Regression testing makes sure that upgradation of software in terms of adding new features or for bug fixing purposes should not hamper previously working functionalities. Whenever a software is upgraded or modified, a set of test cases are run on each of its functions to assure that the change to that function is not affecting other parts of the software that were previously running flawlessly. For achieving this, all existing test cases need to run as well as new test cases might be required to be created. It is not feasible to re- execute every test case for all the functions of a given software, because if there is a large number of test cases to be run, then a lot of time and effort would be required. This problem can be addressed by prioritizing test cases. Test case prioritization technique reorders the priority in which test cases are implemented, in an attempt to ensure that maximum faults are uncovered early on by the high priority test cases implemented first. In this paper we propose an optimized test case prioritization technique using Ant Colony Optimization (ACO) to reduce the cost, effort and time taken to perform regression testing and also uncover maximum faults. Comparison of different techniques such as Retest All, Test Case Minimization, Test Case Prioritization, Random Test Case Selection and Test Case Prioritization using ACO is also depicted.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Chapter 6 - Transitioning Manual Testing to an Automation EnvironmentNeeraj Kumar Singh
This is the chapter 6 of ISTQB Advance Test Automation Engineer certification. This presentation helps aspirants understand and prepare content of certification.
QUALITY METRICS OF TEST SUITES IN TESTDRIVEN DESIGNED APPLICATIONSijseajournal
New techniques for writing and developing software have evolved in recent years. One is Test-Driven
Development (TDD) in which tests are written before code. No code should be written without first having
a test to execute it. Thus, in terms of code coverage, the quality of test suites written using TDD should be
high.
In this work, we analyze applications written using TDD and traditional techniques. Specifically, we
demonstrate the quality of the associated test suites based on two quality metrics: 1) structure-based
criterion, 2) fault-based criterion. We learn that test suites with high branch test coverage will also have
high mutation scores, and we especially reveal this in the case of TDD applications. We found that TestDriven
Development is an effective approach that improves the quality of the test suite to cover more of the
source code and also to reveal more.
This is chapter 2 of ISTQB Advance Test Manager certification. This presentation helps aspirants understand and prepare the content of the certification.
Software testing is an activity which is aimed for evaluating quality of a program and also for improving it, by identifying defects and problems. Software testing strives for achieving its goal (both implicit and explicit) but it has certain limitations, still testing can be done more effectively if certain established principles are to be followed. In spite of having limitations, software testing continues to dominate other verification techniques like static analysis, model checking and proofs. So it is indispensable to understand the goals, principles and limitations of software testing so that the effectiveness of software testing could be maximized.
Software Testing and Quality Assurance Assignment 3Gurpreet singh
Short questions :
Que 1 : Define Software Testing.
Que 2 : What is risk identification ?
Que 3 : What is SCM ?
Que 4 : Define Debugging.
Que 5 : Explain Configuration audit.
Que 6 : Differentiate between white box testing & black box testing.
Que 7 : What do you mean by metrics ?
Que 8 : What do you mean by version control ?
Que 9 : Explain Object Oriented Software Engineering.
Que 10 : What are the advantages and disadvantages of manual testing tools ?
Long Questions:
Que 1 : What do you mean by baselines ? Explain their importance.
Que 2 : What do you mean by change control ? Explain the various steps in detail.
Que 3 : Explain various types of testing in detail.
Que 4 : Differentiate between automated testing and manual testing.
Que 5 : What is web engineering ? Explain in detail its model and features.
Software testing means to cut errors, reduce
maintenances and to short the cost of software development. Many
software development and testing methods are used from many
past years to improve software quality and software reliability. The
major problem arises in the field of software testing is to find the
best test case to performs testing of software. There are many kind
of testing methods used for making a best case. Teasing is a
important part of software development cycle .The process of
testing is not bounded to detection of ’error’ in software but also
enhances the surety of proper functioning and help to find out the
functional and non functional particularities .Testing activities
focuses on the overall progress of software.
Configuration Navigation Analysis Model for Regression Test Case Prioritizationijsrd.com
Regression testing has been receiving increasing attention nowadays. Numerous regression testing strategies have been proposed. Most of them take into account various metrics like cost as well as the ability to find faults quickly thereby saving overall testing time. In this paper, a new model called the Configuration Navigation Analysis Model is proposed which tries to consider all stakeholders and various testing aspects while prioritizing regression test cases.
A NOVEL APPROACH FOR TEST CASEPRIORITIZATIONIJCSEA Journal
Test case prioritization techniques basically schedule the execution of test cases in a definite order such that to attain an objective function with greater efficiency. This scheduling of test cases improves the results of regression testing. Test case prioritization techniques order the test cases such that the most important ones are executed first encountering the faults first and thus makes the testing effective. In this paper an approach is presented which calculates the product of statement coverage and function calls. The results illustrate the effectiveness of formula computed with the help of APFD metric.
Real time implementation of the software system requires being more versatile. In the maintenance phase, the modified system under regression testing must assure that the existing system remains defect free. Test case prioritization technique of regression testing includes code as well as model based methods of prioritizing the test cases. System model based test case prioritization can detect the severe faults early as compare to the code based test case prioritization. Model based prioritization techniques based on requirements in a cost effective manner has not been taken for study so far. Model based testing used to test the functionality of the software system based on requirement. An effective model based approach is defined for prioritizing test cases and to generate the effective test sequence. The test cases are rescheduled based on requirement analysis and user view analysis. With the use of weighted approach the overall cost is estimated to test the functionality of the model elements. Here, the genetic approach has been applied to generate efficient test path. The regression cost in terms of effort has been reduced under model based prioritization approach.
Regression testing concentrates on finding defects after a major code change has occurred. Specifically, it
exposes software regressions or old bugs that have reappeared. It is an expensive testing process that has
been estimated to account for almost half of the cost of software maintenance. To improve the regression
testing process, test case prioritization techniques organizes the execution level of test cases. Further, it
gives an improved rate of fault identification, when test suites cannot run to completion.
Chapter 6 - Transitioning Manual Testing to an Automation EnvironmentNeeraj Kumar Singh
This is the chapter 6 of ISTQB Advance Test Automation Engineer certification. This presentation helps aspirants understand and prepare content of certification.
QUALITY METRICS OF TEST SUITES IN TESTDRIVEN DESIGNED APPLICATIONSijseajournal
New techniques for writing and developing software have evolved in recent years. One is Test-Driven
Development (TDD) in which tests are written before code. No code should be written without first having
a test to execute it. Thus, in terms of code coverage, the quality of test suites written using TDD should be
high.
