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Richard Torkar

Publications and source records attributed to Richard Torkar.

31 records · Page 2Linked to original sources
arXiv2019

Estimating Return on Investment for GUI Test Automation Tools

Automated graphical user interface (GUI) tests can reduce manual testing activities and increase test frequency. This motivates the conversion of manual test cases into automated GUI tests. However, it is not clear whether such automation is cost-effective given that GUI automation scripts add to the code base and demand maintenance as a system evolves. In this paper, we introduce a method for estimating maintenance cost and Return on Investment (ROI) for Automated GUI Testing (AGT). The method utilizes the existing source code change history and can be used for evaluation also of other testing or quality assurance automation technologies. We evaluate the method for a real-world, industrial software system and compare two fundamentally different AGT tools, namely Selenium and EyeAutomate, to estimate and compare their ROI. We also report on their defect-finding capabilities and usability. The quantitative data is complemented by interviews with employees at the case company. The method was successfully applied and estimated maintenance cost and ROI for both tools are reported. Overall, the study supports earlier results showing that implementation time is the leading cost for introducing AGT. The findings further suggest that while EyeAutomate tests are significantly faster to implement, Selenium tests require more of a programming background but less maintenance.

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arXiv2019

Bayesian Data Analysis in Empirical Software Engineering Research

Statistics comes in two main flavors: frequentist and Bayesian. For historical and technical reasons, frequentist statistics have traditionally dominated empirical data analysis, and certainly remain prevalent in empirical software engineering. This situation is unfortunate because frequentist statistics suffer from a number of shortcomings---such as lack of flexibility and results that are unintuitive and hard to interpret---that curtail their effectiveness when dealing with the heterogeneous data that is increasingly available for empirical analysis of software engineering practice. In this paper, we pinpoint these shortcomings, and present Bayesian data analysis techniques that provide tangible benefits---as they can provide clearer results that are simultaneously robust and nuanced. After a short, high-level introduction to the basic tools of Bayesian statistics, we present the reanalysis of two empirical studies on the effectiveness of automatically generated tests and the performance of programming languages. By contrasting the original frequentist analyses with our new Bayesian analyses, we demonstrate the concrete advantages of the latter. To conclude we advocate a more prominent role for Bayesian statistical techniques in empirical software engineering research and practice.

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arXiv2019

Evolution of statistical analysis in empirical software engineering research: Current state and steps forward

Software engineering research is evolving and papers are increasingly based on empirical data from a multitude of sources, using statistical tests to determine if and to what degree empirical evidence supports their hypotheses. To investigate the practices and trends of statistical analysis in empirical software engineering (ESE), this paper presents a review of a large pool of papers from top-ranked software engineering journals. First, we manually reviewed 161 papers and in the second phase of our method, we conducted a more extensive semi-automatic classification of papers spanning the years 2001--2015 and 5,196 papers. Results from both review steps was used to: i) identify and analyze the predominant practices in ESE (e.g., using t-test or ANOVA), as well as relevant trends in usage of specific statistical methods (e.g., nonparametric tests and effect size measures) and, ii) develop a conceptual model for a statistical analysis workflow with suggestions on how to apply different statistical methods as well as guidelines to avoid pitfalls. Lastly, we confirm existing claims that current ESE practices lack a standard to report practical significance of results. We illustrate how practical significance can be discussed in terms of both the statistical analysis and in the practitioner's context.

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arXiv2019

The Connection Between Burnout and Personality Types in Software Developers

This paper examines the connection between the Five Factor Model personality traits and burnout in software developers. This study aims to validate generalizations of findings in other fields. An online survey consisting of a miniaturized International Personality Item Pool questionnaire for measuring the Five Factor Model personality traits, and the Shirom-Melamed Burnout Measure for measuring burnout, were distributed to open source developer mailing lists, obtaining 47 valid responses. The results from a Bayesian Linear Regression analysis indicate a strong link between neuroticism and burnout confirming previous work, while the other Five Factor Model traits were not adding power to the model. It is important to note that we did not investigate the quality of work in connection to personality, nor did we take any other confounding factors into account like, for example, teamwork. Nonetheless, employers could be aware of, and support, software developers with high neuroticism.

