earticle

논문검색

Theoretical Investigations to Random Testing Variants and its Implications

초록

영어

In real world Testing is the most challenging job in software development. In these days of the information technology epoch, the software has become the lifeline of every human activity. It may not be hyperbole, if someone states that our lives will come to stand-still if every software machine in the universe stops working! When software plays such a crucial role in our lives, it is very important that the software we use should be very high quality and reliability. Even the small gremlin is there in any software that causes huge disaster. These are the examples PATRIOT MISSILE- the patriot missile example shows how a small software bug accumulation of error due to rounding off a number can lead to catastrophe. And ARIANE-5- European Space Agency launched the ariane5 satellite launch vehicle. Exactly 40 seconds after lift-off at an attitude of 3700meters, the launcher devastated and became a ball of fire. This type of mint errors can’t be covered in normal testing’s like Unit Testing, Integration Testing, etc. For that reason RANDOM TESTING is introduced. Random testing is a dominant or a commanding tool in finding low-frequency bugs that are nearly impossible to find using other methods. A Low-frequency bug sometimes leads to system to crash, hence these have to be identified and removed. By using a test, Oracle one may also detect non-crashing errors in the system. Here the objective of work is to study the advantage and various implications of Random Testing, later we will develop one assumed application “Trading system”, to that we will apply random testing to accentuate theoretical and practical implications including variants of Random Testing.

목차

Abstract
 1. Introduction
 2. Random Testing [RT]
  2.1. Effectiveness of Random Testing
  2.2. Scalability
 3. Theoretical Implications of Random Testing
  3.1. Random Testing is not Applicable for Misapplication of Methods
  3.2 Reusable Components
  3.3 Predictability
  3.4 The problem of operative distribution
 4. Practical Implications
  4.1. Automated Oracle
  4.2. Small Size Projects
  4.3. Generating Pseudorandom Number Values
  4.4. Similar Test Case Generations
  4.5. Generation of Invalid Test Cases
  4.6. Automated Tool Support
 5. Origin and Definition of the Problem
 6. Results
 7. Future Work
 References

저자정보

  • K. Koteswara Rao Research Scholar @JNTUK, CSE Department, GMRIT
  • Prof GSVP Raju Department of CS&ST, SDE, Andhra University, Vizag, AP, India

참고문헌

자료제공 : 네이버학술정보

    함께 이용한 논문

      ※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

      0개의 논문이 장바구니에 담겼습니다.