In this work, we analyze applications written using TDD and traditional techniques. Specifically, we
demonstrate the quality of the associated test suites based on two quality metrics: 1) structure-based
criterion, 2) fault-based criterion. We learn that test suites with high branch test coverage will also have
high mutation scores, and we especially reveal this in the case of TDD applications. We found that TestDriven
Development is an effective approach that improves the quality of the test suite to cover more of the
source code and also to reveal more.
This is chapter 2 of ISTQB Advance Test Manager certification. This presentation helps aspirants understand and prepare the content of the certification.
Software testing is an activity which is aimed for evaluating quality of a program and also for improving it, by identifying defects and problems. Software testing strives for achieving its goal (both implicit and explicit) but it has certain limitations, still testing can be done more effectively if certain established principles are to be followed. In spite of having limitations, software testing continues to dominate other verification techniques like static analysis, model checking and proofs. So it is indispensable to understand the goals, principles and limitations of software testing so that the effectiveness of software testing could be maximized.
Software Testing and Quality Assurance Assignment 3Gurpreet singh
Short questions :
Que 1 : Define Software Testing.
Que 2 : What is risk identification ?
Que 3 : What is SCM ?
Que 4 : Define Debugging.
Que 5 : Explain Configuration audit.
Que 6 : Differentiate between white box testing & black box testing.
Que 7 : What do you mean by metrics ?
Que 8 : What do you mean by version control ?
Que 9 : Explain Object Oriented Software Engineering.
Que 10 : What are the advantages and disadvantages of manual testing tools ?
Long Questions:
Que 1 : What do you mean by baselines ? Explain their importance.
Que 2 : What do you mean by change control ? Explain the various steps in detail.
Que 3 : Explain various types of testing in detail.
Que 4 : Differentiate between automated testing and manual testing.
Que 5 : What is web engineering ? Explain in detail its model and features.
Software testing means to cut errors, reduce
maintenances and to short the cost of software development. Many
software development and testing methods are used from many
past years to improve software quality and software reliability. The
major problem arises in the field of software testing is to find the
best test case to performs testing of software. There are many kind
of testing methods used for making a best case. Teasing is a
important part of software development cycle .The process of
testing is not bounded to detection of ’error’ in software but also
enhances the surety of proper functioning and help to find out the
functional and non functional particularities .Testing activities
focuses on the overall progress of software.
Configuration Navigation Analysis Model for Regression Test Case Prioritizationijsrd.com
Regression testing has been receiving increasing attention nowadays. Numerous regression testing strategies have been proposed. Most of them take into account various metrics like cost as well as the ability to find faults quickly thereby saving overall testing time. In this paper, a new model called the Configuration Navigation Analysis Model is proposed which tries to consider all stakeholders and various testing aspects while prioritizing regression test cases.
A NOVEL APPROACH FOR TEST CASEPRIORITIZATIONIJCSEA Journal
Test case prioritization techniques basically schedule the execution of test cases in a definite order such that to attain an objective function with greater efficiency. This scheduling of test cases improves the results of regression testing. Test case prioritization techniques order the test cases such that the most important ones are executed first encountering the faults first and thus makes the testing effective. In this paper an approach is presented which calculates the product of statement coverage and function calls. The results illustrate the effectiveness of formula computed with the help of APFD metric.
Real time implementation of the software system requires being more versatile. In the maintenance phase, the modified system under regression testing must assure that the existing system remains defect free. Test case prioritization technique of regression testing includes code as well as model based methods of prioritizing the test cases. System model based test case prioritization can detect the severe faults early as compare to the code based test case prioritization. Model based prioritization techniques based on requirements in a cost effective manner has not been taken for study so far. Model based testing used to test the functionality of the software system based on requirement. An effective model based approach is defined for prioritizing test cases and to generate the effective test sequence. The test cases are rescheduled based on requirement analysis and user view analysis. With the use of weighted approach the overall cost is estimated to test the functionality of the model elements. Here, the genetic approach has been applied to generate efficient test path. The regression cost in terms of effort has been reduced under model based prioritization approach.
Regression testing concentrates on finding defects after a major code change has occurred. Specifically, it
exposes software regressions or old bugs that have reappeared. It is an expensive testing process that has
been estimated to account for almost half of the cost of software maintenance. To improve the regression
testing process, test case prioritization techniques organizes the execution level of test cases. Further, it
gives an improved rate of fault identification, when test suites cannot run to completion.
A Complexity Based Regression Test Selection StrategyCSEIJJournal
Software is unequivocally the foremost and indispensable entity in this technologically driven world.
Therefore quality assurance, and in particular, software testing is a crucial step in the software
development cycle. This paper presents an effective test selection strategy that uses a Spectrum of
Complexity Metrics (SCM). Our aim in this paper is to increase the efficiency of the testing process by
significantly reducing the number of test cases without having a significant drop in test effectiveness. The
strategy makes use of a comprehensive taxonomy of complexity metrics based on the product level (class,
method, statement) and its characteristics.We use a series of experiments based on three applications with
a significant number of mutants to demonstrate the effectiveness of our selection strategy.For further
evaluation, we compareour approach to boundary value analysis. The results show the capability of our
approach to detect mutants as well as the seeded errors.
An Adaptive Hybrid Technique approach of Test Case PrioritizationINFOGAIN PUBLICATION
Test-Case Prioritization is the method to schedule any execution order of the test with the purpose of maximizing some objects like revealing faults early. In this paper we have proposed the hybrid approach for the purpose of the test case prioritization involving Robust Genetic Algorithm to improve the parameters like APSC and execution time. This technique involves robust approach, parent generation, cross-over and mutation over each test-case and then calculates APSC and execution time.
EXTRACTING THE MINIMIZED TEST SUITE FOR REVISED SIMULINK/STATEFLOW MODELijaia
Test case generation techniques are successfully employed to generate test cases from a formal model. A problem is that as the model evolves, test suites tend to grow in size, making it too costly to execute entire test suites. This paper aims to propose a practical approach to reduce the size of test suites for modified Simulink/Stateflow (SL/SF) model, which is popularly used for modeling software behavior in many industries like automobile manufacturers. The model for describing a system is frequently modified until it is fixed. The proposed technique is capable of extracting the minimized sized test suite in terms of test coverage, by taking into account both the modified and the affected portion of revised SL/SF model. Two real models for the ECUs deployed in a commercial car are used for an empirical study.
Software testing is an important activity of the software development process. Software testing is most
efforts consuming phase in software development. One would like to minimize the effort and maximize the
number of faults detected and automated test case generation contributes to reduce cost and time effort.
Hence test case generation may be treated as an optimization problem In this paper we have used genetic
algorithm to optimize the test case that are generated applying conditional coverage on source code. Test
case data is generated automatically using genetic algorithm are optimized and outperforms the test cases
generated by random testing.
