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: 30-40 2017: 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, 2.7.6 , ipython 1.0

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)

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