1. Software coding/testing
Not correct system: math/logic proof, right take: I find no error so far at my best. Incomplete induction. Debugging: part of coding phase, by self vs testing: conform to spec—most important quality
Verification=testing: conform to the spec;
Validation: verification + better general quality:
understandable: clean/simple logic, more comments , naming convention,
Static: reading doc: spec/design/code and dynamic testing: run
statistical: collect stats defect: non-conforming spec
stat: guiding
double blind testing: google vs bing, modern science
New medicine: doctor, patient: med, suger: 1917: : 75-80
1900: <10 reliable medicine
Component testing, integration: interface modules user test
Thread testing: typical scenario follow thru it
Alpha version: internal testing version, beta version: init: alpha
dynamic: free send feedback, pay experts, delivered version 1.0
Minor change 1.01, , ipython 1.0

2. Unit/module/sub-system/ acceptance: delivered version (after beta), Black box testing: partitioning cases: cannot see,
input --- output according to spec
White-box glass –box or structural testing: exhaustive traversal all possible branch
End result: delivered system (not final, to be revised during maintenance phase)

3. Evolution & maintenance
Maintenance: change after delivery
corrective: fix error; required
adaptive: to new envir; optional
perfective: new req; more optional/volunteer new
Process: user complaints. Pool whinings; change req/spec, assessment, new iteration of dev-new life cycle
System documentation: spec+plan+design+src code + testing cases report (bugs, fix)
Software re-engineering: legacy system: in old PL(cobol, algol), old DS, alg.; which is easierCobol to C
Software Reverse engineering: military AI; obtain design and spec from object code