ENHANCING ENGLISH WRITING SKILLS THROUGH INTERNET-PLUS TOOLS IN THE PERSPECTI...ijfcstjournal
This investigation delves into incorporating a hybridized memetic strategy within the framework of English
composition pedagogy, leveraging Internet Plus resources. The study aims to provide an in-depth analysis
of how this method influences students’ writing competence, their perceptions of writing, and their
enthusiasm for English acquisition. Employing an explanatory research design that combines qualitative
and quantitative methods, the study collects data through surveys, interviews, and observations of students’
writing performance before and after the intervention. Findings demonstrate a beneficial impact of
integrating the memetic approach alongside Internet Plus tools on the writing aptitude of English as a
Foreign Language (EFL) learners. Students reported increased engagement with writing, attributing it to
the use of Internet plus tools. They also expressed that the memetic approach facilitated a deeper
understanding of cultural and social contexts in writing. Furthermore, the findings highlight a significant
improvement in students’ writing skills following the intervention. This study provides significant insights
into the practical implementation of the memetic approach within English writing education, highlighting
the beneficial contribution of Internet Plus tools in enriching students' learning journeys.
A SURVEY TO REAL-TIME MESSAGE-ROUTING NETWORK SYSTEM WITH KLA MODELLINGijfcstjournal
Messages routing over a network is one of the most fundamental concept in communication which requires
simultaneous transmission of messages from a source to a destination. In terms of Real-Time Routing, it
refers to the addition of a timing constraint in which messages should be received within a specified time
delay. This study involves Scheduling, Algorithm Design and Graph Theory which are essential parts of
the Computer Science (CS) discipline. Our goal is to investigate an innovative and efficient way to present
these concepts in the context of CS Education. In this paper, we will explore the fundamental modelling of
routing real-time messages on networks. We study whether it is possible to have an optimal on-line
algorithm for the Arbitrary Directed Graph network topology. In addition, we will examine the message
routing’s algorithmic complexity by breaking down the complex mathematical proofs into concrete, visual
examples. Next, we explore the Unidirectional Ring topology in finding the transmission’s
“makespan”.Lastly, we propose the same network modelling through the technique of Kinesthetic Learning
Activity (KLA). We will analyse the data collected and present the results in a case study to evaluate the
effectiveness of the KLA approach compared to the traditional teaching method.
A COMPARATIVE ANALYSIS ON SOFTWARE ARCHITECTURE STYLESijfcstjournal
Software architecture is the structural solution that achieves the overall technical and operational
requirements for software developments. Software engineers applied software architectures for their
software system developments; however, they worry the basic benchmarks in order to select software
architecture styles, possible components, integration methods (connectors) and the exact application of
each style.
The objective of this research work was a comparative analysis of software architecture styles by its
weakness and benefits in order to select by the programmer during their design time. Finally, in this study,
the researcher has been identified architectural styles, weakness, and Strength and application areas with
its component, connector and Interface for the selected architectural styles.
SYSTEM ANALYSIS AND DESIGN FOR A BUSINESS DEVELOPMENT MANAGEMENT SYSTEM BASED...ijfcstjournal
A design of a sales system for professional services requires a comprehensive understanding of the
dynamics of sale cycles and how key knowledge for completing sales is managed. This research describes
a design model of a business development (sales) system for professional service firms based on the Saudi
Arabian commercial market, which takes into account the new advances in technology while preserving
unique or cultural practices that are an important part of the Saudi Arabian commercial market. The
design model has combined a number of key technologies, such as cloud computing and mobility, as an
integral part of the proposed system. An adaptive development process has also been used in implementing
the proposed design model.
AN ALGORITHM FOR SOLVING LINEAR OPTIMIZATION PROBLEMS SUBJECTED TO THE INTERS...ijfcstjournal
Frank t-norms are parametric family of continuous Archimedean t-norms whose members are also strict
functions. Very often, this family of t-norms is also called the family of fundamental t-norms because of the
role it plays in several applications. In this paper, optimization of a linear objective function with fuzzy
relational inequality constraints is investigated. The feasible region is formed as the intersection of two
inequality fuzzy systems defined by frank family of t-norms is considered as fuzzy composition. First, the
resolution of the feasible solutions set is studied where the two fuzzy inequality systems are defined with
max-Frank composition. Second, some related basic and theoretical properties are derived. Then, a
necessary and sufficient condition and three other necessary conditions are presented to conceptualize the
feasibility of the problem. Subsequently, it is shown that a lower bound is always attainable for the optimal
objective value. Also, it is proved that the optimal solution of the problem is always resulted from the
unique maximum solution and a minimal solution of the feasible region. Finally, an algorithm is presented
to solve the problem and an example is described to illustrate the algorithm. Additionally, a method is
proposed to generate random feasible max-Frank fuzzy relational inequalities. By this method, we can
easily generate a feasible test problem and employ our algorithm to it.
LBRP: A RESILIENT ENERGY HARVESTING NOISE AWARE ROUTING PROTOCOL FOR UNDER WA...ijfcstjournal
Underwater detector network is one amongst the foremost difficult and fascinating analysis arenas that
open the door of pleasing plenty of researchers during this field of study. In several under water based
sensor applications, nodes are square measured and through this the energy is affected. Thus, the mobility
of each sensor nodes are measured through the water atmosphere from the water flow for sensor based
protocol formations. Researchers have developed many routing protocols. However, those lost their charm
with the time. This can be the demand of the age to supply associate degree upon energy-efficient and
ascendable strong routing protocol for under water actuator networks. During this work, the authors tend
to propose a customary routing protocol named level primarily based routing protocol (LBRP), reaching to
offer strong, ascendable and energy economical routing. LBRP conjointly guarantees the most effective use
of total energy consumption and ensures packet transmission which redirects as an additional reliability in
compare to different routing protocols. In this work, the authors have used the level of forwarding node,
residual energy and distance from the forwarding node to the causing node as a proof in multicasting
technique comparisons. Throughout this work, the authors have got a recognition result concerning about
86.35% on the average in node multicasting performances. Simulation has been experienced each in a
wheezy and quiet atmosphere which represents the endorsement of higher performance for the planned
protocol.
STRUCTURAL DYNAMICS AND EVOLUTION OF CAPSULE ENDOSCOPY (PILL CAMERA) TECHNOLO...ijfcstjournal
This research paper examined and re-evaluates the technological innovation, theory, structural dynamics
and evolution of Pill Camera(Capsule Endoscopy) technology in redirecting the response manner of small
bowel (intestine) examination in human. The Pill Camera (Endoscopy Capsule) is made up of sealed
biocompatible material to withstand acid, enzymes and other antibody chemicals in the stomach is a
technology that helps the medical practitioners especially the general physicians and the
gastroenterologists to examine and re-examine the intestine for possible bleeding or infection. Before the
advent of the Pill camera (Endoscopy Capsule) the colonoscopy was the local method used but research
showed that some parts (bowel) of the intestine can’t be reach by mere traditional method hence the need
for Pill Camera. Countless number of deaths from stomach disease such as polyps, inflammatory bowel
(Crohn”s diseases), Cancers, Ulcer, anaemia and tumours of small intestines which ordinary would have
been detected by sophisticated technology like Pill Camera has become norm in the developing nations.
