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The Verification Grand Challenge

Tony Hoare Menlo Park Feb 21, 2005. The Verification Grand Challenge . A mature scientific discipline. Sets its own agenda for accumulation of knowledge and skills Pursues its own ideals of purity, accuracy, generality, certainty… Poses its own fundamental questions

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The Verification Grand Challenge

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  1. Tony Hoare Menlo Park Feb 21, 2005 The Verification Grand Challenge

  2. A mature scientific discipline • Sets its own agenda • for accumulation of knowledge and skills • Pursues its own ideals • of purity, accuracy, generality, certainty… • Poses its own fundamental questions • to satisfy curiosity, both practical and theoretical

  3. In Engineering we ask… • What does the product do? • the specification tells us • How does it work? • its internal interface specifications tell us. • How can we make it better? • cheaper, more reliable,… • and delivered sooner!

  4. In Science we ask more… • Why does the product work? • The underlying scientific theory explains. • How does the theory generalise? • so results apply in different domains. • How do we know the answers are right? • by calculation and by convincing experiment, • reproducible and subject to scrutiny.

  5. Verified Programs • Have precise external specifications • At appropriate level of soundness, safety, security, serviceability, functionality, … • Have complete internal specifications • of interfaces between components • With correctness checked by proof • which should be fully mechanised • Based on a sound theory of programming • which should be general and complete

  6. A Program Verifier was proposed in 1969 as a fully automatic check of validity of an explanation why the program works. It is needed as a basic experimental tool for the science of programming. Its construction is still a grand challenge for research in Computer Science

  7. The Human Genome project(1990-2004) • had a clear set of deliverables, • a planned route to application, • in areas of great potential benefit. • It pursued scientific ideals • free from commercial pressures. • Building on the current state of the art • it looked 15 years ahead, • and changed the mode of conduct of Science.

  8. The Verified Software project • is modelled on the Human Genome project • and shares many of its properties • Does not need glamour or massive funds

  9. Clear deliverables • A comprehensive theory of programming • concurrency, object orientation, inheritance,… • A coherent toolset based on the theory • development aids, test case generators, harnesses, assertion inference engines, program analysers,… • A collection of mechanically verified programs • safety-critical and embedded codes, open source libraries, middleware and desktop applications • fully verified at high levels of soundness, safety, security, serviceability, functional correctness.

  10. Route to application • Verified programs will replace existing versions in daily use • subsequent evolution will maintain correctness. • Verification technology will be integrated into commercial toolsets • for general use by software engineers • The costs associated with program error will be significantly reduced

  11. ‘Based on the software developer and user surveys, the national (US) annual costs of an inadequate infrastructure for software testing is estimated to range from $22.2 to $59.5 billion. • Over half of these costs are borne by software users in the form of error avoidance and mitigation activities. • The remaining costs are borne by software developers’ • ‘In 2000, total sales of software reached $180 billion’ • “The Economic Impacts of Inadequate Infrastructure for Software Testing” • (US Dept. Commerce Planning Report 02-03, May 2002 ).

  12. Scientific ideals • Academic research pursues ideals • generality of theory, • of certainty of knowledge • purity of materials, • accuracy of measurement, • and now correctness of programs • far beyond the current needs of the market place

  13. Commercial pressures • commercial program analysis and development tools • will follow market demand • to discover more faults in existing programs • appealing to current educational level of programmers • preferably with pictorial representations

  14. State of the art • Smart-card applications have been manually proved (eg. Logica). • Safety-critical systems have been developed from specification (eg. Praxis). • Commodity software already includes many assertions (eg. Microsoft Office) • Open Source software is freely available for research, as well as for use (eg. Apache). • Programming theory covers O-O, concurrency (eg. Separation Logic, Process algebra ,…)

  15. Some Available Tools • Assertion generators • Program optimisers and analysers • Type inferencers and checkers • Abstract Syntax Tree compilers • Verification Condition Generators • Program Development Environments • Code generators

  16. Theorem proving • Proof searchers, • Constraint solvers, • Model checkers, • Decision procedures, • Algebraic simplifiers

  17. Change in conduct of Science • Commitment to a large and long-term project • involving collaboration as well as competition • on an international scale. • New links between established research schools, conference series, journals,… • New criteria for refereeing, research grant evaluation, personal promotion,… • That’s why we need a ‘Grand Challenge’

  18. Determinants of success • Support of the scientific community • Skill and enthusiasm of participants • Strategy for accumulation of results • by co-operation and competition. • Standards for inter-operation of tools • Agreement on challenge codes • Understanding from funding bodies

  19. Public appeal • Win public confidence and respect. • Beware of glamour • manned space flight • chess playing machine • the nematode worm

  20. First steps • A ‘verified software repository’ • a growing sample of challenge codes, with • specifications, design paths, assertions, • test suites, test harnesses, post mortems, • and an evolving set of analysis tools • observing standards for inter-operation • applicable to the challenge codes • with accumulation of ‘experimental’ results

  21. IFIP Working Conference • Verified Software: Theories, Tools and Experiments • Zurich, October 10-14, 2005 • Chairmen: Tony Hoare and Jay Misra • Organisers: Bertrand Meyer, Natarajan Shankar, Jim Woodcock • Participants: by invitation

  22. A Program Verifier One can dream of routinely using a verifying compiler as an everyday tool. In the context of this idea our work has been extremely modest and must be considered as a small first step. We only hope that, indeed, this has been a first step of a progression which will allow this dream to come to fruition. A Program Verifier Thesis by James C. King Carnegie Institute of Technology September 1969

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