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QA Training In Nepal

QA Training

ㅤ Duration:2.5 Months ㅤㅤㅤㅤ ㅤCareer:QA Engineer
Course Overview Course Syllabus

Quality assurance is a rigorous, systematic, objective, impartial, expert-based examination, evaluation and self-evaluation of how effectively a university/faculty/department/school/program is working, as part of the ongoing pursuit of higher levels of achievement and quality in the university, for action planning and continuous improvement. Quality here is defined as excellence, reliability and consistency fitness for purpose, fitness of purpose, conformance to specifications, meeting objectives, meeting stakeholders'needs and requirements. Quality enhancement is the act of taking planned steps to bring about continuous improvement in the effectiveness and efficiency of the learning experiences of students.

Quality assurance is based on the principle that every aspect of the work of the faculty/department/school/university can be improved continuously and that evaluation and self-evaluation, both internal and external, are ongoing practices that serve that improvement. It is constructive and formative (rather than solely judgemental and summative), is evaluative as well as descriptive, and is evidence-based and data-driven, with evidence drawn from a wide range of referenced sources. Quality assurance is a collaborative exercise, and one of its benefits is a consensus on goals, objectives and intended outcomes, such that there is a common benchmark set of criteria for planning and evaluating the work of the university/faculty/department/school/program. In working towards consensus, staff are involved in examining best practice in their own and others'work.

Exercise: What is quality, quality assurance Quality in the project manager’s triangle Quality is free, cost of poor quality What we, others mean by quality Need for positive common quality definition Quality factors and quality dimensions Engineered Deliverable Quality Quality assurance vs. quality control SQA in IEEE Stds. 12207 and 730 Proactive SQA changes in IEEE Std. 730 Not just ‘traffic cop’ compliance

REAL vs. Presumed processes, silos Exercise: Your software process Defect injection, detection, ejection metrics Economics of quality problems in life cycle Making the business case for SQA Life cycle concepts, waterfall vs. iterative Process capability, variation, improvement Project, process, product measures Direct and indirect process evaluation SEI Process Capability Maturity Models

Exercise: Why SQA groups so often fail SQA groups’ changes over time Common SQA interpretations, issues Quality control (QC) testing ‘QA Test’ Document and procedure compliance ‘QA Reviews’ and toll gates Standards and procedures manuals Staffing and organizational influence Reasons for resistance to SQA SQA needs broader view of quality Proactive SQA™ for effectiveness Assuring processes vs. doing it all 6 functions of effective software QA QA Plans, quality reviews of deliverables Exercise: Managing SQA tasks, resources Engineering standards, conventions Quality controls at all key points Project control Configuration management, checkpoints Recordkeeping and auditing Metrics and analysis for improvement Exercise: Key product and process metrics Promoting awareness and recognition

Role of requirements in producing quality Exercise: ‘Established Requirements’ issues Exercise: Reviewing Requirements Unrecognized weaknesses of “Regular Way” Why review of requirements fails Formal technical reviews, procedures Review approaches, formality Often overlooked walkthrough limitations Why reviews so economically find defects Foundation technique, topic guidelines Evaluating requirements form, testability REAL, business vs. system requirements Finding overlooked, incorrect requirements Reviewing design suitability and content Four powerful design review CAT-Scans Exercise: Reviews and Software Process QA

Testing for correctness vs. testing for errors Developer views of testing Reactive testing—out of time, but not tests Proactive Testing Life Cycle model CAT-Scan Approach to find more errors Dynamic, passive and active static testing V-model and objectives of each test level Developer vs. independent test group testing Strategy—create fewer errors, catch more Four keys to effective testing Need for testing sampling Written vs. not written benefits and issues Test activities that save the developer’s time The “we don’t have time” fallacy

Risk elements, relation to testing Proactive vs. reactive risk analysis IEEE Standard for Test Documentation Benefits of the structure Enabling manageability, reuse, selectivity Test plans vs. test designs, cases, procedures Exercise: Anticipating showstoppers Risk-based way to define test units Letting testing drive development Preventing major cause of overruns Master Test Plan counterpart to project plan Approach, use of automated tools Entry/exit criteria, anticipating change

IEEE Standard on Unit Testing Functional (Black Box) testing strategy 3-level top-down test planning and design Exercise: Functionality matrix Detailed Test Plan technical document White box structural testing coverage Use cases, revealing overlooked conditions Exercise: Defining use case test coverage

Graphical technique to simplify integrations Integration test plans prevent schedule slips Smoke tests; system and special testing Daily, top- and bottom-down builds strategy

Exercise: Your challenges and issues Exercise: Disciplined brainstorming Checklists find more overlooked conditions Data formats, data and process models Business rules, decision tables and trees Equivalence classes and boundary values Formal, informal Test Design Specifications Leveraging reusable test designs Test Case Specifications vs. test data values Writing test cases, script/matrix Embedding keystroke-level procedural detail Exploratory testing applied most effectively

Estimating Defect isolation Defect reporting, categories and analysis Defect reports that prompt suitable action Exercise: Measures for managing testing Common measures of test status, issues Exercise: Test status report audiences Projecting when software is good enough Exercise: Measuring testing effectiveness Exercise: Post-Implementation Review

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