Measuring testability early in the development life cycle especially at design phase is a criterion of crucial importance to software designers, developers, quality controllers and practitioners. However, most of the
mechanism available for testability measurement may be used in the later phases of development life cycle.
Early estimation of testability, absolutely at design phase helps designers to improve their designs before
the coding starts. Practitioners regularly advocate that testability should be planned early in design phase.
Testability measurement early in design phase is greatly emphasized in this study; hence, considered significant for the delivery of quality software. As a result, it extensively reduces rework during and after implementation, as well as facilitate for design effective test plans, better project and resource planning in a practical manner, with a focus on the design phase. An effort has been put forth in this paper to recognize the key factors contributing in testability measurement at design phase. Additionally, testability
measurement model is developed to quantify software testability at design phase. Furthermore, the relationship of Testability with these factors has been tested and justified with the help of statistical measures. The developed model has been validated using experimental tryout. Finally, it incorporates the empirical validation of the testability measurement model as the author’s most important contribution.
Flexibility a key factor to testability ijseajournal
Testability is an important software quality factor that is ineffective if it is not available at an early stage in
the development life-cycle. It becomes more essential in the case of object oriented design. Flexibility is an
important key factor to testability analysis and measurement for delivering high class testable and
maintainable software. Flexibility is a criterion of crucial significance to software developers, designers
and the quality controllers. It constantly guides and supports to avoid wastage of resources as well as
enable the designers for continuous improvement in the development process. Flexibility is concerned with
building high quality and reliable software within the constraints of cost and time. It greatly influences
cost, quality and reliability at software evolution process. Despite the fact flexibility is vital and highly
significant aspect for software development processes, it is poorly managed. This paper focuses the need
and importance of flexibility early at design phase. A model has been proposed for flexibility measurement
of object oriented design by establishing multiple linear regression. Finally the proposed model has been
validated using experimental tryout.
Evaluating effectiveness factor of object oriented design a testability pers...ijseajournal
Effectiveness is important quality factor to testability measurement of object oriented software at an initial
stage of software development process exclusively at design phase for high quality product. It will help
developer’s design capability to achieve the specified functionalities, characteristics, better design quality
and behavior using appropriate object oriented design (OOD) concepts and procedures. Metric based
model for ‘Effectiveness Quantification Model of Object Oriented Design’ has been proposed by
establishing the correlation between effectiveness and OOD constructs. Later ‘Effectiveness Quantification
Model’ is empirically validated and statistical significance of the study considers the high correlation for
model acceptance. The aim of this research work is to encourage researchers and developers for inclusion
of the effectiveness quantification model to access and quantify software effectiveness quality factor at
design time.
STATISTICAL ANALYSIS OF METRICS FOR SOFTWARE QUALITY IMPROVEMENT ijseajournal
Software product quality can be defined as the features and characteristics of the product that meet the user needs. The quality of any software can be achieved by following a well defined software process. These software process results into various metrics like Project metrics, Product metrics and Process metrics. Software quality depends on the process which is carried out to design and develop software. Even though the process can be carried out with utmost care, still it can introduce some error and defects. Process metrics are very useful from management point of view. Process metrics can be used for improving the software development and maintenance process for defect removal and also for reducing the response
time.
This paper describes the importance of capturing the Process metrics during the quality audit process and also attempts to categorize them based on the nature of error captured. To reduce such errors and defects found, steps for corrective actions are recommended.
In the software measurement validations, assessing the validation of software metrics in software
engineering is a very difficult task due to lack of theoretical methodology and empirical methodology [41,
44, 45]. During recent years, there have been a number of researchers addressing the issue of validating
software metrics. At present, software metrics are validated theoretically using properties of measures.
Further, software measurement plays an important role in understanding and controlling software
development practices and products. The major requirement in software measurement is that the measures
must represent accurately those attributes they purport to quantify and validation is critical to the success
of software measurement. Normally, validation is a collection of analysis and testing activities across the
full life cycle and complements the efforts of other quality engineering functions and validation is a critical
task in any engineering project. Further, validation objective is to discover defects in a system and assess
whether or not the system is useful and usable in operational situation. In the case of software engineering,
validation is one of the software engineering disciplines that help build quality into software. The major
objective of software validation process is to determine that the software performs its intended functions
correctly and provides information about its quality and reliability. This paper discusses the validation
methodology, techniques and different properties of measures that are used for software metrics validation.
In most cases, theoretical and empirical validations are conducted for software metrics validations in
software engineering [1-50].
7.significance of software layered technology on size of projects (2)EditorJST
The objective of the software engineering is committed to build software projects within the budget, time and required quality. Software engineering is a layered paradigm comprised of process, methods, tools and quality focus as bedrock to develop the product. Software firms build software projects of varying sizes constrained on resources, time and functional requirement. Impact of software engineering layered technology may vary according to the size of the projects during their development. Quantitative evaluation of layer significance on size of the software project could be categorized as a complex task because it involves a collective decision on multiple criteria. Analytic Hierarchy Process (AHP) provides an effective quantitative approach for finding the significance of software layered technology on size of the projects. This paper presents the estimations through quantitative approach on real time data collected from several software firms. These findings help for a better project management with respect to the cost, time and resources during building a software project.
Flexibility a key factor to testability ijseajournal
Testability is an important software quality factor that is ineffective if it is not available at an early stage in
the development life-cycle. It becomes more essential in the case of object oriented design. Flexibility is an
important key factor to testability analysis and measurement for delivering high class testable and
maintainable software. Flexibility is a criterion of crucial significance to software developers, designers
and the quality controllers. It constantly guides and supports to avoid wastage of resources as well as
enable the designers for continuous improvement in the development process. Flexibility is concerned with
building high quality and reliable software within the constraints of cost and time. It greatly influences
cost, quality and reliability at software evolution process. Despite the fact flexibility is vital and highly
significant aspect for software development processes, it is poorly managed. This paper focuses the need
and importance of flexibility early at design phase. A model has been proposed for flexibility measurement
of object oriented design by establishing multiple linear regression. Finally the proposed model has been
validated using experimental tryout.
Evaluating effectiveness factor of object oriented design a testability pers...ijseajournal
Effectiveness is important quality factor to testability measurement of object oriented software at an initial
stage of software development process exclusively at design phase for high quality product. It will help
developer’s design capability to achieve the specified functionalities, characteristics, better design quality
and behavior using appropriate object oriented design (OOD) concepts and procedures. Metric based
model for ‘Effectiveness Quantification Model of Object Oriented Design’ has been proposed by
establishing the correlation between effectiveness and OOD constructs. Later ‘Effectiveness Quantification
Model’ is empirically validated and statistical significance of the study considers the high correlation for
model acceptance. The aim of this research work is to encourage researchers and developers for inclusion
of the effectiveness quantification model to access and quantify software effectiveness quality factor at
design time.
