modified from sommerville’s originals software engineering, 7th edition. chapter 20&24 slide 1...

Modified from Sommerville’s originals Software Engineering, 7th edition. Chapter 20&24 Slide 1

Critical systems development


Topics covered

Dependable processes Dependable programming Fault tolerance Fault tolerant architectures


Approaches for developing dependable software

Fault avoidance• The system is developed in such a way that human error is

avoided and thus system faults are minimised.• The development process is organised so that faults in the system

are detected and repaired before delivery to the customer.• Activities: dependable programming practices

Fault detection (Chapter 24)• Verification and validation techniques are used to discover and

remove faults in a system before it is deployed.• Activities: reviews, formal verification, testing

Fault tolerance• The system is designed so that faults in the delivered software do

not result in system failure.• Activities: fault detection, damage assessment, recovery, repair.


Fault-free software

Fault-free software means software which conforms to its specification. It does NOT mean software which will always perform correctly as there may be specification errors.

The cost of producing fault free software is very high. It is only cost-effective in exceptional situations. It is often cheaper to accept software faults and pay for their consequences than to expend resources on developing fault-free software.


Fault removal costs

Few

Number of residual errors

Many Very few


Fault-free software development

Current methods of software engineering now allow for the production of fault-free software, at least for relatively small systems.

Examples• Dependable software processes• Quality management• Formal specification• Static verification• Strong typing• Safe programming• Protected information


Dependable processes

To ensure a minimal number of software faults, it is important to have a well-defined, repeatable software process.

A well-defined repeatable process is one that does not depend entirely on individual skills; rather can be enacted by different people.

For fault detection, it is clear that the process activities should include significant effort devoted to verification and validation.


Dependable process characteristics

Documentable The process should have a defined process model that sets out the activities in the process and the documentation that is to be produced during these activities.

Standardised A comprehensive set of software development standards that define how the software is to be produced and documented should be available.

Auditable The process should be understandable by people apart from process participants who can check that process standards are being followed and make suggestions for process improvement.

Diverse The process should include redundant and diverse verification and validation activities.

Robust The process should be able to recover from failures of individual process activities.


Validation activities

Requirements inspections. Requirements management. Model checking. Design and code inspection. Static analysis. Test planning and management. Configuration management.


Topics covered



Safe programming practices

Faults in programs are usually a consequence of programmers making mistakes.

These mistakes occur because people lose track of the relationships between program variables.

Examples of safe programming practices• Design for simplicity.• Protect information from unauthorised access.• Avoid “unsafe” programming language constructs.• Handle exceptions consistently.


Information protection

Information should only be exposed to those parts of the program which need to access it. This involves the creation of objects or abstract data types that maintain state and that provide operations on that state.

This avoids faults for three reasons:• the probability of accidental corruption of information is

reduced; • the information is surrounded by ‘firewalls’ so that

problems are less likely to spread to other parts of the program;

• as all information is localised, you are less likely to make errors and reviewers are more likely to find errors.


A queue specification in Java


Signal declaration in Java


Structured programming

First proposed in 1968 as an approach to development that makes programs easier to understand and that avoids programmer errors.

Programming without gotos. While loops and if statements as the only

control statements. Top-down design. An important development because it promoted

thought and discussion about programming.


Error-prone constructs

Floating-point numbers• Inherently imprecise. The imprecision may lead to invalid

comparisons. Pointers

• Pointers referring to the wrong memory areas can corrupt data. Aliasing can make programs difficult to understand and change.

Dynamic memory allocation• Run-time allocation can cause memory overflow.

Parallelism• Can result in subtle timing errors because of unforeseen

interaction between parallel processes. Recursion

• Errors in recursion can cause memory overflow.


Error-prone constructs

Interrupts• Interrupts can cause a critical operation to be terminated

and make a program difficult to understand. Inheritance

• Code is not localised. This can result in unexpected behaviour when changes are made and problems of understanding.

Aliasing• Using more than 1 name to refer to the same state variable.

Unbounded arrays• Buffer overflow failures can occur if no bound checking on

arrays. Default input processing

• An input action that occurs irrespective of the input.


Exception handling

A program exception is an error or some unexpected event such as a power failure.

