Journal Title
Title of Journal: Empir Software Eng
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Abbravation: Empirical Software Engineering
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Authors: Jeff Offutt Chandra Alluri
Publish Date: 2012/09/23
Volume: 19, Issue: 3, Pages: 558-581
Abstract
This paper presents results from an industrial study that applied input space partitioning and semiautomated requirements modeling to largescale industrial software specifically financial calculation engines Calculation engines are used in financial service applications such as banking mortgage insurance and trading to compute complex multiconditional formulas to make high risk financial decisions They form the heart of financial applications and can cause severe economic harm if incorrect Controllability and observability of these calculation engines are low so robust and sophisticated test methods are needed to ensure the results are valid However the industry norm is to use pure humanbased requirementsdriven test design usually with very little automation The Federal Home Loan Mortgage Corporation FHLMC commonly known as Freddie Mac concerned that these test design techniques may lead to ineffective and inefficient testing partnered with a university to use high quality sophisticated test design on several ongoing projects The goal was to determine if such test design can be costeffective on this type of critical software In this study input space partitioning along with automation were applied with the help of several specialpurpose tools to validate the effectiveness of input space partitioning Results showed that these techniques were far more effective finding more software faults and more efficient requiring fewer tests and less labor and the managers reported that the testing cycle was reduced from five human days to 05 This study convinced upper management to begin infusing this approach into other software development projects
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