STATISTICAL ANALYSIS OF METRICS FOR SOFTWARE QUALITY IMPROVEMENT ijseajournal
Software product quality can be defined as the features and characteristics of the product that meet the user needs. The quality of any software can be achieved by following a well defined software process. These software process results into various metrics like Project metrics, Product metrics and Process metrics. Software quality depends on the process which is carried out to design and develop software. Even though the process can be carried out with utmost care, still it can introduce some error and defects. Process metrics are very useful from management point of view. Process metrics can be used for improving the software development and maintenance process for defect removal and also for reducing the response
time.
This paper describes the importance of capturing the Process metrics during the quality audit process and also attempts to categorize them based on the nature of error captured. To reduce such errors and defects found, steps for corrective actions are recommended.
In the software measurement validations, assessing the validation of software metrics in software
engineering is a very difficult task due to lack of theoretical methodology and empirical methodology [41,
44, 45]. During recent years, there have been a number of researchers addressing the issue of validating
software metrics. At present, software metrics are validated theoretically using properties of measures.
Further, software measurement plays an important role in understanding and controlling software
development practices and products. The major requirement in software measurement is that the measures
must represent accurately those attributes they purport to quantify and validation is critical to the success
of software measurement. Normally, validation is a collection of analysis and testing activities across the
full life cycle and complements the efforts of other quality engineering functions and validation is a critical
task in any engineering project. Further, validation objective is to discover defects in a system and assess
whether or not the system is useful and usable in operational situation. In the case of software engineering,
validation is one of the software engineering disciplines that help build quality into software. The major
objective of software validation process is to determine that the software performs its intended functions
correctly and provides information about its quality and reliability. This paper discusses the validation
methodology, techniques and different properties of measures that are used for software metrics validation.
In most cases, theoretical and empirical validations are conducted for software metrics validations in
software engineering [1-50].
7.significance of software layered technology on size of projects (2)EditorJST
The objective of the software engineering is committed to build software projects within the budget, time and required quality. Software engineering is a layered paradigm comprised of process, methods, tools and quality focus as bedrock to develop the product. Software firms build software projects of varying sizes constrained on resources, time and functional requirement. Impact of software engineering layered technology may vary according to the size of the projects during their development. Quantitative evaluation of layer significance on size of the software project could be categorized as a complex task because it involves a collective decision on multiple criteria. Analytic Hierarchy Process (AHP) provides an effective quantitative approach for finding the significance of software layered technology on size of the projects. This paper presents the estimations through quantitative approach on real time data collected from several software firms. These findings help for a better project management with respect to the cost, time and resources during building a software project.
An empirical evaluation of impact of refactoring on internal and external mea...ijseajournal
Refactoring is the process of improving the design of existing code by changing its internal structure
without affecting its external behaviour, with the main aims of improving the quality of software product.
Therefore, there is a belief that refactoring improves quality factors such as understandability, flexibility,
and reusability. However, there is limited empirical evidence to support such assumptions.
The objective of this study is to validate/invalidate the claims that refactoring improves software quality.
The impact of selected refactoring techniques was assessed using both external and internal measures. Ten
refactoring techniques were evaluated through experiments to assess external measures: Resource
Utilization, Time Behaviour, Changeability and Analysability which are ISO external quality factors and
five internal measures: Maintainability Index, Cyclomatic Complexity, Depth of Inheritance, Class
Coupling and Lines of Code.
The result of external measures did not show any improvements in code quality after the refactoring
treatment. However, from internal measures, maintainability index indicated an improvement in code
quality of refactored code than non-refactored code and other internal measures did not indicate any
positive effect on refactored code.
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.
The most important aim of software engineering is to improve software productivity and quality of software product and further reduce the cost of software and time using engineering and management techniques.Broadly speaking, software engineering initiative has been introduced during software crisis period to describe the collection of techniques that apply engineering and management skills to the construction and
support of software process and products. There is no universally agreed theory for software measurement and the software metrics are useful for obtaining the information on evaluation of process and product in software engineering. It helps to plan and carry out improvement in software organizations and to provide objective information about project performance, process capability and product quality. The process capability is extremely important for software industry because the quality of products is largely determined by the quality of the processes. The make use of of existing metrics and development of innovative software metrics will be important factors in future software engineering process and product development. In future, research work will be based on using software metrics in software development for the development of the time schedule, cost estimates and software quality and can be improved through software metrics. The permanent application of measurement based methodologies is used to the software process and its products to provide important and timely management information, together with the use of those techniques to improve that software process and its products. This research paper mainly concentrates on the overview of unique basics of software measurement and exclusive fundamentals of software metrics in software engineering.
Syed Zaffar Iqbal, Prof. Urwa Javed and Dr. Shakeel Ahmed Roshan. Department of Computer Science, Alhamd Islamic University, Pakistan. “Software Quality Assurance Model for Software Excellence with Its Requirements” United International Journal for Research & Technology (UIJRT) 1.1 (2019): 39-43.
STRATEGIES TO REDUCE REWORK IN SOFTWARE DEVELOPMENT ON AN ORGANISATION IN MAU...ijseajournal
Rework is a known vicious circle in software development since it plays a central role in the generation of
delays, extra costs and diverse risks introduced after software delivery. It eventually triggers a negative
impact on the quality of the software developed. In order to cater the rework issue, this paper goes in depth
with the notion of rework in software development as it occurs in practice by analysing a development
process on an organisation in Mauritius where rework is a major issue. Meticulous strategies to reduce
rework are then analysed and discussed. The paper ultimately leads to the recommendation of the best
strategy that is software configuration management to reduce the rework problem in software development
The result of applying a new testing model for improving the quality of softw...amiraiti
This paper shows the result of applying a new testing model which provides the know-how for performing the different activities covered in the test process for functional testing. It was noticed that the customer risks experienced during examining the accuracy of software used in different business sectors are not the main focus of the Quality Control team members. Moreover there are no standard testing techniques used by the team members during creating the test conditions and test cases, the result is a lot of reworks.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
The presentation covers the overview of software metrics, its need, classification and important product metrics. It also explains GQM approach of metrics programme.
