Outsourcing, subcontracting and COTS Tor Stålhane

Contents We will cover the following topics Testing as a confidence building activity Testing and outsourcing Testing COTS components Sequential testing Simple Bayesian methods

Responsibility It is important to bear in mind that The company that brings the product to the marketplace carries full responsibility for the product’s quality. It is only possible to seek redress from the company we outsourced to if we can show that they did not fulfill their contract

Testing and confidence The role of testing during: Development – find and remove defects. Acceptance – build confidence in the component When we use testing for COTS or components where the development has been outsourced or developed by a subcontractor, we want to build confidence.

A product trustworthiness pattern Product is trustworthy Trustworthiness definition Product related Process related People related Environment definition System definition

Means to create product trust Based on the product trust pattern, we see that we build trust based on The product itself – e.g. a COTS component The process – how it was developed and tested People – the personnel that developed and tested the component

A process trustworthiness pattern Activity is trustworthy Argument by considering process Trustworthiness definition Process definition Team is competent Method address problem Process is traceable

Means to create process trust If we apply the pattern on the previous slide we see that trust in the process stems from three sources: Who does it – “Team is competent” How is it done – “Method addresses problem” We can check that the process is used correctly – “Process is traceable”

Testing and outsourcing If we outsource development, testing need to be an integrated part of the development process. Testing is thus a contract question. If we apply the trustworthiness pattern, we need to include requirements for The component - what The competence of the personnel – who The process – how

Outsourcing requirements - 1 When drawing up an outsourcing contract we should include: Personnel requirements – the right persons for the job. We need to see the CV for each person. Development process – including testing. The trust can come from – A certificate – e.g. ISO 9001 – Our own process audits

Outsourcing requirements - 2 Last but not least, we need to see and inspect some important artifacts: Project plan – when shall they do what? Test strategy – how will they test our component requirements? Test plan – how will the tests be run? Test log – what were the results of the tests?

Trust in the component The trust we have in the component will depend on how satisfied we are with the answers to the questions on the previous slide. We can, however, also build our trust on earlier experience with the company. The more we trust the company based on earlier experiences, the less rigor we will need in the contract.

Testing COTS We can test COTS by using e.g. black box testing or domain partition testing. Experience has shown that we will get the greatest benefit from our effort by focusing on tests for Internal robustness External robustness

Robustness – 1 There are several ways to categorize these two robustness modes. We will use the following definitions: Internal robustness – the ability to handle faults in the component or its environment. Here we will need wrappers, fault injection etc. External robustness – the ability to handle faulty input. Here we will only need the component “as is”

Robustness – 2 The importance of the two types of robustness will vary over component types. Internal robustness - components that are only visible inside the system border External robustness – components that are part of the user interface.

Internal robustness testing Internal robustness is the ability to Survive all erroneous situations, e.g. – Memory faults – both code and data – Failing function calls, including calls to OS functions Go to a defined, safe state after having given the error message Continued after the erroneous situation with a minimum loss of information.

Why do we need a wrapper By using a wrapper, we obtain some important effects: We control the component’s input, even though the component is inserted into the real system. We can collect and report input and output from the component. We can manipulate the exception handling and effect this component only.

What is a wrapper – 1 A wrapper has two essential characteristics An implementation that defines the functionality that we wish to access. This may, or may not be an object (one example of a non-object implementation would be a DLL whose functions we need to access). The “wrapper” class that provides an object interface to access the implementation and methods to manage the implementation. The client calls a method on the wrapper which access the implementation as needed to fulfill the request.

What is a wrapper – 2 A wrapper provides interface for, and services to, behavior that is defined elsewhere

Fault injection – 1 On order to test robustness, we need to be able to modify the component’s code – usually through fault injection. A fault is an abnormal condition or defect which may lead to a failure. Fault injection involves the deliberate insertion of faults or errors into a computer system in order to determine its response. The goal is not to recreate the conditions that produced the fault

Fault injection – 2 There are two steps to Fault Injection: Identify the set of faults that can occur within an application, module, class, method. E.g. if the application does not use the network then there’s no point in injecting network faults Exercise those faults to evaluate how the application responds. Does the application detect the fault, is it isolated and does the application recover?

