413,921 research outputs found
A Study on Software Testability and the Quality of Testing in Object-Oriented Systems
Software testing is known to be important to the delivery of high-quality systems, but it is also challenging, expensive and time-consuming. This has motivated academic and industrial researchers to seek ways to improve the testability of software. Software testability is the ease with which a software artefact can be effectively tested.
The first step towards building testable software components is to understand the factors – of software processes, products and people – that are related to and can influence software testability. In particular, the goal of this thesis is to provide researchers and practitioners with a comprehensive understanding of design and source code factors that can affect the testability of a class in object oriented systems. This thesis considers three different views on software testability that address three related aspects: 1) the distribution of unit tests in relation to the dynamic coupling and centrality of software production classes, 2) the relationship between dynamic (i.e., runtime) software properties and class testability, and 3) the relationship between code smells, test smells and the factors related to smells distribution. The thesis utilises a combination of source code analysis techniques (both static and dynamic), software metrics, software visualisation techniques and graph-based metrics (from complex networks theory) to address its goals and objectives.
A systematic mapping study was first conducted to thoroughly investigate the body of research on dynamic software metrics and to identify issues associated with their selection, design and implementation. This mapping study identified, evaluated and classified 62 research works based on a pre-tested protocol and a set of classification criteria. Based on the findings of this study, a number of dynamic metrics were selected and used in the experiments that were then conducted.
The thesis demonstrates that by using a combination of visualisation, dynamic analysis, static analysis and graph-based metrics it is feasible to identify central classes and to diagrammatically depict testing coverage information. Experimental results show that, even in projects with high test coverage, some classes appear to be left without any direct unit testing, even though they play a central role during a typical execution profile. It is contended that the proposed visualisation techniques could be particularly helpful when developers need to maintain and reengineer existing test suites.
Another important finding of this thesis is that frequently executed and tightly coupled classes are correlated with the testability of the class – such classes require larger unit tests and more test cases. This information could inform estimates of the effort required to test classes when developing new unit tests or when maintaining and refactoring existing tests.
An additional key finding of this thesis is that test and code smells, in general, can have a negative impact on class testability. Increasing levels of size and complexity in code are associated with the increased presence of test smells. In addition, production classes that contain smells generally require larger unit tests, and are also likely to be associated with test smells in their associated unit tests. There are some particular smells that are more significantly associated with class testability than other smells. Furthermore, some particular code smells can be seen as a sign for the presence of test smells, as some test and code smells are found to co-occur in the test and production code. These results suggest that code smells, and specifically certain types of smells, as well as measures of size and complexity, can be used to provide a more comprehensive indication of smells likely to emerge in test code produced subsequently (or vice versa in a test-first context). Such findings should contribute positively to the work of testers and maintainers when writing unit tests and when refactoring and maintaining existing tests
Non-Technical Individual Skills are Weakly Connected to the Maturity of Agile Practices
Context: Existing knowledge in agile software development suggests that
individual competency (e.g. skills) is a critical success factor for agile
projects. While assuming that technical skills are important for every kind of
software development project, many researchers suggest that non-technical
individual skills are especially important in agile software development.
Objective: In this paper, we investigate whether non-technical individual
skills can predict the use of agile practices. Method: Through creating a set
of multiple linear regression models using a total of 113 participants from
agile teams in six software development organizations from The Netherlands and
Brazil, we analyzed the predictive power of non-technical individual skills in
relation to agile practices. Results: The results show that there is
surprisingly low power in using non-technical individual skills to predict
(i.e. explain variance in) the mature use of agile practices in software
development. Conclusions: Therefore, we conclude that looking at non-technical
individual skills is not the optimal level of analysis when trying to
understand, and explain, the mature use of agile practices in the software
development context. We argue that it is more important to focus on the
non-technical skills as a team-level capacity instead of assuring that all
individuals possess such skills when understanding the use of the agile
practices.Comment: 18 pages, 1 figur
Mapping Varieties of Industrial Relations: Eurofound\u27s Analytical Framework Applied
Eurofound’s 2016 report Mapping key dimensions of industrial relations identified four key dimensions of industrial relations: industrial democracy, industrial competitiveness, social justice, and quality of work and employment. This report builds upon that earlier study, developing a dashboard of 45 indicators to assess how and to what extent the conceptual framework of these key dimensions can be applied at national level. The indicators were tested across the Member States by Eurofound’s Network of European Correspondents and show reasonable accuracy when used to map the predominant features and trends of the national industrial relations systems. The study confirms that a dashboard of indicators that can accurately measure and summarise the complex reality of industrial relations across the EU is a valuable tool for comparative research and a useful instrument for supporting policymakers, social partners and stakeholders. The report sets out a range of options for further developing this conceptual approach
Maintenance of Automated Test Suites in Industry: An Empirical study on Visual GUI Testing
Context: Verification and validation (V&V) activities make up 20 to 50
percent of the total development costs of a software system in practice. Test
automation is proposed to lower these V&V costs but available research only
provides limited empirical data from industrial practice about the maintenance
costs of automated tests and what factors affect these costs. In particular,
these costs and factors are unknown for automated GUI-based testing.