EFFICIENCY OF SOFTWARE DEVELOPMENT AFTER IMPROVEMENTS IN REQUIREMENTS ENGINEE...ijseajournal
In the past decade multiple challenges arose from the method of software development [4, 4]. As described by Davenport, the development process needs an overhaul [4, 4]. Different disciplines, like project management, requirements engineering, the development of code or quality assurance have been investigated intensively, in order to improve the productivity of development. To obtain valid results, the
overhaul needs to start with the refactoring of the right process at first. Often, it is sensible to start with such processes, which operate at the interface to the customer, because they are perhaps the most critical to an organization’s success [3, 270 – 271]. Mainly, software development consists of four sub processes:
requirements engineering, development, quality assurance and delivery. Requirements engineering and
delivery operate on the interface to the customers. Because of the fact that the analysis of requirements is
groundbreaking, we select this process as the starting point of a process innovation initiative. We analyse
the impact of requirements engineering in KANBAN development processes. Special emphasis is put on the
productivity of the overall development process, after a refactoring of requirements engineering.
SCHEDULING AND INSPECTION PLANNING IN SOFTWARE DEVELOPMENT PROJECTS USING MUL...ijseajournal
This paper presents a Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution
of Scheduling and Inspection Planning in Software Development Projects. Scheduling and Inspection
planning is a vital problem in software engineering whose main objective is to schedule the persons to
various activities in the software development process such as coding, inspection, testing and rework in
such a way that the quality of the software product is maximum and at the same time the project make span
and cost of the project are minimum. The problem becomes challenging when the size of the project is
huge. The MHypEA is an effective metaheuristic search technique for suggesting scheduling and inspection
planning. It incorporates twelve low-level heuristics which are based on different methods of selection,
crossover and mutation operations of Evolutionary Algorithms. The selection mechanism to select a lowlevel
heuristic is based on reinforcement learning with adaptive weights. The efficacy of the algorithm has
been studied on randomly generated test problem.
Proposed an Integrated Model to Detect The Defect in Software Development Pro...Waqas Tariq
Currently, software quality assurance does not apply completely on the development of software industry and this leads to some challenges in the industry of software, specially, concerning cost and time consuming. While, the success of software development project depends on the application quality assurance standards, which starts by the pre-project and continue through the project till it reaches the user at the end. The aim of this model is the challenge to produce not only the software development project without defects but also the customer’s acceptance and satisfaction of the software. Thus to prevent software development project failure, this defect should be detected at an early stage.This study will deal with; the quality assurance inspection and testing, in the whole stages of software development projects. Then proposing the quality assurance inspection and testing model for the software development projects process, which known as “Integrated Model”.
An empirical evaluation of impact of refactoring on internal and external mea...ijseajournal
Refactoring is the process of improving the design of existing code by changing its internal structure
without affecting its external behaviour, with the main aims of improving the quality of software product.
Therefore, there is a belief that refactoring improves quality factors such as understandability, flexibility,
and reusability. However, there is limited empirical evidence to support such assumptions.
The objective of this study is to validate/invalidate the claims that refactoring improves software quality.
The impact of selected refactoring techniques was assessed using both external and internal measures. Ten
refactoring techniques were evaluated through experiments to assess external measures: Resource
Utilization, Time Behaviour, Changeability and Analysability which are ISO external quality factors and
five internal measures: Maintainability Index, Cyclomatic Complexity, Depth of Inheritance, Class
Coupling and Lines of Code.
The result of external measures did not show any improvements in code quality after the refactoring
treatment. However, from internal measures, maintainability index indicated an improvement in code
quality of refactored code than non-refactored code and other internal measures did not indicate any
positive effect on refactored code.
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.
The most important aim of software engineering is to improve software productivity and quality of software product and further reduce the cost of software and time using engineering and management techniques.Broadly speaking, software engineering initiative has been introduced during software crisis period to describe the collection of techniques that apply engineering and management skills to the construction and
support of software process and products. There is no universally agreed theory for software measurement and the software metrics are useful for obtaining the information on evaluation of process and product in software engineering. It helps to plan and carry out improvement in software organizations and to provide objective information about project performance, process capability and product quality. The process capability is extremely important for software industry because the quality of products is largely determined by the quality of the processes. The make use of of existing metrics and development of innovative software metrics will be important factors in future software engineering process and product development. In future, research work will be based on using software metrics in software development for the development of the time schedule, cost estimates and software quality and can be improved through software metrics. The permanent application of measurement based methodologies is used to the software process and its products to provide important and timely management information, together with the use of those techniques to improve that software process and its products. This research paper mainly concentrates on the overview of unique basics of software measurement and exclusive fundamentals of software metrics in software engineering.
Syed Zaffar Iqbal, Prof. Urwa Javed and Dr. Shakeel Ahmed Roshan. Department of Computer Science, Alhamd Islamic University, Pakistan. “Software Quality Assurance Model for Software Excellence with Its Requirements” United International Journal for Research & Technology (UIJRT) 1.1 (2019): 39-43.
STRATEGIES TO REDUCE REWORK IN SOFTWARE DEVELOPMENT ON AN ORGANISATION IN MAU...ijseajournal
Rework is a known vicious circle in software development since it plays a central role in the generation of
delays, extra costs and diverse risks introduced after software delivery. It eventually triggers a negative
impact on the quality of the software developed. In order to cater the rework issue, this paper goes in depth
with the notion of rework in software development as it occurs in practice by analysing a development
process on an organisation in Mauritius where rework is a major issue. Meticulous strategies to reduce
rework are then analysed and discussed. The paper ultimately leads to the recommendation of the best
strategy that is software configuration management to reduce the rework problem in software development
The result of applying a new testing model for improving the quality of softw...amiraiti
This paper shows the result of applying a new testing model which provides the know-how for performing the different activities covered in the test process for functional testing. It was noticed that the customer risks experienced during examining the accuracy of software used in different business sectors are not the main focus of the Quality Control team members. Moreover there are no standard testing techniques used by the team members during creating the test conditions and test cases, the result is a lot of reworks.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology
The presentation covers the overview of software metrics, its need, classification and important product metrics. It also explains GQM approach of metrics programme.
EFFICIENCY OF SOFTWARE DEVELOPMENT AFTER IMPROVEMENTS IN REQUIREMENTS ENGINEE...ijseajournal
In the past decade multiple challenges arose from the method of software development [4, 4]. As described by Davenport, the development process needs an overhaul [4, 4]. Different disciplines, like project management, requirements engineering, the development of code or quality assurance have been investigated intensively, in order to improve the productivity of development. To obtain valid results, the
overhaul needs to start with the refactoring of the right process at first. Often, it is sensible to start with such processes, which operate at the interface to the customer, because they are perhaps the most critical to an organization’s success [3, 270 – 271]. Mainly, software development consists of four sub processes:
requirements engineering, development, quality assurance and delivery. Requirements engineering and
delivery operate on the interface to the customers. Because of the fact that the analysis of requirements is
groundbreaking, we select this process as the starting point of a process innovation initiative. We analyse
the impact of requirements engineering in KANBAN development processes. Special emphasis is put on the
productivity of the overall development process, after a refactoring of requirements engineering.