Nevertheless, not only will this paper examine and re-evaluate the Pill Camera Innovation, theory,
Structural dynamics and evolution it unravelled and aimed to create awareness for both medical
practitioners and the public.
AN OPTIMIZED HYBRID APPROACH FOR PATH FINDINGijfcstjournal
Path finding algorithm addresses problem of finding shortest path from source to destination avoiding
obstacles. There exist various search algorithms namely A*, Dijkstra's and ant colony optimization. Unlike
most path finding algorithms which require destination co-ordinates to compute path, the proposed
algorithm comprises of a new method which finds path using backtracking without requiring destination
co-ordinates. Moreover, in existing path finding algorithm, the number of iterations required to find path is
large. Hence, to overcome this, an algorithm is proposed which reduces number of iterations required to
traverse the path. The proposed algorithm is hybrid of backtracking and a new technique(modified 8-
neighbor approach). The proposed algorithm can become essential part in location based, network, gaming
applications. grid traversal, navigation, gaming applications, mobile robot and Artificial Intelligence.
EAGRO CROP MARKETING FOR FARMING COMMUNITYijfcstjournal
The Major Occupation in India is the Agriculture; the people involved in the Agriculture belong to the poor
class and category. The people of the farming community are unaware of the new techniques and Agromachines, which would direct the world to greater heights in the field of agriculture. Though the farmers
work hard, they are cheated by agents in today’s market. This serves as a opportunity to solve
all the problems that farmers face in the current world. The eAgro crop marketing will serve as a better
way for the farmers to sell their products within the country with some mediocre knowledge about using
the website. This would provide information to the farmers about current market rate of agro-products,
their sale history and profits earned in a sale. This site will also help the farmers to know about the market
information and to view agricultural schemes of the Government provided to farmers.
EDGE-TENACITY IN CYCLES AND COMPLETE GRAPHSijfcstjournal
It is well known that the tenacity is a proper measure for studying vulnerability and reliability in graphs.
Here, a modified edge-tenacity of a graph is introduced based on the classical definition of tenacity.
Properties and bounds for this measure are introduced; meanwhile edge-tenacity is calculated for cycle
graphs and also for complete graphs.
COMPARATIVE STUDY OF DIFFERENT ALGORITHMS TO SOLVE N QUEENS PROBLEMijfcstjournal
This Paper provides a brief description of the Genetic Algorithm (GA), the Simulated Annealing (SA)
Algorithm, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm and attempts to
explain the way as how the Proposed Genetic Algorithm (GA), the Proposed Simulated Annealing (SA)
Algorithm using GA, the Backtracking (BT) Algorithm and the Brute Force (BF) Search Algorithm can be
employed in finding the best solution of N Queens Problem and also, makes a comparison between these
four algorithms. It is entirely a review based work. The four algorithms were written as well as
implemented. From the Results, it was found that, the Proposed Genetic Algorithm (GA) performed better
than the Proposed Simulated Annealing (SA) Algorithm using GA, the Backtracking (BT) Algorithm and
the Brute Force (BF) Search Algorithm and it also provided better fitness value (solution) than the
Proposed Simulated Annealing Algorithm (SA) using GA, the Backtracking (BT) Algorithm and the Brute
Force (BF) Search Algorithm, for different N values. Also, it was noticed that, the Proposed GA took more
time to provide result than the Proposed SA using GA.
PSTECEQL: A NOVEL EVENT QUERY LANGUAGE FOR VANET’S UNCERTAIN EVENT STREAMSijfcstjournal
In recent years, the complex event processing technology has been used to process the VANET’s temporal
and spatial event streams. However, we usually cannot get the accurate data because the device sensing
accuracy limitations of the system. We only can get the uncertain data from the complex and limited
environment of the VANET. Because the VANET’s event streams are consist of the uncertain data, so they
are also uncertain. How effective to express and process these uncertain event streams has become the core
issue for the VANET system. To solve this problem, we propose a novel complex event query language
PSTeCEQL (probabilistic spatio-temporal constraint event query language). Firstly, we give the definition
of the possible world model of VANET’s uncertain event streams. Secondly, we propose an event query
language PSTeCEQL and give the syntax and the operational semantics of the language. Finally, we
illustrate the validity of the PSTeCEQL by an example.
CLUSTBIGFIM-FREQUENT ITEMSET MINING OF BIG DATA USING PRE-PROCESSING BASED ON...ijfcstjournal
Now a day enormous amount of data is getting explored through Internet of Things (IoT) as technologies
are advancing and people uses these technologies in day to day activities, this data is termed as Big Data
having its characteristics and challenges. Frequent Itemset Mining algorithms are aimed to disclose
frequent itemsets from transactional database but as the dataset size increases, it cannot be handled by
traditional frequent itemset mining. MapReduce programming model solves the problem of large datasets
but it has large communication cost which reduces execution efficiency. This proposed new pre-processed
k-means technique applied on BigFIM algorithm. ClustBigFIM uses hybrid approach, clustering using kmeans algorithm to generate Clusters from huge datasets and Apriori and Eclat to mine frequent itemsets
from generated clusters using MapReduce programming model. Results shown that execution efficiency of
ClustBigFIM algorithm is increased by applying k-means clustering algorithm before BigFIM algorithm as
one of the pre-processing technique.
A MUTATION TESTING ANALYSIS AND REGRESSION TESTINGijfcstjournal
Software testing is a testing which conducted a test to provide information to client about the quality of the
product under test. Software testing can also provide an objective, independent view of the software to
allow the business to appreciate and understand the risks of software implementation. In this paper we
focused on two main software testing –mutation testing and mutation testing. Mutation testing is a
procedural testing method, i.e. we use the structure of the code to guide the test program, A mutation is a
little change in a program. Such changes are applied to model low level defects that obtain in the process
of coding systems. Ideally mutations should model low-level defect creation. Mutation testing is a process
of testing in which code is modified then mutated code is tested against test suites. The mutations used in
source code are planned to include in common programming errors. A good unit test typically detects the
program mutations and fails automatically. Mutation testing is used on many different platforms, including
Java, C++, C# and Ruby. Regression testing is a type of software testing that seeks to uncover
new software bugs, or regressions, in existing functional and non-functional areas of a system after
changes such as enhancements, patches or configuration changes, have been made to them. When defects
are found during testing, the defect got fixed and that part of the software started working as needed. But
there may be a case that the defects that fixed have introduced or uncovered a different defect in the
software. The way to detect these unexpected bugs and to fix them used regression testing. The main focus
of regression testing is to verify that changes in the software or program have not made any adverse side
effects and that the software still meets its need. Regression tests are done when there are any changes
made on software, because of modified functions.