Using normal control constructs to detect exceptions needs many additional statements to be added to the program. This adds a significant overhead and is potentially error-prone.

Exception handling constructs allow for such events to be handled without the need for continual status checking to detect exceptions.


Exceptions in Java 1


Exceptions in Java 2


Topics covered



Fault tolerance

In critical situations, software systems must be fault tolerant.

Fault tolerance is required where there are high availability requirements or where system failure costs are very high.

Fault tolerance means that the system can continue in operation in spite of software failure.

Even if the system has been proved to conform to its specification, it must also be fault tolerant as there may be specification errors or the validation may be incorrect.


Fault tolerance actions

Fault detection• The system must detect that a fault (an incorrect system

state) has occurred. Damage assessment

• The parts of the system state affected by the fault must be detected.

Fault recovery• The system must restore its state to a known safe state.

Fault repair• The system may be modified to prevent recurrence of the

fault. As many software faults are transitory, this is often unnecessary.


Fault detection

Preventative fault detection• The fault detection mechanism is initiated before the state

change is committed. If an erroneous state is detected, the change is not made.

Retrospective fault detection• The fault detection mechanism is initiated after the

system state has been changed. This is used when a incorrect sequence of correct actions leads to an erroneous state or when preventative fault detection involves too much overhead.


Preventative fault detection really involves extending the type system by including additional constraints as part of the type definition.

These constraints are implemented by defining basic operations within a class definition.

Type system extension


PositiveEvenInteger 1


PositiveEvenInteger 2


Damage assessment

Analyse system state to judge the extent of corruption caused by a system failure.

The assessment must check what parts of the state space have been affected by the failure.

Generally based on ‘validity functions’ that can be applied to the state elements to assess if their value is within an allowed range.


Robust array 1


Robust array 2


Checksums are used for damage assessment in data transmission.

Redundant pointers can be used to check the integrity of data structures.

Watch dog timers can check for non-terminating processes. If no response after a certain time, a problem is assumed.

Damage assessment techniques


Forward recovery• Apply repairs to a corrupted system state.

Backward recovery• Restore the system state to a known safe state.

Forward recovery is usually application specific - domain knowledge is required to compute possible state corrections.

Backward error recovery is simpler. Details of a safe state are maintained and this replaces the corrupted system state.

Fault recovery and repair


Corruption of data coding• Error coding techniques which add redundancy to coded

data can be used for repairing data corrupted during transmission.

Redundant pointers• When redundant pointers are included in data structures

(e.g. two-way lists), a corrupted list or filestore may be rebuilt if a sufficient number of pointers are uncorrupted

• Often used for database and file system repair.

Forward recovery


Transactions are a frequently used method of backward recovery. Changes are not applied until computation is complete. If an error occurs, the system is left in the state preceding the transaction.

Periodic checkpoints allow system to 'roll-back' to a correct state.

Backward recovery


Safe sort procedure

A sort operation monitors its own execution and assesses if the sort has been correctly executed.

It maintains a copy of its input so that if an error occurs, the input is not corrupted.

Based on identifying and handling exceptions. Possible in this case as the condition for a‘valid’ sort

is known. However, in many cases it is difficult to write validity checks.


Safe sort 1


Safe sort 2


Topics covered



Fault tolerant architecture

Defensive programming cannot cope with faults that involve interactions between the hardware and the software.

Misunderstandings of the requirements may mean that checks and the associated code are incorrect.

Where systems have high availability requirements, a specific architecture designed to support fault tolerance may be required.

This must tolerate both hardware and software failure.


Diversity and redundancy

Redundancy• Keep more than 1 version of a critical component

available so that if one fails then a backup is available. Diversity

• Provide the same functionality in different ways so that they will not fail in the same way.

However, adding diversity and redundancy adds complexity and this can increase the chances of error.

Some engineers advocate simplicity and extensive V & V is a more effective route to software dependability.


Diversity and redundancy examples

Redundancy. Where availability is critical (e.g. in e-commerce systems), companies normally keep backup servers and switch to these automatically if failure occurs.

Diversity. To provide resilience against external attacks, different servers may be implemented using different operating systems (e.g. Windows and Linux)


Hardware fault tolerance

Depends on triple-modular redundancy (TMR). There are three replicated identical components that

receive the same input and whose outputs are compared.