SCHEDULING AND INSPECTION PLANNING IN SOFTWARE DEVELOPMENT PROJECTS USING MUL...ijseajournal
This paper presents a Multi-objective Hyper-heuristic Evolutionary Algorithm (MHypEA) for the solution
of Scheduling and Inspection Planning in Software Development Projects. Scheduling and Inspection
planning is a vital problem in software engineering whose main objective is to schedule the persons to
various activities in the software development process such as coding, inspection, testing and rework in
such a way that the quality of the software product is maximum and at the same time the project make span
and cost of the project are minimum. The problem becomes challenging when the size of the project is
huge. The MHypEA is an effective metaheuristic search technique for suggesting scheduling and inspection
planning. It incorporates twelve low-level heuristics which are based on different methods of selection,
crossover and mutation operations of Evolutionary Algorithms. The selection mechanism to select a lowlevel
heuristic is based on reinforcement learning with adaptive weights. The efficacy of the algorithm has
been studied on randomly generated test problem.
Proposed an Integrated Model to Detect The Defect in Software Development Pro...Waqas Tariq
Currently, software quality assurance does not apply completely on the development of software industry and this leads to some challenges in the industry of software, specially, concerning cost and time consuming. While, the success of software development project depends on the application quality assurance standards, which starts by the pre-project and continue through the project till it reaches the user at the end. The aim of this model is the challenge to produce not only the software development project without defects but also the customer’s acceptance and satisfaction of the software. Thus to prevent software development project failure, this defect should be detected at an early stage.This study will deal with; the quality assurance inspection and testing, in the whole stages of software development projects. Then proposing the quality assurance inspection and testing model for the software development projects process, which known as “Integrated Model”.
A comprehensive comparison of the original forms of biogeography based optimi...ijscai
Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and one of meta-heuristic algorithms. This technique is based on an old mathematical study that explains the geographical distribution of biological organisms. The first original form of BBO was introduced in 2008 and known as a partial migration based BBO. After three months, BBO was re-introduced again with additional three other forms and known as single, simplified partial, and simplified single migration based BBOs. Then a lot of modifications and hybridizations were employed to boost-up the performance of BBO and solve its weak exploration. However, the literature lacks the explanations and the reasons on which the modifications of the BBO forms are based on. This paper tries to clarify this issue by making a comparison between the four original BBO algorithms through 23 benchmark functions with different dimensions and complexities. The final judgment is confirmed by evaluating the performance based on the effect of the problem’s dimensions, the side constraints and the population size. The results show that both single and simplified single migration based BBOs are faster, but have less performance as compared to the others. The comparison between the partial and the simplified partial migration based BBOs shows that the preference depends on the population size, problem’s complexity and dimensions, and the values of the upper and lower side constraints. The partial migration model wins when these factors, except the population size, are increased, and vice versa for the simplified partial migration model. The results can be used as a foundation and a first step of modification for enhancing any proposed modification on BBO including the existing modifications that are described in literature.
P REPROCESSING FOR PPM: COMPRESSING UTF - 8 ENCODED NATURAL LANG UAGE TEXTijcsit
In this paper,
several new universal preprocessing techniques
are described
to improve Prediction by
Partial Matching (PPM) compression of UTF
-
8 encoded natural language text. These methods essentially
adjust the alphabet in some manner (for exampl
e, by expanding or reducing it) prior to the compression
algorithm then being applied to the amended text.
Firstly,
a simple bigraphs (two
-
byte) substitution
technique
is described
that leads to significant improvement in compression for many languages whe
n they
are encoded by the Unicode scheme (25% for Arabic text, 14% for Armenian,
9% for Persian, 15% for
Russian, 1% for Chinese text, and over 5% for both English and Welsh text)
.
Secondly,
a new
preprocessing technique t
hat outputs separate vocabulary
an
d symbols streams
–
that are subsequently
encoded separately
–
is also investigated
. This also leads to significant improvement in compression for
many languages (24% for Arabic text, 30% for Armenian, 32% for Persian and 35% for Russian). Finally
,
novel p
reprocessing and postprocessing techniques for lossy and lossless text compression of Arabic text
are described for dotted and non
-
dotted forms of the language
Authoring system of drill & practice elearning modules for hearing impaired s...ijcsit
Hearing Impaired (HI) persons need to keep on practicing and repeating their lessons as well as their exercises. Teaching methodology of HI students differ than normal students. HI students need to be involved in practicing more and more using their modes of visual communication like sign language to cover their audio disability. Teaching methodology of HI students recommends demonstration and repeating with slow presentations of instructional material. A teacher displays his lesson directly face to
face without visual noise. More reinforcement and encouragement to HI students , fun & enjoyment should
be strongly included in the e-lessons as well as continuous interaction between teacher and HI students. As
per previous factors the decision of researchers is to develop Drill & Practice (D&P) e-learning modules(eLMs) for selected topics like Mathematics. D&P eLMs of Mathematics for HI persons would be the case study of this research including Developing & Evaluating.
The authors selected D&P eLMs Because eLMs match the requirements and mechanism of teaching methodology for HI students.
The mechanism of developing eLMs is represented by Developing an Authoring System which allows teachers of HI persons to generate any eLM of any selected topic for HI students. Also they can generate multiple eLMs in the project.
The evaluating producer & tools for the experimental eLMs were view points of Experts through openQuestionnaire to list their evaluating comments. Besides view points of experts. There are experiments which were held in real environment of HI students to test the eLMs of D&P of Mathematics to get valuable feedback from them.
SFAMSS:A S ECURE F RAMEWORK F OR ATM M ACHINES V IA S ECRET S HARINGijcsit
As ATM applications deploy for a banking system, th
e need to secure communications will become critica
l.
However, multicast protocols do not fit the point-t
o-point model of most network security protocols wh
ich
were designed with unicast communications in mind.
In recent years, we have seen the emergence and the
growing of ATMs (Automatic Teller Machines) in bank
ing systems. Many banks are extending their activit
y
and increasing transactions by using ATMs. ATM will
allow them to reach more customers in a cost
effective way and to make their transactions fast a
nd efficient. However, communicating in the network
must satisfy integrity, privacy, confidentiality, a
uthentication and non-repudiation. Many frameworks
have
been implemented to provide security in communicati
on and transactions. In this paper, we analyze ATM
communication protocol and propose a novel framewor
k for ATM systems that allows entities communicate
in a secure way without using a lot of storage. We
describe the architecture and operation of SFAMSS i
n
detail. Our framework is implemented with Java and
the software architecture, and its components are
studied in detailed.