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arXiv2019

The Unfulfilled Potential of Data-Driven Decision Making in Agile Software Development

With the general trend towards data-driven decision making (DDDM), organizations are looking for ways to use DDDM to improve their decisions. However, few studies have looked into the practitioners view of DDDM, in particular for agile organizations. In this paper we investigated the experiences of using DDDM, and how data can improve decision making. An emailed questionnaire was sent out to 124 industry practitioners in agile software developing companies, of which 84 answered. The results show that few practitioners indicated a widespread use of DDDM in their current decision making practices. The practitioners were more positive to its future use for higher-level and more general decision making, fairly positive to its use for requirements elicitation and prioritization decisions, while being less positive to its future use at the team level. The practitioners do see a lot of potential for DDDM in an agile context; however, currently unfulfilled.

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arXiv2019

The prospects of a quantitative measurement of agility: A validation study on an agile maturity model

Agile development has now become a well-known approach to collaboration in professional work life. Both researchers and practitioners want validated tools to measure agility. This study sets out to validate an agile maturity measurement model with statistical tests and empirical data. First, a pretest was conducted as a case study including a survey and focus group. Second, the main study was conducted with 45 employees from two SAP customers in the US. We used internal consistency (by a Cronbach's alpha) as the main measure for reliability and analyzed construct validity by exploratory principal factor analysis (PFA). The results suggest a new categorization of a subset of items existing in the tool and provides empirical support for these new groups of factors. However, we argue that more work is needed to reach the point where a maturity models with quantitative data can be said to validly measure agility, and even then, such a measurement still needs to include some deeper analysis with cultural and contextual items.

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arXiv2019

Group development and group maturity when building agile teams: A qualitative and quantitative investigation at eight large companies

The agile approach to projects focuses more on close-knit teams than traditional waterfall projects, which means that aspects of group maturity become even more important. This psychological aspect is not much researched in connection to the building of an "agile team." The purpose of this study is to investigate how building agile teams is connected to a group development model taken from social psychology. We conducted ten semi-structured interviews with coaches, Scrum Masters, and managers responsible for the agile process from seven different companies, and collected survey data from 66 group-members from four companies (a total of eight different companies). The survey included an agile measurement tool and the one part of the Group Development Questionnaire. The results show that the practitioners define group developmental aspects as key factors to a successful agile transition. Also, the quantitative measurement of agility was significantly correlated to the group maturity measurement. We conclude that adding these psychological aspects to the description of the "agile team" could increase the understanding of agility and partly help define an "agile team." We propose that future work should develop specific guidelines for how software development teams at different maturity levels might adopt agile principles and practices differently.

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arXiv2019

Work Motivational Challenges Regarding the Interface Between Agile Teams and a Non-Agile Surrounding Organization: A case study

There are studies showing what happens if agile teams are introduced into a non-agile organization, e.g. higher overhead costs and the necessity of an understanding of agile methods even outside the teams. This case study shows an example of work motivational aspects that might surface when an agile team exists in the middle of a more traditional structure. This case study was conducted at a car manufacturer in Sweden, consisting of an unstructured interview with the Scrum Master and a semi-structured focus group. The results show that the teams felt that the feedback from the surrounding organization was unsynchronized resulting in them not feeling appreciated when delivering their work. Moreover, they felt frustrated when working on non-agile teams after have been working on agile ones. This study concludes that there were work motivational affects of fitting an agile team into a non-agile surrounding organization, and therefore this might also be true for other organizations.

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arXiv2019

Group Maturity and Agility, Are They Connected? - A Survey Study

The focus on psychology has increased within software engineering due to the project management innovation "agile development processes". The agile methods do not explicitly consider group development aspects; they simply assume what is described in group psychology as mature groups. This study was conducted with 45 employees and their twelve managers (N=57) from two SAP customers in the US that were working with agile methods, and the data were collected via an online survey. The selected Agility measurement was correlated to a Group Development measurement and showed significant convergent validity, i.e., a more mature team is also a more agile team. This means that the agile methods probably would benefit from taking group development into account when its practices are being introduced.

