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Test  Generation  And  Regression  Testing Q1  what  is  the  test  selection  problem? ,  Test  Adequacy: Answer:  It  is  essential  to  choose  tests  that  meet  the  four  criteria  of  sensitivity, standardization,  reliability  and  validity. It  is  very  difficult  to  achieve  the standards  required  if  an  organization  tries  to  develop  its  own  test  batteries, unless  it  employs  a  qualified  psychologist  or  obtains  professional  advice  from  a member  of  the  British  Psychological  Society.  This  organizati on,  with  the support  of  the  reputable  test  suppliers,  exercises  rigorous  control  over  who  can use  what  tests  and  the  standard  of  training  required  and  given.  Particular  care should  be  taken  when  selecting  personality  tests a bout.  Doitthere  are  a  lot  of  charlatans yourself  tests  are  always  suspect  unless  they  have  been  properly validated  and  realistic  norms  have  been  established.  They  should  not  be  used. Q2  what  is  Test  Generation  from  Predicates? Answer:   We propose  a  new  technique  for  automatic  genera tion  of  test  cases  for predicates.  Earlier  we  proposed  an  efficient  and  effective  test  generation strategy  for  Boolean  expressions.  We  now  extend  this  strategy  to  predicates. Our  new  strategy  addresses  a  number  of  issues,  including:  analysis  of dependencie s  between  relational  expressions  in  a  predicate  P;  generation  of  test constraints  for  P  based  on  the  detection  of  Boolean  and  relational  operator  faults in  P;  and  generation  of  actual  tests  according  to  the  generated  test  constraints for  P.  We  propose  the use  of  constraint  logic  programming  (CLP)  to  automate test  data  generation  for  a  predicate.  Furthermore,  we  propose  an  incremental approach  to  apply  CLP  techniques  to  solve  a  constraint  system.  Since  our technique  is  specificationbased,  it  can  facilitate for  actual  tests. Q3  what  is  fault  model? Answer: A fault  model generation  of  expected  outputs is  an  engineering  model  of  something  that  could  go wrong  in  the  construction  or  operation  of  a  piece  of  equipment.  From  the  model, the  designer  or  user  can  then predict  the  consequences  of  this  particular  fault. Fault  models  can  be  used  in  almost  all  branches  of  engineering. Static  faults,  which  give  incorrect  values  at  any  speed  and  sensitized  by performing  only  one  operation:
. the stuck-at fault model. A signal, or gate output, is stuck at a 0 or 1 value, independent of the inputs to the circuit.  the bridging fault model. Two signals are connected together when they should not be. Depending on the logic circuitry employed, this may result in a wired-OR or wired-AND logic function. Since there are O(n^2) potential bridging faults, they are normally restricted to signals that are physically adjacent in the design.  the transistor faults. This model is used to describe faults for CMOS logic gates. At transistor level, a transistor maybe stuck-short or stuck-open. In stuck-short, a transistor behaves as it is always conducts (or stuck-on), and stuck-open is when a transistor never conducts current (or stuck-off). Stuck-short will produce a short between VDD and VSS.  The open fault model. Here a wire is assumed broken, and one or more inputs are disconnected from the output that should drive them. As with bridging faults, the resulting behavior depends on the circuit implementation. A fault model, falls under one of the following assumptions:  single fault assumption: only one fault occur in a circuit. if we define k possible fault types in our fault model the circuit has n signal lines, by single fault assumption, the total number of single faults is k×n.  multiple fault assumption: multiple faults may occur in a circuit.  Q4 what are difference between Control Flow Data- Flow? Answer: If we discuss the SSIS architecture then it is vital for you to understand these two terms, Data flow, and Control flow. One excellent way to know about both terms is to check out the working of components and how they are connected together. For the Control Flow, the task is the smallest piece of work that you have to complete on priority. If a particular task is not completed as needed, then you cannot switch to other tasks. For the Data Flow, Data source, destination, and the data transformation are the major components and their functioning is highly different from a task. When Data is transformed into anything meaningful, it is done on the basis of logic how are components connected together, data management, etc. Both Control Flow and Data Flow work similar to an objective of processing objects and there are connectors to make a bridge among them. Still, there is an ocean of differences between both of the terms. For example, you cannot pass the data among components using control flow but it works as a task coordinator only. Here are some of the major objectives of the control flow.  It helps in orchestrating workflows.  It is more process-oriented.  It can help in executing tasks either serially or parallelly.  It helps in processing data synchronously. As we have discussed earlier, tasks in the control flow are majorly designed to execute either serially or parallelly. Further, it is possible to divide a task into multiple branches that can be executed in parallel one by one. Here,you can also define the priority about which task to be executed first. For example, if there are a few tasks that are connected in a linear fashion, then they can be serialized and only one task has to be executed at one time. On the other side, Data Flow can split, merge, or branch tasks for parallel processing but it is absolutely different from the Control Flow in SSIS. Here are some of the most important features of Data Flow in SSIS.  It is more information-oriented, not based on processes.  It can group data together based on logic and transforming it into meaningful content.  Multiple data batches can be coordinated for effective processing.  Data is extracted from the source and loaded to the destination later. The major difference between control flow and data flow in SSIS is that Control Flow can execute only one task at a time in a linear fashion. On the other hand, Data Flow can perform multiple transformations at the same time. So this was it on SSIS control flow vs data flow, now let’s understand how data packets are executed in SSIS. Q5 what is Combinatorial Designs? Answer: Combinatorial design theory is the part of combinatorial mathematics that deals with the existence, construction and properties of systems of finite sets whose arrangements satisfy generalized concepts of balance and/or symmetry. These concepts are not made precise so that a wide range of objects can be thought of as being under the same umbrella. At times this might involve the numerical sizes of set intersections as in block designs, while at other times it could involve the spatial arrangement of entries in an array as in sudoku grids. 
Combinatorial design theory can be applied to the area of design of experiments. Some of the basic theory of combinatorial designs originated in the statistician Ronald Fisher's work on the design of biological experiments. Modern applications are also found in a wide gamut of areas including finite geometry, tournament scheduling, lotteries, mathematical chemistry, mathematical biology, algorithm design and analysis, networking, group testing and cryptography. Given a certain number n of people, is it possible to assign them to sets so that each person is in at least one set, each pair of people is in exactly one set together, every two sets have exactly one person in common, and no set contains everyone, all but one person, or exactly one person? The answer depends on n. This has a solution only if n has the form q2 + q + 1. It is less simple to prove that a solution exists if q is a prime power. It is conjectured that these are the only solutions. It has been further shown that if a solution exists for q congruent to 1 or 2 mod 4, then q is a sum of two square numbers. This last result, the Bruck–Ryser theorem, is proved by a combination of constructive methods based on finite fields and an application of quadratic forms. When such a structure does exist, it is called a finite projective plane; thus showing how finite geometry and combinatorics intersect. When q = 2, the projective plane is called the Fano plane.     
Anurag

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