Software quality attribute measurement and analysis based on class diagram metrics

Software quality measurement lies at the heart of the quality engineering process. Quality measurement for object-oriented artifacts has become the key for ensuring high quality software. Both researchers and practitioners are interested in measuring software product quality for improvement. It has recently become more important to consider the quality of products at the early phases, especially at the design level to ensure that the coding and testing would be conducted more quickly and accurately. The research work on measuring quality at the design level progressed in a number of steps. The first step was to discover the correct set of metrics to measure design elements at the design level. Chidamber and Kemerer (C&K) formulated the first suite of OO metrics. Other researchers extended on this suite and provided additional metrics. The next step was to collect these metrics by using software tools. A number of tools were developed to measure the different suites of metrics; some represent their measurements in the form of ordinary numbers, others represent them in 3D visual form. In recent years, researchers developed software quality models which went a bit further by computing quality attributes from collected design metrics. In this research we extended on the software quality modelers’ work by adding a quality attribute prioritization scheme and a design metric analysis layer. Our work is all focused on the class diagram, the most fundamental constituent in any object oriented design. Using earlier researchers’ work, we extract a class diagram’s metrics and compute its quality attributes. We then analyze the results and inform the user. We present our figures and observations in the form of an analysis report. Our target user could be a project manager or a software quality engineer or a developer who needs to improve the class diagram’s quality. We closely examine the design metrics that affect quality attributes. We pinpoint the weaknesses in the class diagram, based on these metrics, inform the user about the problems that emerged from these classes, and advice him/her as to how he/she can go about improving the overall design quality. We consider the six basic quality attributes: “Reusability”, “Functionality”, “Understandability”, “Flexibility”, “Extendibility”, and “Effectiveness” of the whole class diagram. We allow the user to set priorities on these quality attributes in a sequential manner based on his/her requirements. Using a geometric series, we calculate a weighted average value for the arranged list of quality attributes. This weighted average value indicates the overall quality of the product, the class diagram. Our experimental work gave us much insight into the meanings and dependencies between design metrics and quality attributes. This helped us refine our analysis technique and give more concrete observations to the user

Comparing the effectiveness of automated test generation tools "EVOSUITE"� and "Tpalus"�

University of Minnesota M.S. thesis. July 2015. Major: Computer Science. Advisor: Andrew Brooks. 1 computer file (PDF); vii, 71 pages.Automated testing has been evolving over the years and the main reason behind the growth of these tools is to reduce the manual effort in checking the correctness of any software. Writing test cases to check the correctness of software is very time consuming and requires a great deal of patience. A lot of time and effort used on writing manual test cases can be saved and in turn we can focus on improving the performance of the application. Statistics show that 50% of the total cost of software development is devoted to software testing, even more in the case of critical software. The growth of these automated test generation tools lead us to a big question of "How effective are these tools in checking the correctness of the application?"� There are several challenges associated with developing automated test generation tools and currently there is no particular tool or metric to check the effectiveness of these automated test generation tools. In my thesis, I aim to measure the effectiveness of two automated test generation tools. The two automated tools on which I have experimented on are Tpalus and EVOSUITE. Tpalus and EVOSUITE are capable of generating test cases for any program written in Java. They are specifically designed to work on Java. Several metrics have to be considered in measuring the effectiveness of a tool. I use the results obtained from these tools on several open source subjects to evaluate both the tools. The metrics that were chosen in comparing these tools include code coverage, mutation scores, and size of the test suite. Code coverage tells us how well the source code is covered by the test cases. A better test suite generally aims to cover most of the source code to consider each and every statement as a part of testing. A mutation score is an indication of the test suite detecting and killing mutants. In this case, a mutant is a new version of a program that is created by making a small syntactic change to the original program. The higher mutation score, the higher the number of mutants detected and killed. Results obtained during the experiment include branch coverage, line coverage, raw kill score and normalized kill score. These results help us to decide how effective these tools are when testing critical software

Cloud based testing of business applications and web services

This paper deals with testing of applications based on the principles of cloud computing. It is aimed to describe options of testing business software in clouds (cloud testing). It identifies the needs for cloud testing tools including multi-layer testing; service level agreement (SLA) based testing, large scale simulation, and on-demand test environment. In a cloud-based model, ICT services are distributed and accessed over networks such as intranet or internet, which offer large data centers deliver on demand, resources as a service, eliminating the need for investments in specific hardware, software, or on data center infrastructure. Businesses can apply those new technologies in the contest of intellectual capital management to lower the cost and increase competitiveness and also earnings. Based on comparison of the testing tools and techniques, the paper further investigates future trend of cloud based testing tools research and development. It is also important to say that this comparison and classification of testing tools describes a new area and it has not yet been done

Measuring the software process and product: Lessons learned in the SEL

The software development process and product can and should be measured. The software measurement process at the Software Engineering Laboratory (SEL) has taught a major lesson: develop a goal-driven paradigm (also characterized as a goal/question/metric paradigm) for data collection. Project analysis under this paradigm leads to a design for evaluating and improving the methodology of software development and maintenance

Software Measurement Activities in Small and Medium Enterprises: an Empirical Assessment

An empirical study for evaluating the proper implementation of measurement/metric programs in software companies in one area of Turkey is presented. The research questions are discussed and validated with the help of senior software managers (more than 15 years’ experience) and then used for interviewing a variety of medium and small scale software companies in Ankara. Observations show that there is a common reluctance/lack of interest in utilizing measurements/metrics despite the fact that they are well known in the industry. A side product of this research is that internationally recognized standards such as ISO and CMMI are pursued if they are a part of project/job requirements; without these requirements, introducing those standards to the companies remains as a long-term target to increase quality

Software component testing : a standard and the effectiveness of techniques

This portfolio comprises two projects linked by the theme of software component testing, which is also often referred to as module or unit testing. One project covers its standardisation, while the other considers the analysis and evaluation of the application of selected testing techniques to an existing avionics system. The evaluation is based on empirical data obtained from fault reports relating to the avionics system. The standardisation project is based on the development of the BC BSI Software Component Testing Standard and the BCS/BSI Glossary of terms used in software testing, which are both included in the portfolio. The papers included for this project consider both those issues concerned with the adopted development process and the resolution of technical matters concerning the definition of the testing techniques and their associated measures. The test effectiveness project documents a retrospective analysis of an operational avionics system to determine the relative effectiveness of several software component testing techniques. The methodology differs from that used in other test effectiveness experiments in that it considers every possible set of inputs that are required to satisfy a testing technique rather than arbitrarily chosen values from within this set. The three papers present the experimental methodology used, intermediate results from a failure analysis of the studied system, and the test effectiveness results for ten testing techniques, definitions for which were taken from the BCS BSI Software Component Testing Standard. The creation of the two standards has filled a gap in both the national and international software testing standards arenas. Their production required an in-depth knowledge of software component testing techniques, the identification and use of a development process, and the negotiation of the standardisation process at a national level. The knowledge gained during this process has been disseminated by the author in the papers included as part of this portfolio. The investigation of test effectiveness has introduced a new methodology for determining the test effectiveness of software component testing techniques by means of a retrospective analysis and so provided a new set of data that can be added to the body of empirical data on software component testing effectiveness