One of the core quality assurance feature which combines fault prevention and fault detection, is often known as testability approach also. There are many assessment techniques and quantification method evolved for software testability prediction which actually identifies testability weakness or factors to further help reduce test effort. This paper examines all those measurement techniques that are being proposed for software testability assessment at various phases of object oriented software development life cycle. The aim is to find the best metrics suit for software quality improvisation through software testability support. The ultimate objective is to establish the ground work for finding ways reduce the testing effort by improvising software testability and its assessment using well planned guidelines for object-oriented software development with the help of suitable metrics.
MAKE THE QUALITY OF SOFTWARE PRODUCT IN THE VIEW OF POOR PRACTICES BY USING S...Journal For Research
In the Software Engineering, One of the most important factors to impact national and international business is quality of software and its assurance. Integral part of software development cycle is SQA, evaluation of software Quality product when compared to other industrial projects and it is very highly difficult. For developing, performance, speed, maintaining the quality, cost and efficiency of the software, SQA activities, principles and its methods are implemented in the early stages of the software engineering development phases. Where in this paper there is little visibility of lack of software Quality product in the view of poor practices. Hence we proposed a new system with best practices in software quality management to make the best quality product. This System works on Gain Better Visibility into Supplier Quality with Technology.
PRODUCT QUALITY EVALUATION METHOD (PQEM): TO UNDERSTAND THE EVOLUTION OF QUAL...ijseajournal
Promoting quality within the context of agile software development, it is extremely important as well as
useful to improve not only the knowledge and decision-making of project managers, product owners, and
quality assurance leaders but also to support the communication between teams. In this context, quality
needs to be visible in a synthetic and intuitive way in order to facilitate the decision of accepting or
rejecting each iteration within the software life cycle. This article introduces a novel solution called
Product Quality Evaluation Method (PQEM) which can be used to evaluate a set of quality characteristics
for each iteration within a software product life cycle. PQEM is based on the Goal-Question-Metric
approach, the standard ISO/IEC 25010, and the extension made of testing coverage in order to obtain the
quality coverage of each quality characteristic. The outcome of PQEM is a unique multidimensional value,
that represents the quality level reached by each iteration of a product, as an aggregated measure. Even
though a value it is not the regular idea of measuring quality, we believe that it can be useful to use this
value to easily understand the quality level of each iteration. An illustrative example of the PQEM method
was carried out with two iterations from a web and mobile application, within the healthcare environment.
A single measure makes it possible to observe the evolution of the level of quality reached in the evolution
of the product through the iterations.
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In this Study, the researcher used a collection of literatures from various electronic databases, available since 2008 to understand and know the software metrics. Finally, in this study, the researcher has been identified software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from others for this reason it is better to apply the software metrics to measure the quality of software and the current most common software metrics tools to reduce the subjectivity of faults during the assessment of software quality. The central contribution of this study is an overview about software metrics that can illustrate us the development in this area, and a critical analysis about the main metrics founded on the various literatures.
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Software metrics have a direct link with measurement in software engineering. Correct measurement is the prior condition in any engineering fields, and software engineering is not an exception, as the size and complexity of software increases, manual inspection of software becomes a harder task. Most Software Engineers worry about the quality of software, how to measure and enhance its quality. The overall objective of this study was to asses and analysis’s software metrics used to measure the software product and process.
In this Study, the researcher used a collection of literatures from various electronic databases, available since 2008 to understand and know the software metrics. Finally, in this study, the researcher has been identified software quality is a means of measuring how software is designed and how well the software conforms to that design. Some of the variables that we are looking for software quality are Correctness, Product quality, Scalability, Completeness and Absence of bugs, However the quality standard that was used from one organization is different from others for this reason it is better to apply the software metrics to measure the quality of software and the current most common software metrics tools to reduce the subjectivity of faults during the assessment of software quality. The central contribution of this study is an overview about software metrics that can illustrate us the development in this area, and a critical analysis about the main metrics founded on the various literatures.
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and therefore to gives faulty design and development results. This is mainly seeming and appears owing to
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and program simplicity are very necessary and one of the vital attributes of the system development cycle.This research paper highlights the impact and significance of design level software simplicity in common and as a one of the most useful key factor or index of software quality assurance and testing. In this research work principally there are three major efforts are made. As a first contribution, a valuable
relationship between software design quality factor simplicity and related object oriented design
properties, this has been set up. In the second contribution, using design level corresponding metrics a
simplicity evaluation model for object oriented software is developed. Subsequently, the developed
simplicity model has been rationally authenticated by means of experimental data try-out.
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testing process and setting the right lean test metrics help to improve the software quality effectively in agile
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A RELIABLE AND AN EFFICIENT WEB TESTING SYSTEMijseajournal
To improve the reliability and efficiency of Web Software, the Testing Team should be creative and
innovative, the experience and intuition of Tester also matters a lot. And most often the destructive nature
of Tester brings reliable software to the user. Actually, Testing is the responsibility of everybody who is
involved in the Project. But, one’s personal curiosity and attention is more important than the various
techniques and tools available in the market for Web Testing due to the phenomena that Software Testing is
an art. In this study, we are actually discussing certain techniques and tools which can be helpful to
minimize bugs in Web Application and achieve reliability and efficiency to a certain level. Indeed, for
bettering the quality of Web Application, Testing may not be considered as the only effective method
because no one can certify that a system is bug-free. This paper presents some essential web testing
techniques, strategies, methods and tools which need to be focused on when performing Web Testing for
several web applications in order to achieve better results.
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To improve the reliability and efficiency of Web Software, the Testing Team should be creative and innovative, the experience and intuition of Tester also matters a lot. And most often the destructive nature of Tester brings reliable software to the user. Actually, Testing is the responsibility of everybody who is
involved in the Project. But, one’s personal curiosity and attention is more important than the various techniques and tools available in the market for Web Testing due to the phenomena that Software Testing is an art. In this study, we are actually discussing certain techniques and tools which can be helpful to minimize bugs in Web Application and achieve reliability and efficiency to a certain level. Indeed, for
bettering the quality of Web Application, Testing may not be considered as the only effective method because no one can certify that a system is bug-free. This paper presents some essential web testing
techniques, strategies, methods and tools which need to be focused on when performing Web Testing for
several web applications in order to achieve better results.
