testing strategies.