GREEN WSN- OPTIMIZATION OF ENERGY USE THROUGH REDUCTION IN COMMUNICATION WORK...ijfcstjournal
Advances in micro fabrication and communication techniques have led to unimaginable proliferation of
WSN applications. Research is focussed on reduction of setup operational energy costs. Bulk of operational
energy costs are linked to communication activities of WSN. Any progress towards energy efficiency has a
potential of huge savings globally. Therefore, every energy efficient step is an endeavour to cut costs and
‘Go Green’. In this paper, we have proposed a framework to reduce communication workload through: Innetwork compression and multiple query synthesis at the base-station and modification of query syntax
through introduction of Static Variables. These approaches are general approaches which can be used in
any WSN irrespective of application.
A NEW MODEL FOR SOFTWARE COSTESTIMATION USING HARMONY SEARCHijfcstjournal
Accurate and realistic estimation is always considered to be a great challenge in software industry.
Software Cost Estimation (SCE) is the standard application used to manage software projects. Determining
the amount of estimation in the initial stages of the project depends on planning other activities of the
project. In fact, the estimation is confronted with a number of uncertainties and barriers’, yet assessing the
previous projects is essential to solve this problem. Several models have been developed for the analysis of
software projects. But the classical reference method is the COCOMO model, there are other methods
which are also applied such as Function Point (FP), Line of Code(LOC); meanwhile, the expert`s opinions
matter in this regard. In recent years, the growth and the combination of meta-heuristic algorithms with
high accuracy have brought about a great achievement in software engineering. Meta-heuristic algorithms
which can analyze data from multiple dimensions and identify the optimum solution between them are
analytical tools for the analysis of data. In this paper, we have used the Harmony Search (HS)algorithm for
SCE. The proposed model which is a collection of 60 standard projects from Dataset NASA60 has been
assessed.The experimental results show that HS algorithm is a good way for determining the weight
similarity measures factors of software effort, and reducing the error of MRE.
AGENT ENABLED MINING OF DISTRIBUTED PROTEIN DATA BANKSijfcstjournal
Mining biological data is an emergent area at the intersection between bioinformatics and data mining
(DM). The intelligent agent based model is a popular approach in constructing Distributed Data Mining
(DDM) systems to address scalable mining over large scale distributed data. The nature of associations
between different amino acids in proteins has also been a subject of great anxiety. There is a strong need to
develop new models and exploit and analyze the available distributed biological data sources. In this study,
we have designed and implemented a multi-agent system (MAS) called Agent enriched Quantitative
Association Rules Mining for Amino Acids in distributed Protein Data Banks (AeQARM-AAPDB). Such
globally strong association rules enhance understanding of protein composition and are desirable for
synthesis of artificial proteins. A real protein data bank is used to validate the system.
International Journal on Foundations of Computer Science & Technology (IJFCST)ijfcstjournal
International Journal on Foundations of Computer Science & Technology (IJFCST) is a Bi-monthly peer-reviewed and refereed open access journal that publishes articles which contribute new results in all areas of the Foundations of Computer Science & Technology. Over the last decade, there has been an explosion in the field of computer science to solve various problems from mathematics to engineering. This journal aims to provide a platform for exchanging ideas in new emerging trends that needs more focus and exposure and will attempt to publish proposals that strengthen our goals. Topics of interest include, but are not limited to the following:
Because the technology is used largely in the last decades; cybercrimes have become a significant
international issue as a result of the huge damage that it causes to the business and even to the ordinary
users of technology. The main aims of this paper is to shed light on digital crimes and gives overview about
what a person who is related to computer science has to know about this new type of crimes. The paper has
three sections: Introduction to Digital Crime which gives fundamental information about digital crimes,
Digital Crime Investigation which presents different investigation models and the third section is about
Cybercrime Law.
DISTRIBUTION OF MAXIMAL CLIQUE SIZE UNDER THE WATTS-STROGATZ MODEL OF EVOLUTI...ijfcstjournal
In this paper, we analyze the evolution of a small-world network and its subsequent transformation to a
random network using the idea of link rewiring under the well-known Watts-Strogatz model for complex
networks. Every link u-v in the regular network is considered for rewiring with a certain probability and if
chosen for rewiring, the link u-v is removed from the network and the node u is connected to a randomly
chosen node w (other than nodes u and v). Our objective in this paper is to analyze the distribution of the
maximal clique size per node by varying the probability of link rewiring and the degree per node (number
of links incident on a node) in the initial regular network. For a given probability of rewiring and initial
number of links per node, we observe the distribution of the maximal clique per node to follow a Poisson
distribution. We also observe the maximal clique size per node in the small-world network to be very close
to that of the average value and close to that of the maximal clique size in a regular network. There is no
appreciable decrease in the maximal clique size per node when the network transforms from a regular
network to a small-world network. On the other hand, when the network transforms from a small-world
network to a random network, the average maximal clique size value decreases significantly
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
TOP 10 B TECH COLLEGES IN JAIPUR 2024.pptxnikitacareer3
Looking for the best engineering colleges in Jaipur for 2024?
Check out our list of the top 10 B.Tech colleges to help you make the right choice for your future career!
1) MNIT
2) MANIPAL UNIV
3) LNMIIT
4) NIMS UNIV
5) JECRC
6) VIVEKANANDA GLOBAL UNIV
7) BIT JAIPUR
8) APEX UNIV
9) AMITY UNIV.
10) JNU
TO KNOW MORE ABOUT COLLEGES, FEES AND PLACEMENT, WATCH THE FULL VIDEO GIVEN BELOW ON "TOP 10 B TECH COLLEGES IN JAIPUR"
https://www.youtube.com/watch?v=vSNje0MBh7g
VISIT CAREER MANTRA PORTAL TO KNOW MORE ABOUT COLLEGES/UNIVERSITITES in Jaipur:
https://careermantra.net/colleges/3378/Jaipur/b-tech
Get all the information you need to plan your next steps in your medical career with Career Mantra!
https://careermantra.net/
Online aptitude test management system project report.pdfKamal Acharya
The purpose of on-line aptitude test system is to take online test in an efficient manner and no time wasting for checking the paper. The main objective of on-line aptitude test system is to efficiently evaluate the candidate thoroughly through a fully automated system that not only saves lot of time but also gives fast results. For students they give papers according to their convenience and time and there is no need of using extra thing like paper, pen etc. This can be used in educational institutions as well as in corporate world. Can be used anywhere any time as it is a web based application (user Location doesn’t matter). No restriction that examiner has to be present when the candidate takes the test.