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Testability measurement model for object oriented design (tmmood)
1. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
DOI:10.5121/ijcsit.2015.7115 153
TESTABILITY MEASUREMENT MODEL FOR OBJECT
ORIENTED DESIGN(TMMOOD
)
Abdullah1
, Dr. M.H. Khan2
, Dr. Reena Srivastava3
1
Research Scholar, School of Computer Application, BBD University, Lucknow, India
2
Associate Professor, Department of C.S. E., I.E.T., Lucknow, India
3
Dean, School of Computer Application, BBD University, Lucknow, India
ABSTRACT
Measuring testability early in the development life cycle especially at design phase is a criterion of crucial
importance to software designers, developers, quality controllers and practitioners. However, most of the
mechanism available for testability measurement may be used in the later phases of development life cycle.
Early estimation of testability, absolutely at design phase helps designers to improve their designs before
the coding starts. Practitioners regularly advocate that testability should be planned early in design phase.
Testability measurement early in design phase is greatly emphasized in this study; hence, considered
significant for the delivery of quality software. As a result, it extensively reduces rework during and after
implementation, as well as facilitate for design effective test plans, better project and resource planning in
a practical manner, with a focus on the design phase. An effort has been put forth in this paper to recognize
the key factors contributing in testability measurement at design phase. Additionally, testability
measurement model is developed to quantify software testability at design phase. Furthermore, the
relationship of Testability with these factors has been tested and justified with the help of statistical
measures. The developed model has been validated using experimental tryout. Finally, it incorporates the
empirical validation of the testability measurement model as the author’s most important contribution.
KEYWORDS
Testability, Object Oriented Metrics, Testability Factors, Testability Measurement, Design Phase,
Development Life Cycle.
1. INTRODUCTION
Software industries have realized that quality software is an important means to improve
performance and to gain competitive advantage. The development and supply of software is one
of the fastest growing industry segments in India and abroad. The software developed as
commercial products are generally much different from computer programs written for academic
or research purpose. A great deal of effort, time and cost are required to design and develop any
commercial software. Development of even a trivial piece of software requires many activities to
be performed and it is regarded as a project. Computer programming is just one part of the
software development process. Like any other economic endeavor, development of software
requires a systematic approach that includes comprehensive methods, better tools for smooth
execution of these methods and procedures for quality assurance, coordination and control [1].
Testability has been recognized as one of the most important issues in the field of Software
Engineering. It presents insights that are found to be very much important and helpful for the
duration of software development life cycle and quality assurance [2] [3] [19].
2. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
154
Testability study early in the development life cycle is a norm of crucial importance to software
designers, developers and the quality controllers. However, most of the studies measure testability
or precisely the attributes that have impact on testability at the source code level [4] [5].
Measuring testability at a later stage leads to the late arrival of desired information, leading to late
decisions about changes in design. This simply increases cost and rework. A decision to change
the design in order to improve testability after coding has started may be very expensive and
error-prone. Therefore, early evaluation of testability in the development process may enhance
quality and reduce testing efforts and costs. Testability estimation early in design phase is highly
emphasized in the study; hence, considered important for the delivery of quality software. The
major objective of software testability measurement is to find out which software components are
inferior in quality, as well as where errors can hide from software testing.
A frame work to measure testability of object oriented software early at the design phase has been
proposed, and it has been validated with a sound theoretical basis for high and improved level
acceptability [2]. An effort has been put forth to recognize the key factors contributing in
testability measurement at design phase of development life cycle. It has been concluded that
Modifiability and Flexibility are the two most important factors affecting software testability
measurement in design phase. Taking into consideration the importance and significance of their
contribution, a testability measurement model has been developed to measure software testability
at design phase. Furthermore, statistical test are performed to justify the correlation of testability
with Modifiability and Flexibility.
2. TESTABILITY FACTORS AND KEY CONTRIBUTORS
Software testability is now established to be an important and distinct software quality
characteristic. Testability is one of the most essential quality indicators and its measurement leads
to the prospects of facilitating and improving a test process. Testability has always been an
elusive concept and its correct measurement or evaluation a difficult exercise [6]. Moreover, there
is little consensus among researchers and practitioners about ‘what aspects of software are truly
related to testability’. So it is hard to get an understandable view on all the prospective factors
that have an effect on testability and the dominant degree of these factors under different testing
perspectives [8]. Researchers and Practitioners have made significant amount of effort and
contribution in the way of investigating testability factors in common and object oriented
software in particular [9] [10] [11] [12] [13] [14] [21]. It comes into view fairly, conclusive from
the existing literature review that there is a difference among researchers and practitioners in
considering the factors while measuring testability in general and absolutely at design phase.
A truthful measure of software quality fully depends on testability measurement, which in turn
depends on the factors that have an effect on software testability. Above mentioned explanation
confirms that there is a divergence among researchers and practitioners regarding considering the
factors while estimating the testability. Hence, it appears extremely desirable and important to
recognize the factors that facilitate testability in order to get the accurate and reliable measure of
software testability.
Despite the fact that, getting a universally accepted set of testability factors is only probable.
Testability quality criteria are the characteristics which help to identify the testability factors.
Criteria present a more complete, actual definition of factors as well as criteria common among
factors assist to show the interrelationship between factors. The criteria of the testability factor are
the characteristics of the software product or development cycle by which the factor can be
judged or recognized. An endeavor has been made to collect a set of testability factors that can
affect software testability. However, without any loss of generality, it comes into view to include
the factors namely, modifiability, simplicity, understandability, flexibility, traceability,
complexity, self descriptiveness and modularity as testability factors. Out of these eight factors,
3. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
155
some of them have their positive impact in measuring testability of object oriented software
design, while others have less or negligible impact. An effort has been made to recognize the
testability factors that truly affect testability measurement at design phase. Modifiability and
Flexibility are the key testability factors that truly affect software testability measurement and
fulfill the quality criteria, particularly Modifiability quality criteria is understandability,
traceability, self descriptiveness and Flexibility quality criteria is simplicity, complexity [21].
Therefore, without any loss of generality, it comes into view realistic to include Modifiability and
Flexibility for testability measurement at design phase.
3. MODEL DEVELOPMENT
The generic quality models [15] [16] have been considered as a basis to develop the Testability
Measurement Model for Object Oriented Design (TMMOOD
) shown in figure 1, which involves
the following steps.
I) Recognition of testability factors of object oriented software that has positive impact on
testability measurement at design phase of development life cycle.
II) Recognition of object oriented design properties.
III) A means of connecting of them.