If one output is different, it is ignored and component failure is assumed.

Based on most faults resulting from component failures rather than design faults and a low probability of simultaneous component failure.


Hardware reliability with TMR

A2

A1

A3

Outputcomparator


Output selection

The output comparator is a (relatively) simple hardware unit.

It compares its input signals and, if one is different from the others, it rejects it. Essentially, the selection of the actual output depends on the majority vote.

The output comparator is connected to a fault management unit that can either try to repair the faulty unit or take it out of service.


Fault tolerant software architectures

The success of TMR at providing fault tolerance is based on two fundamental assumptions• The hardware components do not include common

design faults;• Components fail randomly and there is a low probability

of simultaneous component failure. Neither of these assumptions are true for software

• It isn’t possible simply to replicate the same component as they would have common design faults;

• Simultaneous component failure is therefore virtually inevitable.

Software systems must therefore be diverse.


Design diversity

Different versions of the system are designed and implemented in different ways. They therefore ought to have different failure modes.

Different approaches to design (e.g object-oriented and function oriented)• Implementation in different programming languages;• Use of different tools and development environments;• Use of different algorithms in the implementation.


Software analogies to TMR

N-version programming• The same specification is implemented in a number of

different versions by different teams. All versions compute simultaneously and the majority output is selected using a voting system.

• This is the most commonly used approach e.g. in many models of the Airbus commercial aircraft.

Recovery blocks• A number of explicitly different versions of the same

specification are written and executed in sequence.• An acceptance test is used to select the output to be

transmitted.


N-version programming

Version 2

Version 1

Version 3

Outputcomparator

N-versions

Agreedresult

Faultmanager

Input


N-version programming

The different system versions are designed and implemented by different teams. It is assumed that there is a low probability that they will make the same mistakes. The algorithms used should but may not be different.

There is some empirical evidence that teams commonly misinterpret specifications in the same way and chose the same algorithms in their systems.


Recovery blocks

Acceptancetest

Algorithm 2

Algorithm 1

Algorithm 3

Recovery blocks

Test forsuccess

Re-test

Retry

Re-test

Try algorithm1

Continue execution ifacceptance test succeeds

Signal exception if allalgorithms fail

Acceptance testfails – retry


Recovery blocks

These force a different algorithm to be used for each version so they reduce the probability of common errors.

However, the design of the acceptance test is difficult as it must be independent of the computation used.

There are problems with this approach for real-time systems because of the sequential operation of the redundant versions.


Problems with design diversity

Teams are not culturally diverse so they tend to tackle problems in the same way.

Characteristic errors• Different teams make the same mistakes. Some parts of

an implementation are more difficult than others so all teams tend to make mistakes in the same place;

• Specification errors;• If there is an error in the specification then this is reflected

in all implementations;• This can be addressed to some extent by using multiple

specification representations.


Specification dependency

Both approaches to software redundancy are susceptible to specification errors. If the specification is incorrect, the system could fail

This is also a problem with hardware but software specifications are usually more complex than hardware specifications and harder to validate.

This has been addressed in some cases by developing separate software specifications from the same user specification.


Critical Systems Validation


Topics covered

Reliability validation Safety assurance Security assessment Safety and dependability cases


Validation of critical systems

The verification and validation costs for critical systems involves additional validation processes and analysis than for non-critical systems:• The costs and consequences of failure are high so it is

cheaper to find and remove faults than to pay for system failure;

• You may have to make a formal case to customers or to a regulator that the system meets its dependability requirements. This dependability case may require specific V & V activities to be carried out.


Reliability validation

Reliability validation involves exercising the program to assess whether or not it has reached the required level of reliability.

This cannot normally be included as part of a normal defect testing process because data for defect testing is (usually) atypical of actual usage data.

Reliability measurement therefore requires a specially designed data set that replicates the pattern of inputs (the operational profile) to be processed by the system.


The reliability measurement process

Computeobservedreliability

Apply tests tosystem

Prepare testdata set

Identifyoperational

profiles


Reliability validation activities

Establish the operational profile for the system.

Construct test data reflecting the operational profile.

Test the system and observe the number of failures and the times of these failures.

Compute the reliability after a statistically significant number of failures have been observed.