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arXiv2018

Transferring Interactive Search-Based Software Testing to Industry

Search-Based Software Testing (SBST) is the application of optimization algorithms to problems in software testing. In previous work, we have implemented and evaluated Interactive Search-Based Software Testing (ISBST) tool prototypes, with a goal to successfully transfer the technique to industry. While SBSE solutions are often validated on benchmark problems, there is a need to validate them in an operational setting. The present paper discusses the development and deployment of SBST tools for use in industry and reflects on the transfer of these techniques to industry. In addition to previous work discussing the development and validation of an ISBST prototype, a new version of the prototype ISBST system was evaluated in the laboratory and in industry. This evaluation is based on an industrial System under Test (SUT) and was carried out with industrial practitioners. The Technology Transfer Model is used as a framework to describe the progression of the development and evaluation of the ISBST system. The paper presents a synthesis of previous work developing and evaluating the ISBST prototype, as well as presenting an evaluation, in both academia and industry, of that prototype's latest version. This paper presents an overview of the development and deployment of the ISBST system in an industrial setting, using the framework of the Technology Transfer Model. We conclude that the ISBST system is capable of evolving useful test cases for that setting, though improvements in the means the system uses to communicate that information to the user are still required. In addition, a set of lessons learned from the project are listed and discussed. Our objective is to help other researchers that wish to validate search-based systems in industry and provide more information about the benefits and drawbacks of these systems.

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arXiv2018

Ways of Applying Artificial Intelligence in Software Engineering

As Artificial Intelligence (AI) techniques have become more powerful and easier to use they are increasingly deployed as key components of modern software systems. While this enables new functionality and often allows better adaptation to user needs it also creates additional problems for software engineers and exposes companies to new risks. Some work has been done to better understand the interaction between Software Engineering and AI but we lack methods to classify ways of applying AI in software systems and to analyse and understand the risks this poses. Only by doing so can we devise tools and solutions to help mitigate them. This paper presents the AI in SE Application Levels (AI-SEAL) taxonomy that categorises applications according to their point of AI application, the type of AI technology used and the automation level allowed. We show the usefulness of this taxonomy by classifying 15 papers from previous editions of the RAISE workshop. Results show that the taxonomy allows classification of distinct AI applications and provides insights concerning the risks associated with them. We argue that this will be important for companies in deciding how to apply AI in their software applications and to create strategies for its use.

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arXiv2015

Tester Interactivity makes a Difference in Search-Based Software Testing: A Controlled Experiment

Context: Search-based software testing promises to provide users with the ability to generate high-quality test cases, and hence increase product quality, with a minimal increase in the time and effort required. One result that emerged out of a previous study to investigate the application of search-based software testing (SBST) in an industrial setting was the development of the Interactive Search-Based Software Testing (ISBST) system. ISBST allows users to interact with the underlying SBST system, guiding the search and assessing the results. An industrial evaluation indicated that the ISBST system could find test cases that are not created by testers employing manual techniques. The validity of the evaluation was threatened, however, by the low number of participants. Objective: This paper presents a follow-up study, to provide a more rigorous evaluation of the ISBST system. Method: To assess the ISBST system a two-way crossover controlled experiment was conducted with 58 students taking a Verification and Validation course. The NASA Task Load Index (NASA-TLX) is used to assess the workload experienced by the participants in the experiment. Results: The experimental results validated the hypothesis that the ISBST system generates test cases that are not found by the same participants employing manual testing techniques. A follow-up laboratory experiment also investigates the importance of interaction in obtaining the results. In addition to this main result, the subjective workload was assessed for each participant by means of the NASA-TLX tool. The evaluation showed that, while the ISBST system required more effort from the participants, they achieved the same performance. Conclusions: The paper provides evidence that the ISBST system develops test cases that are not found by manual techniques, and that interaction plays an important role in achieving that result.

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