Based upon the relationship of the testability factors and design constructs, the relative
significance of individual factors that has major impact on testability at design phase is weighted
proportionally. In order to set up a model for Testability Measurement, a multiple linear
regression method has been used to get the coefficients [17]. This method establishes a
relationship between dependent variable and multiple independent variables. Multivariate linear
equation is given below in Eq (1) which is as follows.
Y=a0 +a1 X1 +a2 X2 +a3 X3 +-------+an Xn Eq (1)
Where,
Y is dependent variable.
X1, X2, X3--------Xn are independent variables, associated to Y and are expected to
explain the variance in Y.
a1, a2, a3--------an., are the coefficient of the particular independent variables.
And a0 is the intercept.
It has been extensively reviewed and discussed in section 2 that Modifiability and Flexibility are
the major factors affecting software testability measurement at design phase. Therefore, these key
testability factors were addressed well in advance while integrating testability at design phase. By
applying the regression method, we developed Modifiability Model [6] and Flexibility Model [7]
that are given below in equation (2) and (3) respectively. The model of Modifiability and
Flexibility forms the strong basis for development of testability measurement model.
Modifiability = 1.107- .102 × Encapsulation + 1.810 × Inheritance + .850 × Coupling
Eq (2)
Flexibility= 1.051 + 2.320 × Encapsulation + 0.160 × Coupling - 2.283 × Cohesion + 11.572 ×
Inheritance Eq (3)
Metrics of the design constructs namely Encapsulation (ENM), Inheritance (INM), Coupling
(CPM) and Cohesion (COM) are used to address the major testability factors namely
Modifiability and Flexibility. These two factors are further used to measure and control testability
of object oriented software at design phase. Below is the Figure 1, which gives an overview of the
main idea.
4. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
156
Figure 1: Mapping Design Constructs with Key Factors of Testability
In order to establish a model for testability measurement, a multiple linear regression technique
discussed above in equation (1) has been used. Taking into account the impact of Encapsulation,
Inheritance, Coupling and Cohesion on testability contributors ‘Modifiability and Flexibility’,
following MR equation has been formulated that can measure testability of object oriented
design.
Testability = α0 + ß1 × Modifiability + ß2 × Flexibility Eq (4)
The data used for developing model given in equation (4) has been taken from [20], which consist
of six industrial projects with around 10 to 20 classes. The values of ‘Encapsulation Metrics
(ENM), Inheritance Metrics (INM), Coupling Metrics (CPM) and Cohesion Metrics (COM)’and
the values of ‘Modifiability and Flexibility’ have been used. Using SPSS, correlation coefficients
are computed and model of testability measurement is thus formulated as given below in equation
(5).
Testability = -98.666 + 49.210 × Modifiability - 2.983 × Flexibility Eq (5)
Table 1: Correlation coefficients
Model
Unstandardized
Coefficients
Standardized
Coefficients
t Sig.B Std. Error Beta
1 (Constant) -98.666 25.518 -3.866 .031
Modifiability 49.210 11.538 1.331 4.265 .024
Flexibility -2.983 1.768 -.527 -1.687 .190
The Model Summary table of the output is most useful when performing multiple regression.
Capital R is the multiple correlation coefficients that tell us how strongly the multiple
independent variables are related to the dependent variable. R square is very supportive as it gives
us the coefficient of determination. The Model Summary is shown in Table 2.
Table 2: Model Summary
Model R R Square Adjusted R Square Std. Error of the Estimate
1 .950a
.903 .839 5.81531
5. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
157
4. VALIDATING the MODEL -TMMOOD
The applications that are used in validating the multivariate linear regression model for
computation of Testability (Eq. 5) have been taken from [18].We labelled the applications as:
System W, System X, System Y, and System Z. All the systems are commercial software
implemented in C++ with the number of projects as shown in table 3(a).
Table 3(a): Group and Projects
Group Projects
System W 6
System X 4
System Y 7
System Z 4
Table 3(b): Descriptive Statistics for System W
Minimum Maximum Mean
Modifiability 5.86 9.89 8.2029
Flexibility 3.78 9.29 7.3063
Testability 171.27 360.09 283.2014
Table 3(c): Correlations Analysis for System W
Testability Modifiability Flexibility
Testability 1 .999 .877
Modifiability .999 1 .893
Flexibility .877 .893 1
Table 3(d): Descriptive Statistics for System X
Minimum Maximum Mean
Modifiability 2.64 5.85 3.9059
Flexibility 4.78 7.58 6.4951
Testability 17.08 166.76 74.1701
Table 3(e): Correlations Analysis for System X
Testability Modifiability Flexibility
Testability 1 .999 .772
Modifiability .999 1 .794
Flexibility .772 .794 1
6. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
158
Table 3(f): Descriptive Statistics for System Y
Minimum Maximum Mean
Modifiability 2.34 3.13 2.7666
Flexibility 3.56 10.47 7.2894
Testability 4.50 29.56 15.7328
Table 3(g): Correlations Analysis for System Y
Testability Modifiability Flexibility
Testability 1 .955 .763
Modifiability .955 1 .921
Flexibility .763 .921 1
Table 3(h): Descriptive Statistics for System Z
Minimum Maximum Mean
Modifiability 1.61 3.46 2.9344
Flexibility 1.41 8.30 5.9949
Testability -23.53 48.24 27.8534
Table 3(i): Correlations Analysis for System Z
Testability Modifiability Flexibility
Testability 1 .999 .987
Modifiability .999 1 .992
Flexibility .987 .992 1
Table 3(j): Correlations Analysis Summary
Testability × Modifiability Testability × Flexibility
System W .999 .887
System X .999 .772
System Y .955 .763
System Z .999 .987
Table 3 (j) summarizes the result of the correlation analysis for testability measurement model,
which shows that for all the system, both Modifiability and Flexibility are highly correlated with
testability. The value of correlation ‘r’ lies between ±1, positive value of ‘r’ in table 3(j):
designates positive correlation between the two variables. The values of ‘r’ close to +1 specify
high degree of correlation between the two variables in above table 3(j).
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5. EMPIRICAL VALIDATION
The empirical validation is an essential stage of planned research. Empirical validation is the
correct approach and practice to justify the model acceptance. Keeping view of this fact, realistic
validation of the testability measurement model has been performed using sample tryouts. In
order to validate developed testability measurement model the data has been taken from [18].
During experiments, testability value of the projects has been calculated using the developed
model, followed by the calculation of testability rating. These calculated ratings are then
compared with the known rating given by experts with the help of Charles Speraman’s
Coefficient of Correlation.