Every time when lecturers/professors need to conduct examinations they have to sit down think about the questions and then create a whole new set of questions for each and every exam. In some cases the professor may want to give an open book online exam that is the student can take the exam any time anywhere, but the student might have to answer the questions in a limited time period. The professor may want to change the sequence of questions for every student. The problem that a student has is whenever a date for the exam is declared the student has to take it and there is no way he can take it at some other time. This project will create an interface for the examiner to create and store questions in a repository. It will also create an interface for the student to take examinations at his convenience and the questions and/or exams may be timed. Thereby creating an application which can be used by examiners and examinee’s simultaneously.
Examination System is very useful for Teachers/Professors. As in the teaching profession, you are responsible for writing question papers. In the conventional method, you write the question paper on paper, keep question papers separate from answers and all this information you have to keep in a locker to avoid unauthorized access. Using the Examination System you can create a question paper and everything will be written to a single exam file in encrypted format. You can set the General and Administrator password to avoid unauthorized access to your question paper. Every time you start the examination, the program shuffles all the questions and selects them randomly from the database, which reduces the chances of memorizing the questions.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Planning Of Procurement o different goods and services
TEST CASE PRIORITIZATION FOR OPTIMIZING A REGRESSION TEST
1. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
DOI:10.5121/ijfcst.2016.6202 23
TEST CASE PRIORITIZATION FOR OPTIMIZING A
REGRESSION TEST
Ahlam Ansari1
, Alisha Khan2
, Anam Khan3
and Konain Mukadam4
Department of Computer Engineering, M.H. SabooSiddik,Mumbai, India
ABSTRACT
Regression testing makes sure that upgradation of software in terms of adding new features or for bug
fixing purposes should not hamper previously working functionalities. Whenever a software is upgraded or
modified, a set of test cases are run on each of its functions to assure that the change to that function is not
affecting other parts of the software that were previously running flawlessly. For achieving this, all existing
test cases need to run as well as new test cases might be required to be created. It is not feasible to re-
execute every test case for all the functions of a given software, because if there is a large number of test
cases to be run, then a lot of time and effort would be required. This problem can be addressed by
prioritizing test cases. Test case prioritization technique reorders the priority in which test cases are
implemented, in an attempt to ensure that maximum faults are uncovered early on by the high priority test
cases implemented first. In this paper we propose an optimized test case prioritization technique using Ant
Colony Optimization (ACO) to reduce the cost, effort and time taken to perform regression testing and also
uncover maximum faults. Comparison of different techniques such as Retest All, Test Case Minimization,
Test Case Prioritization, Random Test Case Selection and Test Case Prioritization using ACO is also
depicted.
KEYWORDS
Regression testing, Test case prioritization, Ant colony optimization.
1. INTRODUCTION
No matter how well a software is designed and tested before being released, it will eventually
have to be modified for either adding new features or to fix the bugs in the current version.
Regression testing is type of testing, which is performed on the improved build of the software so
as to verify that the bug fixes or the added functionalities do not hamper the originally flawless
functionalities of the software [1].
Regression testing is the process of verifying the modified software to detect whether new errors
have been introduced into previously flawless code and to provide confidence that modifications
are correct [2]. But, running all the regression test cases again for every iteration of the software
is an expensive and time consuming process. To solve the problem of this “Retest All” approach,
we have various techniques such as Test case selection, Test Case Prioritization and the Hybrid
approach.
The various regression testing techniques are depicted in Figure 1 [3].
2. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
24
Figure 1. Regression Testing Techniques
a) Retest All: This is simply re-execution of all the test cases in the test suite of a particular
function. It is the ideal technique, but however, can consume a lot of time.
b) Regression Test Case Selection: Instead of re-executing the entire test suite, it is logical to
select a certain part of test suite to be run. Test cases selected can be categorized as I) Reusable
Test Cases II) Obsolete Test Cases.
Reusable Test cases can be used in succeeding regression cycles.
Obsolete Test Cases can't be used in succeeding cycles.
c) Prioritization of Test Cases: In this technique we prioritize the list of test cases, enabling test
cases with higher priority, selected on the basis of some predefined criterion, to be executed
before the test cases with a lower priority, to meet the required performance goal. So test case
prioritization technique does not discard any test case hence avoiding the drawback of test case
minimization technique.
d) Hybrid Approach: This technique is a Hybrid Approach of both Regression Test Selection and
Test Case Prioritization. So as to achieve the advantages of both.
Various prioritization criteria may be applied to the regression test suite with the objective of
meeting the required criteria. Test cases can be prioritized in terms of random, optimal, total
statement coverage, failure rates, total branch coverage or total fault exposing potential of the test
cases [4]. Many techniques have been implemented for prioritizing the test cases according to one
or more chosen criteria to meet the requirement. In this paper we make use of ACO to prioritize
the given test cases. ACO is a process based on real life of ants, precisely on their food searching
process.
1.1 Concept of Regression Testing
Regression testing is performed whenever any modifications made to the software, to provide
confidence that the software behaves correctly and the modifications have not impacted the
previously flawless functions and the quality of the software. A regression test is intended to
provide a general assurance that enhancement or defect fixes in the software or its environment
do not impact the previously working functionalities of the software.
3. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
25
Figure 2. Various Activities that are Carried Out During Regression Testing
Regression test suites are often simply the test cases that had been previously developed, and that
have been saved so that they can be used later to perform regression testing [4]. It is an important
and necessary activity as it maintains the quality of modified software systems. Many regression
testing techniques have been proposed that are Test Selection, Test Minimization and Test
Prioritization. The various regression testing techniques can be seen in Figure 2.
1.2 Activities Performed During Regression Testing
a) Test case selection: Test selection chooses the test cases that are relevant for a specific part of
the application or for the performed maintenance operation.
b) Test case minimization: Test minimization reduces the number of test cases to be executed by
removing redundant test cases, thus preserving the capability of the suite in discovering faults.
c) Test case prioritization: Test case prioritization determines the execution order of test cases
that maximizes the probability of early discovering faults [5].
Minimization of test cases may require discarding of few test cases whereas prioritization of test
cases gives an execution order of test cases such that all higher priority test cases are executed
based on the selection criteria thereby reducing the probability of degradation in software
components quality.
2. TEST CASE PRIORITIZATION
Test case prioritization involves the arrangement of test cases based on some specific criteria. The
technique emphasizes on prioritizing the test cases and enhancing the probability of meeting the
specified goals within assigned time and cost which was not effectively achievable by non
prioritized test cases.
Test case prioritization is used to achieve various objectives as follows:
a) Software developers/testers intend to increase the rate of fault detection.
b) Early detection of the faults that are more risky in testing life cycle.
c) To increase the reliability of the system [6].
4. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
26
2.1 Test Case Prioritization Techniques
In test case prioritization technique test cases that cover maximum faults in a particular function
of the software are selected. Test cases with minimum execution time and maximum usage are
assigned high priorities .The objective of this technique is to test the functionalities of a
component in minimum time so as to reduce efforts and cost of testing.
The nine different test case prioritization techniques are as follows [7]:
a) No prioritization: One prioritization technique that we consider is simply the application
of no technique; that is the test cases are untreated.
b) Random prioritization: Here we apply random prioritization, in which we randomly order
the tests in a test suite.
c) Optimal prioritization: We can determine, for any test suite, which test cases expose
which faults of a system, and thus we can determine an optimal ordering of test cases for
maximizing rate of fault detection.
d) Total branch coverage prioritization: We can determine, for any test case, the number of
decisions (branches) in that program that were exercised by that test case. We can
prioritize these test cases according to the total number of branches they cover simply by
sorting them in order of total branch coverage achieved.
e) Additional branch coverage prioritization: Additional branch coverage prioritization
prioritizes test case in order of coverage of branches not yet covered.
f) Total fault-exposing-potential (FEP) prioritization: prioritize in order of total probability
of exposing faults.
g) Additional fault-exposing-potential (FEP) prioritization: Prioritize test case in order of
total probability of exposing faults, adjusted to consider effects of previous tests.
h) Total statement coverage prioritization: Prioritize in order of coverage of statements.
i) Additional statement coverage prioritization: Prioritize in order of coverage of statements
not yet covered.
2.2 Algorithms for Test Case Prioritization
Several researchers have been working on developing algorithms for prioritization of test cases.
Some of which are listed below:
a) Greedy Algorithm
b) Additional Greedy Algorithm
c) Optimal Algorithm
d) Hill Climbing Algorithm
e) Genetic Algorithm
f) PORT version1.1
g) Ant Colony optimization [3].
3. PROPOSED SYSTEM
Ant colony optimization technique is used for prioritizing the test cases.
3.1 Ant colony optimization
Ants are blind and small in size and still are able to find the shortest route to their food source.
They make the use of antennas and pheromone liquid to be in touch with each other. Ant Colony
Optimization (ACO) inspired from the behaviour of live ants on a food hunt is an optimal path
5. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
searching technique, capable of synchronization with searching solutions for local problem by
maintaining array list to maintaining previous information gathered by each ant [8].
While on food hunt ants follow a certain path. A chemical substance called “pheromone” is left
behind by each ant following the path. The ants that follow similar path are able to trace the path
by smelling the odour of pheromone that the preceding ants left behind [9].
The optimal or shortest path discovery is done by observing teamwork and pheromone evaluation
process. The possible random paths from ant hill to the food particle are shown in Figure 3
[9].Ants take random paths and the pheromone is deposited on every path taken by t
However on their return ants will take the path which has more residual pheromone.
Figure 3. Random path followed by ants
Pheromone evaporation rate depends upon the path length. The longer the path the more will be
pheromone evaporation. Hence the longer path has less residual pheromone
Figure 4. Shorter path followed by ants
As seen in Figure 4 [8], remaining succeeding ants will take a shorter path which has more
residual pheromone left behind.
3.2 Working of Proposed System
During software testing, testers often encounter time and budget constraints which make it
difficult to rerun all test cases. To
the specified goals within stipulated time and cost.
list of test cases to make regression testing efficient .To achieve this
the form of matrices and sorted by taking several factors into consideration.
the test will be optimized by reducing the time required to perform the test, reducing the cost
required to conduct the test, increasing the productivity of the tester and the software and
uncovering maximum number of faults.
The basic processing of Test Case Prioriti
International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
searching technique, capable of synchronization with searching solutions for local problem by
maintaining array list to maintaining previous information gathered by each ant [8].
w a certain path. A chemical substance called “pheromone” is left
behind by each ant following the path. The ants that follow similar path are able to trace the path
by smelling the odour of pheromone that the preceding ants left behind [9].
or shortest path discovery is done by observing teamwork and pheromone evaluation
process. The possible random paths from ant hill to the food particle are shown in Figure 3
[9].Ants take random paths and the pheromone is deposited on every path taken by the ants
However on their return ants will take the path which has more residual pheromone.
Figure 3. Random path followed by ants
Pheromone evaporation rate depends upon the path length. The longer the path the more will be
Hence the longer path has less residual pheromone.
Figure 4. Shorter path followed by ants
As seen in Figure 4 [8], remaining succeeding ants will take a shorter path which has more
Proposed System
During software testing, testers often encounter time and budget constraints which make it
cases. To avoid this situation, we prioritize the given test cases to meet
the specified goals within stipulated time and cost. The main focus of this paper is to optimize the
list of test cases to make regression testing efficient .To achieve this objective,inputs are taken in
the form of matrices and sorted by taking several factors into consideration. Thus the efficiency of
be optimized by reducing the time required to perform the test, reducing the cost
required to conduct the test, increasing the productivity of the tester and the software and
mber of faults.
The basic processing of Test Case Prioritization can be seen in figure 5.
International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
27
searching technique, capable of synchronization with searching solutions for local problem by
w a certain path. A chemical substance called “pheromone” is left
behind by each ant following the path. The ants that follow similar path are able to trace the path
or shortest path discovery is done by observing teamwork and pheromone evaluation
process. The possible random paths from ant hill to the food particle are shown in Figure 3
he ants.
Pheromone evaporation rate depends upon the path length. The longer the path the more will be
As seen in Figure 4 [8], remaining succeeding ants will take a shorter path which has more
During software testing, testers often encounter time and budget constraints which make it
avoid this situation, we prioritize the given test cases to meet
focus of this paper is to optimize the
inputs are taken in
Thus the efficiency of
be optimized by reducing the time required to perform the test, reducing the cost
required to conduct the test, increasing the productivity of the tester and the software and
6. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
28
Figure 5. Basic processing of Test case prioritization using ACO
Figure 5 shows the input requirements and the output produced using the proposed technique.
The input to the system consists of the following matrices
a) Fault test case matrix: The no. of faults uncovered by a test case for each requirement of a
project.
b) Execution time test case matrix: The time taken by each test case to complete its execution.
c) Usage matrix: The no. of times a test case has been used to uncover faults from each
requirement.
d) Pheromone matrix: The pheromone values associated with each test case.
The proposed technique uses the above matrices as inputs, applies the algorithm based on fault
coverage and produces a pool of prioritized test cases. Prioritization is done so that all faults are
detected and cost of execution is minimum.
Output from the system will consist of the following:
a) Updated pheromone matrix.
b) Best path of test case with execution time.
c) Prioritized test cases.