Example byte[] readFile() throws IOException {... final InputStream is = new FileInputStream(…);... while((offset < bytes.length) && (numRead = is.read(bytes,offset,(bytes.length-offset))) >=0) offset += numRead;... is.close(); return bytes; } What could go wrong with this code? new FileInputStream() can throw FileNotFoundException InputStream.read() can throw IOException and IndexOutOfBoundsException and can return -1 for end of file is.close() can throw IOException

Fault injection – 3 Change the code – Replace the call to InputStream.read() with some local instrumented method – Create our own instrumented InputStream subclass possibly using mock objects – Inject the subclass via IoC (requires some framework such as PicoContainer or Spring) Comment out the code and replace with throw new IOException()

Fault injection – 4 Fault injection doesn’t have to be all on or all off. Logic can be coded around injected faults, e.g. for InputStream.read(): Throw IOException after n bytes are read Return -1 (EOF) one byte before the actual EOF occurs Sporadically mutate the read bytes

External robustness testing – 1 Error handling must be tested to show that Wrong input gives an error message The error message is understandable for the intended users Continued after the error with a minimum loss of information.

External robustness testing – 2 External robustness is the ability to Survive the input of faulty data – no crash Give an easy-to-understand error message that helps the user to correct the error in the input Go to a defined state Continue after the erroneous situation with a minimum loss of information.

Easy-to-understand message – 1 While all the other characteristics of the external robustness are easy too test, the error message requirement can only be tested by involving the users. We need to know which info the user needs in order to: Correct the faulty input Carry on with his work from the component’s current state

Easy-to-understand message – 2 The simple way to test the error messages is to have a user to Start working on a real task Insert an error in the input at some point during this task We can then observe how the user tries to get out of the situation and how satisfied he is with the assistance he get from the component.

Sequential testing In order to use sequential testing we need: Target failure rate p 1 Unacceptable failure rate p 2 and p 2 > p 1 The acceptable probability of doing a type I or type II decision error –  and  hese two values are used to compute a and b, given as

Background - 1 We will assume that the probability of failure is Binomially distributed. We have: The probability of and the probability of observing the number-of-defects sequence x 1, x 2,…x n can be written as

Background - 2 We will base our test on the log likelihood ratio, which is defined as: For the sake of simplicity, we introduce

The test statistics Using the notation from the previous slide, we find that We have p 1, p 2 << 1 and can thus use the approximations ln(1-p) = -p, v = (p 2 – p 1 ) and further that (u – v) = u

Sequential test – example We will use  = 0.05 and  = This will give us a = -1.6 and b = 2.8. We want a failure rate p 1 = and will not accept a component with a failure rate p 2 higher than 2* Thus we have u = and v = The lines for the “no decision” area are  x i (reject) = M*10 -3  x i (accept) = M*10 -3

Sequential test – example M xx 4*10 3 Accept

Sequential testing - summary Testing software – e.g. p < : The method needs a large number of tests. It should thus only be used for testing robustness based on automatically generated random input. Inspecting documents – e.g. p < : The method will give useful results even when inspecting a reasonable number of documents

Simple Bayesian methods Instead of building our trust on only test results, contractual obligations or past experience, we can combine these three factors. The easy way to do this is to use Bayesian statistics. We will give a short intro to Bayesian statistics and show one example of how it can be applied to software testing

Bayes theorem In a simplified version., Bayes’ theorem says that When we want to estimate B, we will use the likelihood of our observations as our P(B|A) and use P(B) to model our prior knowledge.

A Bayes model for reliability For reliability it is common to use a Beta distribution for the reliability and a Binomial distribution for the number of observed failures. This gives us the following results:

Estimates A priori we have that If x is the number of successes and n is the total number of tests, we have posteriori, that

Some Beta probabilities

Testing for reliability We will use a Beta distribution to model our prior knowledge. The knowledge is related to the company that developed the component or system, e.g. How competent are the developers How good is their process, e.g. – Are they ISO 9001 certified – Have we done a quality audit What is our earlier experience with this company

Modeling our confidence Several handbooks on Bayesian analysis contain tables where we specify two out of three values: R 1 : our mean expected reliability R 2 : our upper 5% limit. P(R > R 2 ) = 0.05 R 3 : our lower 5% limit. P(R < R 3 ) = 0.05 When we know our R-values, we can read the two parameters n 0 and x 0 out of a table.

The result We an now find the two parameters for the prior Beta distribution as:  = x 0  = n 0 – x 0 if we run N tests and observe x successes then the Bayesian estimate for the reliability is: R = (x + x 0 ) / (N + n 0 )

Sequential test with Bayes We can combine the info supplied by the Bayesian model with a standard sequential test chart by starting at (n 0 - x 0, n 0 ) instead of starting at origo as shown in the example on the next slide. Note - we need to use n 0 - x 0, since we are counting failures We have the same number of tests necessary, but n 0 of them are virtual and stems from our confidence in the company.

Sequential test with Bayes – example M xx 4*10 3 Accept n0n0