Statistical testing

Testing software for reliability rather than fault detection.

Measuring the number of errors allows the reliability of the software to be predicted. Note that, for statistical reasons, more errors than are allowed for in the reliability specification must be induced.

An acceptable level of reliability should be specified and the software tested and amended until that level of reliability is reached.


Reliability measurement problems

Operational profile uncertainty• The operational profile may not be an accurate

reflection of the real use of the system. High costs of test data generation

• Costs can be very high if the test data for the system cannot be generated automatically.

Statistical uncertainty• You need a statistically significant number of

failures to compute the reliability but highly reliable systems will rarely fail.


Operational profiles

An operational profile is a set of test data whose frequency matches the actual frequency of these inputs from ‘normal’ usage of the system. A close match with actual usage is necessary otherwise the measured reliability will not be reflected in the actual usage of the system.

It can be generated from real data collected from an existing system or (more often) depends on assumptions made about the pattern of usage of a system.


An operational profile

...

Number ofinputs

Input classes


Reliability prediction

A reliability growth model is a mathematical model of the system reliability change as it is tested and faults are removed.

It is used as a means of reliability prediction by extrapolating from current data• Simplifies test planning and customer negotiations.• You can predict when testing will be completed and

demonstrate to customers whether or not the reliability growth will ever be achieved.

Prediction depends on the use of statistical testing to measure the reliability of a system version.


Equal-step reliability growth

Reliability(ROCOF)

t1 t2 t3 t4 t5Time


Random-step reliability growth

t1 t2 t3 t4 t5Time

Note different reliabilityimprovements

Fault repair adds new faultand decreases reliability(increases ROCOF)

Reliability(ROCOF)


Growth model selection

Many different reliability growth models have been proposed.

There is no universally applicable growth model.

Reliability should be measured and observed data should be fitted to several models.

The best-fit model can then be used for reliability prediction.


Reliability prediction

Reliability

Requiredreliability

Fitted reliabilitymodel curve

Estimatedtime of reliability

achievement

Time

= Measured reliability


Topics covered



Safety assurance

Safety assurance and reliability measurement are quite different:• Within the limits of measurement error, you

know whether or not a required level of reliability has been achieved;

• However, quantitative measurement of safety is impossible. Safety assurance is concerned with establishing a confidence level in the system.


Safety assurance activities

Safety reviews Safety arguments Safety-oriented processes Run-time checking


Safety reviews

Review for correct intended function. Review for maintainable, understandable

structure. Review to verify algorithm and data structure

design against specification. Review to check code consistency with

algorithm and data structure design. Review adequacy of system testing.


Safety arguments

Safety arguments are intended to show that the system cannot reach in unsafe state.

These are weaker than correctness arguments which must show that the system code conforms to its specification.

They are generally based on proof by contradiction• Assume that an unsafe state can be reached;• Show that this is contradicted by the program code.

A graphical model of the safety argument may be developed.


Construction of a safety argument

Establish the safe exit conditions for a component or a program.

Starting from the END of the code, work backwards until you have identified all paths that lead to the exit of the code.

Assume that the exit condition is false. Show that, for each path leading to the exit that the

assignments made in that path contradict the assumption of an unsafe exit from the component.


Insulin delivery code

currentDose > maxDose?


Safety argument model

currentDose = 0

currentDose = 0

if statement 2then branch

executed

currentDose =maxDose

currentDose =maxDose

if statement 2else branchexecuted

if statement 2not executed

currentDose >= minimumDose andcurrentDose <= maxDose

or

currentDose >maxDose

administerInsulin

Contradiction

Contradiction Contradiction

Pre-conditionfor unsafe state

Overdoseadministered

assign assign


Program paths

Neither branch of if-statement 2 is executed• Can only happen if CurrentDose is >= minimumDose and

<= maxDose. then branch of if-statement 2 is executed

• currentDose = 0. else branch of if-statement 2 is executed

• currentDose = maxDose. In all cases, the post conditions contradict the

unsafe condition that the dose administered is greater than maxDose.


Safety related process activities

Creation of a hazard logging and monitoring system.

Appointment of project safety engineers. Extensive use of safety reviews. Creation of a safety certification system. Detailed configuration management (see

Chapter 29).