Objective: This paper addresses this lack of knowledge through analysis of
the costs and factors associated with the maintenance of automated GUI-based
tests in industrial practice.
Method: An empirical study at two companies, Siemens and Saab, is reported
where interviews about, and empirical work with, Visual GUI Testing is
performed to acquire data about the technique's maintenance costs and
feasibility.
Results: 13 factors are observed that affect maintenance, e.g. tester
knowledge/experience and test case complexity. Further, statistical analysis
shows that developing new test scripts is costlier than maintenance but also
that frequent maintenance is less costly than infrequent, big bang maintenance.
In addition a cost model, based on previous work, is presented that estimates
the time to positive return on investment (ROI) of test automation compared to
manual testing.
Conclusions: It is concluded that test automation can lower overall software
development costs of a project whilst also having positive effects on software
quality. However, maintenance costs can still be considerable and the less time
a company currently spends on manual testing, the more time is required before
positive, economic, ROI is reached after automation
SmartUnit: Empirical Evaluations for Automated Unit Testing of Embedded Software in Industry
In this paper, we aim at the automated unit coverage-based testing for
embedded software. To achieve the goal, by analyzing the industrial
requirements and our previous work on automated unit testing tool CAUT, we
rebuild a new tool, SmartUnit, to solve the engineering requirements that take
place in our partner companies. SmartUnit is a dynamic symbolic execution
implementation, which supports statement, branch, boundary value and MC/DC
coverage. SmartUnit has been used to test more than one million lines of code
in real projects. For confidentiality motives, we select three in-house real
projects for the empirical evaluations. We also carry out our evaluations on
two open source database projects, SQLite and PostgreSQL, to test the
scalability of our tool since the scale of the embedded software project is
mostly not large, 5K-50K lines of code on average. From our experimental
results, in general, more than 90% of functions in commercial embedded software
achieve 100% statement, branch, MC/DC coverage, more than 80% of functions in
SQLite achieve 100% MC/DC coverage, and more than 60% of functions in
PostgreSQL achieve 100% MC/DC coverage. Moreover, SmartUnit is able to find the
runtime exceptions at the unit testing level. We also have reported exceptions
like array index out of bounds and divided-by-zero in SQLite. Furthermore, we
analyze the reasons of low coverage in automated unit testing in our setting
and give a survey on the situation of manual unit testing with respect to
automated unit testing in industry.Comment: In Proceedings of 40th International Conference on Software
Engineering: Software Engineering in Practice Track, Gothenburg, Sweden, May
27-June 3, 2018 (ICSE-SEIP '18), 10 page
Introducing Energy Efficiency into SQALE
Energy Efficiency is becoming a key factor in software development, given the sharp growth of IT systems and their impact on worldwide energy consumption. We do believe that a quality process infrastructure should be able to consider the Energy Efficiency of a system since its early development: for this reason we propose to introduce Energy Efficiency into the existing quality models. We selected the SQALE model and we tailored it inserting Energy Efficiency as a sub-characteristic of efficiency. We also propose a set of six source code specific requirements for the Java language starting from guidelines currently suggested in the literature. We experienced two major challenges: the identification of measurable, automatically detectable requirements, and the lack of empirical validation on the guidelines currently present in the literature and in the industrial state of the practice as well. We describe an experiment plan to validate the six requirements and evaluate the impact of their violation on Energy Efficiency, which has been partially proved by preliminary results on C code. Having Energy Efficiency in a quality model and well verified code requirements to measure it, will enable a quality process that precisely assesses and monitors the impact of software on energy consumptio
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