Test Design and Analysis for MTEST

This document provides test case identification and analysis for the MTEST marking and grading application. It includes real-world examples of software failures, test case scenarios based on software requirements, boundary value analysis, and error guessing test cases.

Running head: MTEST TEST DESIGN AND ANALYSIS
MTEST Test Design and Analysis
Name of the Student
Name of the University
Author Note

1
TEST CASE IDENTIFICATION FOR MTEST
Question 1: Real world example of software failure
A range of factors can be at play leading to software failures. In most cases these can
be due to making repeated changes without any plans for conducting follow up tests (Grottke
et al, 2015). Another vital role is played by the security aspect which is always under scanner.
When software programs are built without addressing the loopholes, attackers spare no time
in exploiting the vulnerabilities causing damages to both end user and the service provider
(Kanewala, Bieman & Ben‐Hur, 2016). Glitches and incomplete builds of the software
programs result in generation of erroneous output.
Flights in the aviation industry generally get cancelled because of bad weather and not
software. However in December 2014, one air traffic control centre (ATC) was compelled to
close down the airspace over London as the software tasked with management of departures
as well as arrivals started malfunctioning. Although this software got repaired almost
immediately and brought back up at the pretty fast, the consequences suffered as a result
major and affected flights widely. Heathrow ended up reporting a cancellation of more than
50 flights many of which had to turn back to their originating locations.
The entire incident was considered to be a technical problem at the Air Traffic
Control centre of Swanwick in England. This particular ATC is known for repeatedly
suffering from one issue to another. The responsible governing body NATS had to apologise
for the incident. Though official report by NATS blamed power outage, other reports
mentioned of a bug in the software responsible for sequencing landing and take offs that
could have been prevented if better software testing was conducted before implementation.

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TEST CASE IDENTIFICATION FOR MTEST
Question 2: Identifying the test cases according to the scenarios created
based on requirements of the software
Different software testing strategies utilized for identifying the test cases of the
marking and grading application MTEST are negative testing, error guessing test cases,
boundary value analysis and equivalence class partitioning (Scott et al, 2015). The list of test
cases are given in the table below.
MTEST Application Test Design
Test Case_ID Scenarios Test Cases
Verify that
input files with
question count
0 gets
executed
MTST001
Validate that
the title record
has data
Verify error
script for title
records having
no data
MTST002
Validate No. of
questions >= 1,
<= 999
Verify that
input files
having No. of
questions: 1
get executed
MTST003
Validate No. of
questions >= 1,
<= 999
Verify that
input files
having No. of
questions: 999
get executed
MTST004
Validate No. of
questions >= 1,
<= 999
Verify that
error script
present when
No. of
questions
equal 0
MTST005
Validate No. of
questions >= 1,
<= 999
Verify that
error script
present when
No. of
questions
equal 1000

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TEST CASE IDENTIFICATION FOR MTEST
MTST006
Validate record
set count in
columns (10 –
59)
Verify that
specific record
present for
questions 1 -
50 between
columns (10,
59)
MTST007
Validate record
set count in
columns (10 –
59)
Verify that two
records
present for
questions 51 –
100 between
columns (10,
59)
MTST008
Validate record
set count in
columns (10 –
59)
Verify that
three records
present for
questions 101 -
150 between
columns (10,
59)
MTST009
Validate record
set count in
columns (10 –
59)
Verify that
maximum
records
supported is
present for 999
questions
between
columns (10,
59)
MTST010
Validate
student name
in columns 1 to
9 of student
records
Verify that
student names
present in
columns 1 to 9
of student
records
MTST011
Validate
column 80 data
for student and
question
records
Verify that
error script
present for
input files
having wrong
column 80 data
for student and
question
records

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TEST CASE IDENTIFICATION FOR MTEST
Question 3: Test Cases on BVA (Boundary Value Analysis)
The software testing strategy Boundary Value Analysis or BVA deals with testing
applications by using values at each end of equivalence class partitions as per the requirement
specifications of the application (Niiranen et al, 2017). This is how the testing strategy
inspects the reliability of a software.
Boundary values observed for the application MTEST are found to be 1000, 999, 1
and 0 (Smelyanskiy, Sawaya, & Aspuru-Guzik, 2016). The test cases identified with this
testing strategy are:
 Verify that error script present when No. of questions equal 1000
 Verify that input files having No. of questions: 999 get executed
 Verify that input files having No. of questions: 1 get executed
 Verify that error script present when No. of questions equal 0
Question 4: Error guessing test cases for MTEST marking and grading
application
Error guessing is the type of testing strategy where the tester conducts the tests based
on his own skills and experience to figure out the errors in software programs (Qu et al,
2015). As a result, the experience and level of understanding of the test analyst plays a vital
role here. Error guessing test cases obtained for the MTEST grading application are:
 Verify that maximum records supported is present for 999 questions between columns (10,
59)
 Verify that error script present for input files having wrong column 80 data for student and
question records

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TEST CASE IDENTIFICATION FOR MTEST

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TEST CASE IDENTIFICATION FOR MTEST
References
Grottke, M., Kim, D. S., Mansharamani, R., Nambiar, M., Natella, R., & Trivedi, K. S.
(2015). Recovery from software failures caused by mandelbugs. IEEE Transactions
on Reliability, 65(1), 70-87.
Kanewala, U., Bieman, J. M., & Ben‐Hur, A. (2016). Predicting metamorphic relations for
testing scientific software: a machine learning approach using graph kernels. Software
testing, verification and reliability, 26(3), 245-269.
Niiranen, J., Kiendl, J., Niemi, A. H., & Reali, A. (2017). Isogeometric analysis for sixth-
order boundary value problems of gradient-elastic Kirchhoff plates. Computer
Methods in Applied Mechanics and Engineering, 316, 328-348.
Qu, M., Cui, N., Zou, B., & Wu, X. (2015, January). An Embedded Software Testing
Requirements Modeling Tool Describing Static and Dynamic Characteristics. In 2015
International Symposium on Computers & Informatics. Atlantis Press.
Scott, C., Wundsam, A., Raghavan, B., Panda, A., Or, A., Lai, J., ... & Acharya, H. B. (2015).
Troubleshooting blackbox SDN control software with minimal causal sequences.
ACM SIGCOMM Computer Communication Review, 44(4), 395-406.
Smelyanskiy, M., Sawaya, N. P., & Aspuru-Guzik, A. (2016). qHiPSTER: the quantum high
performance software testing environment. arXiv preprint arXiv:1601.07195.