Run-time safety checking

During program execution, safety checks can be incorporated as assertions to check that the program is executing within a safe operating ‘envelope’.

Assertions can be included as comments (or using an assert statement in some languages). Code can be generated automatically to check these assertions.


Insulin administration with assertions


Topics covered



Security assessment

Security assessment has something in common with safety assessment.

It is intended to demonstrate that the system cannot enter some state (an unsafe or an insecure state) rather than to demonstrate that the system can do something.

However, there are differences• Safety problems are accidental; security problems are

deliberate;• Security problems are more generic - many systems

suffer from the same problems; Safety problems are mostly related to the application domain


Security validation

Experience-based validation• The system is reviewed and analysed against the types of

attack that are known to the validation team. Tool-based validation

• Various security tools such as password checkers are used to analyse the system in operation.

Tiger teams• A team is established whose goal is to breach the security

of the system by simulating attacks on the system. Formal verification

• The system is verified against a formal security specification.


Topics covered



Safety and dependability cases

Safety and dependability cases are structured documents that set out detailed arguments and evidence that a required level of safety or dependability has been achieved.

They are normally required by regulators before a system can be certified for operational use.


The system safety case

It is now normal practice for a formal safety case to be required for all safety-critical computer-based systems e.g. railway signalling, air traffic control, etc.

A safety case is:• A documented body of evidence that provides a

convincing and valid argument that a system is adequately safe for a given application in a given environment.

Arguments in a safety or dependability case can be based on formal proof, design rationale, safety proofs, etc. Process factors may also be included.


Components of a safety case

Component Description

System description An overview of the system and a description of its critical components.

Safety requirements The safety requirements abstracted from the system requirements specification.

Hazard and risk analysis

Documents describing the hazards and risks that have been identified and the measures taken to reduce risk.

Design analysis A set of structured arguments that justify why the design is safe.

Verification and validation

A description of the V & V procedures used and, where appropriate, the test plans for the system. Results of system V &V.

Review reports Records of all design and safety reviews.

Team competences Evidence of the competence of all of the team involved in safety-related systems development and validation.

Process QA Records of the quality assurance processes carried out during system development.

Change management processes

Records of all changes proposed, actions taken and, where appropriate, justification of the safety of these changes.

Associated safety cases

References to other safety cases that may impact on this safety case.


Argument structure

EVIDENCE

EVIDENCE

EVIDENCE

<< ARGUMENT >> CLAIM


Insulin pump argument

Claim: The maximum single dose computed by the insulin pump will not exceed maxDose.Evidence: Safety argument for insulin pump as shown in Figure 24.7Evidence: Test data sets for insulin pumpEvidence: Static analysis report for insulin pump softwareArgument: The safety argument presented shows that the maximum dose of insulin that can be

computed is equal to maxDose.In 400 tests, the value of Dose was correctly computed and never exceeded maxDose.The static analysis of the control software revealed no anomalies.Overall, it is reasonable to assume that the claim is justified.


Claim hierarchy

The maximum singledose computed bythe pump softwarewill not exceedmaxDose

maxDose is set upcorrectly when thepump is configured

maxDose is a safedose for the user ofthe insulin pump

The insulin pumpwill not deliver a

single dose of insulinthat is unsafe

In normaloperation, themaximum dosecomputed will notexceed maxDose

If the software fails,the maximum dose

computed will notexceed maxDose


Approaches to developing dependable systems: fault avoidance, fault detection and fault tolerance.

Fault avoidance measures include• The use of a well-defined repeatable process.• Dependable programming practices

The four aspects of program fault tolerance are: failure detection, damage assessment, fault recovery and fault repair.

Fault tolerant architectures employ redundancy and diversity.

Key points (Chapter 20)


Key points (Chapter 24)

Reliability measurement and prediction relies on exercising the system using an operational profile and modelling how the reliability of a software system improves as it is tested and faults are removed.

Safety arguments or proofs are a way of demonstrating that a hazardous condition can never occur.

Security validation may involve experience-based analysis, tool-based analysis or the use of ‘tiger teams’ to attack the system.

modified from sommerville’s originals software engineering, 7th edition. chapter 20&24 slide 1...

Documents

fault free software

software faults

software dependability

software customers

delivered software

mean software

developing faultfree

fault avoidance