Table 4: Computed Ranking, Actual Ranking and their Relation
Projects
Testability Value Testability Ranking
∑d2
rs
rs
>.4815Computed
Value
Known
Value
Computed
Ranking
Known
Ranking
p1 199.919 5.879 19 19 0 1.0000
p2 280.913 7.716 20 20 0 1.0000
p3 343.761 9.188 22 22 0 1.0000
p4 360.092 9.565 23 23 0 1.0000
p5 343.249 9.174 21 21 0 1.0000
p6 48.877 2.268 15 15 0 1.0000
p7 63.969 2.615 16 16 0 1.0000
p8 166.758 5.013 17 17 0 1.0000
p9 171.274 5.022 18 18 0 1.0000
p10 17.076 1.599 7 10 9 0.9956
p11 4.498 1.176 3 3 0 1.0000
p12 -9.151 0.832 2 2 0 1.0000
p13 18.055 1.490 9 6 9 0.9956
p14 9.692 1.294 5 5 0 1.0000
p15 29.560 1.772 11 11 0 1.0000
p16 14.900 1.532 6 7 1 0.9995
p17 48.235 2.242 14 13 1 0.9995
p18 46.873 2.242 13 14 1 0.9995
p19 19.541 1.577 10 9 1 0.9995
p20 17.582 1.547 8 8 0 1.0000
p21 5.993 1.243 4 4 0 1.0000
p22 39.839 2.041 12 12 0 1.0000
p23 -23.533 0.600 1 1 0 1.0000
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This table (4), therefore, indicates a very significant correlation between the computed ranking
and actual ranking of testability model, at the 0.01 for a 99% confidence interval.
rs >0.4815 means significant results.
Testability measurement model had statistically significant correlations with 23 of 23
projects.
As mentioned above, Charles Speraman’s Coefficient of Correlation (rank relation) rs was used
to check the significance of correlation between ‘Calculated Values’ of Testability using model
and it’s ‘Known Values’. Rank correlation is the process of determining the degree of correlation
between two variables. The ‘rs’ was calculated using the method given as under: Speraman’s
Coefficient of Correlation
‘d’ = difference between ‘Calculated ranking’ and ‘Known ranking’ of testability.
n = number of projects (n=28) used in the experiment.
The correlation values between testability through model and known ranking are shown in table
(4) above. Pairs of these values with correlation values rs above [±.4815] are checked in critical
values table. The correlations are up to standard with high degree of confidence, i.e. up to 99%.
Therefore we can conclude without any loss of generality that testability measurement model;
measures are really highly reliable and significant at design phase.
6. HYPOTHESIS TESTING OF COEFFICIENT OF CORRELATION
An experimental coefficient of corelation of Modifiability and Flexibility with Testability
strongly indicates the higher importance and significance of taking into consideration both the
key factors (Modifiability and Flexibility) for making a measurement of software testability at
design phase. Furthermore, to justify the claim, a test to conclude the statistical significance of the
correlation coefficient observed possibly will be appropriate. For the motivation, Hypothesis
testing is performed to test the significance of r (Correlation Coefficient) using the given below
formula:
With N-2 degree of freedom, a coefficient of correlation is evaluated as statistically importance
when the t value equals or exceeds the t critical value in the t distribution critical values.
H0 (T^M): Testability and Modifiability are not highly correlated.
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Table 5(a): Correlation Coefficient Test for Testability and Modifiability
System W System X System Y System Z
Testability ^
Modifiability
.999 .999 .955 .999
tr 44.69 31.60 7.20 31.60
tr-Critical Value 2.447 2.776 2.365 2.776
tr >tr-Critical Value
H0(T^M) Reject Reject Reject Reject
H0 (T^F): Testability and Flexibility are not highly correlated.
Table 5(b): Correlation Coefficient Test for Testability and Flexibility
System W System X System Y System Z
Testability ^ Flexibility .877 .772 .763 .987
tr 3.65 1.72 2.64 8.68
tr-Critical Value 2.447 2.776 2.365 2.776
tr >tr-Critical Value ×
H0(T^F) Reject Accept Reject Reject
Using 2-tailed test at the 0.05 for a 95% confidence interval with different degrees of freedom, it
is clear from the tables 5(a) and (b), the null hypothesis is rejected (with the exception of, for
system ‘X’ of Testability and Flexibility).As a result, the researcher’s claim of correlating
Testability with Modifiability and Flexibility at design phase is Statistically extremely justified.
7. CONCLUSIONS
In this paper, software testability key factors are identified and their impact on testability
measurement and improvement at design phase has been analyzed. ‘Modifiability and
Flexibility’, two of the key factors affecting object oriented design testability have been taken into
consideration. Considering both the major factors, a testability measurement model for object
oriented design has been developed (TMMOOD
), and the statistical inferences are validated for
high level better acceptability. The developed model to measure testability of object oriented
software design is extremely trustworthy and correlated with object oriented design constructs.
Testability measurement model has been validated theoretically as well as empirically using
experimental try-out. The applied validation on the testability model concludes that proposed
model is highly consistent, acceptable and reliable.
ACKNOWLEDGEMENTS
First and foremost, I would like to thank my supervisor Dr. Reena Srivastava and Dr. M.H.
Khan, for standing beside me throughout my research and authoring this research paper. Both has
been my inspiration and motivation for continuing to improve my knowledge and move my
research forward.
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Authors
Abdullah received the MCA degree from Uttar Pradesh Technical University,
Lucknow, in 2006. He is currently working as an Associate Professor, in the
Department of Computer Application, at Institute of Environment and Management,
Lucknow. His research interests Include Software testability, Software Quality
Estimation. He has written various books and study materials for (North Orissa
University) Orissa, (Suresh Gyan Vihar University, Jaipur) Rajasthan, (Bharati
Vidyapeeth University, Pune) Maharashtra, NAAC Re-Accredited “A" Grade
University.
11. International Journal of Computer Science & Information Technology (IJCSIT) Vol 7, No 1, February 2015
163
Dr. M. H. Khan, Associate Professor, Department of Computer Science and
Engineering at IET Lucknow UP. He obtained his MCA degree from Aligarh
Muslim University (A Central University) in 1989. Later he did his PhD from
Lucknow University. He has around 25 years rich teaching experience at UG and PG
level. His area of research is Software Engineering. Dr. Khan published numerous
articles, several papers in the National and International Journals and conference
proceedings.
Dr. Reena Srivastava is currently working as Dean, School of Computer Applications
at BBD University, Lucknow. She received her Ph.D. degree from MNNIT Allahabad,
India. Her research area includes Multi-Relational Classification, Privacy Preserving
Data Mining and Software Engineering.