3.3 Proposed Algorithm
The basic steps of the proposed technique applied to test case prioritization are shown in the form
of flow chart in Figure.6.A pool of test cases along with their fault covered in each requirement,
execution time, probability of usage and pheromone value is taken as input.
Initially a test case is chosen that covers maximum faults. Since the aim is to uncover all faults,
thus it is checked if all faults are covered by it or not. If all faults are not covered, then choose the
next test case thatcovers the remaining faults and repeat this until all faults have been covered.
Once all faults are covered, calculate the total number of faults covered by each test case which is
stored in total fault test case matrix. This procedure will lead to many combinations of test case
called paths that cover all faults
7. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
29
Figure 6: Flowchart for proposed system
Many such paths are explored while iterating and the best path from all paths explored is selected.
The pheromone value is updated on the best path selected. The selection of best path is based on
minimum execution time, maximum probability of usage and highest pheromone value.
8. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
30
4. RESULT
The results are divided into two sections viz, output section and comparative analysis. In the
output section inputs and outputs screenshots are displayed which are obtained after application
ofthe proposed technique.A comparative analysis is done in second section of results in which
various techniques are compared based on different factors such as their execution time, risk, fault
detection, representative set, cost etc.
4.1 Output
The output of the system will be generated by taking all the input matrices and prioritizing them
based on several criterion. Five test cases along with their faults uncovered, execution time, usage
and its corresponding pheromone value is taken as input. The contents of various input files are
shown below.
Table 1 shows the Fault test case matrix. The faults that a certain test case uncovers are marked as
‘ ’.
Table 1. Fault Test Case matrix
From Table 1 it can be easily concluded that maximum faults are covered by TC 03 and TC 01
covers the faults that are left to be covered.
A test case’s script length determines its execution time. For each Test case, its execution time is
stored in the Execution time test case matrix.
Table 2 displays the Execution time test case matrix.
Table 2. Execution Time test case matrix
Test Case Execution Time
TC 01 7
TC 02 5
TC 03 4
TC 04 4
TC 05 5
The number of times a specific test case is used is displayed in the usage matrix shown in Table 3
below.
Test Case Fault 1 Fault 2 Fault 3 Fault 4 Fault 5 Fault 6
TC 01
TC 02
TC 03
TC 04
TC 05
9. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
31
Table 3. Usage matrix
Test Case Usage
TC 01 3
TC 02 2
TC 03 4
TC 04 2
TC 05 3
Table 3 concludes that maximum times used test cases are TC 03, TC 05 and TC 01.
Test cases and their respective pheromone values are displayed in the Pheromone matrix given
below.
Table 4 represents the Pheromone matrix.
Table 4. Pheromone matrix
Test Case Pheromone Value
TC 01 0.42
TC 02 0.4
TC 03 1
TC 04 0.5
TC 05 0.6
Various combinations of test cases called paths are generated and the best path is selected based
on which the updation of pheromone values is done. The best path or optimal path is selected by
considering several factors such as pheromone value of a test case, probability of its usage and its
average execution time.
The output screens are shown below:
1) Registration of Test Case Prioritization Application
Any user must first register in order to use the system. The registration fields are simply the
personal details of the user.
10. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
32
Figure 7. Registration Screen
2) Login of Test Case Prioritization Application
A registered user can login to the system and upload various files related to system that needs to
be tested.
Figure 8. Login Screen
3) Input Data of Test Case Prioritization Application
Input data is taken in the form of various files i.e. Fault test case matrix, Execution time test case
matrix, Usage matrix and Pheromone matrix.
11. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
33
Figure 9. Data acceptance screen
Figure 10. Uploading files screen
4) Output of Test Case Prioritization Application
The output is divided into two parts. The first part shows a table that contains the list of
prioritized test cases. The second part of output shows comparative analysis between non
prioritized test cases and prioritized test cases on account of factors like Time taken for testing,
Size of test cases, Cost of testing, Effort required and the APFD values associated with each test
case.
12. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
34
Figure 11. Prioritized test case screen
4.2 Comparative Analysis
Table 5 shows comparative analysis between different regression testing techniques based on
factors like Representive set, Execution time, Risk, Cost and Fault Detection.
Table 5. Fault Test Case matrix
Representative
Set
Execution
Time
Risk Cost
Fault
Detection
Retest All Approach Strong RS Slow
No
(Yet risk
areas are
taken care
of)
High High
Test Case
Minimization
Strong RS
(If based on
specifications)
Fast No Low
High
(If based on
specifications)
Test Case
Prioritization
Weak RS Fast
Yes
(If based
on risk
exposure)
Low Lowest
13. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
35
Random Test Case
Selection
Weak RS Fast No Low Medium/Low
Test Case
Prioritization using
ACO
Strong RS Fast Yes Low High
Table 6 shows the analysis of existing system based on time, cost, size, effort and APFD of
untreated test case.
Table 6. Analysis of existing application
Sr.No. Principles Poor Average Good Very
Good
Excellent
i) Time *
ii) Cost *
iii) Size *
iv) Effort *
v) APFD *
Table 7 shows the analysis of proposed system based on time, cost, size, effort and APFD of
prioritized test case
Table 7.Analysis of proposed system
Sr.No. Principles Poor Average Good Very
Good
Excellent
i) Time *
ii) Cost *
iii) Size *
iv) Effort *
v) APFD *
5. CONCLUSION
The proposed technique will optimize test cases for specific components of a software by
automatically generating prioritized list of test cases to increase the efficiency of regression
testing. Ant colony optimization (ACO) technique is used for prioritization and optimization of
test cases. The objective of uncovering maximum faults in the functions of a software will be
achieved by prioritization of test cases thereby minimizing effort, time and cost of
testing.Application of this algorithm will lead to results that are optimal and reduce testers’ effort
and time complexity.
6. FUTURE SCOPE
Currently our system only deals with creating an optimized list of test cases from an already
available pool of test cases.
14. International Journal in Foundations of Computer Science & Technology (IJFCST) Vol.6, No.2, March 2016
36
a) Furthermore, the system can be extended to automatically perform the regression test
after creating a list of prioritized test cases. So as to partially or to some extent completely
eliminate the need of human intervention in the testing process.
b) The accuracy of the system can be increased, if we could somehow estimate that what test
cases would prove to be more important in the future, then their priorities could be
pushed up. This can also be called as an ideal or the most optimal scenario for testing. But
practically, as of now, it is impossible to achieve it, as it is not possible to estimate, in
advance, that which test case might prove to be most important in the future.
c) Also the system can be extended to smartly create or add its own test cases to the pool of
test cases, if required.
ACKNOWLEDGEMENT
Our thanks to M.H. Saboo Siddik College of Engineering, Department of Computer Engineering,
for giving us the initiative to do constructive work. We also thank anonymous reviewers for their
constructive suggestions.