Vahid Garousi

Hybrid software and system development in practice: waterfall, scrum, and beyond

Software and system development faces numerous challenges of rapidly changing markets. To address such challenges, companies and projects design and adopt specific development approaches by combining well-structured comprehensive methods and flexible agile practices. Yet, the number of methods and practices is large, and available studies argue that the actual process composition is carried out in a fairly ad-hoc manner. The present paper reports on a survey on hybrid software development approaches. We study which approaches are used in practice, how different approaches are combined, and what contextual factors influence the use and combination of hybrid software development approaches. Our results from 69 study participants show a variety of development approaches used and combined in practice. We show that most combinations follow a pattern in which a traditional process model serves as framework in which several fine-grained (agile) practices are plugged in. We further show that hybrid software development approaches are independent from the company size and external triggers. We conclude that such approaches are the results of a natural process evolution, which is mainly driven by experience, learning, and pragmatism.

Trustworthy Software Development Processes

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Citations, research topics and active countries in software engineering

Context: An enormous number of papers (more than 70,000) have been published in the area of Software Engineering (SE) since its inception in 1968. To better characterize and understand this massive research literature, there is a need for comprehensive bibliometrics assessments in this vibrant field.Objective: The objective of this study is to utilize automated citation and topic analysis to characterize the software engineering research literature over the years. While a few bibliometrics studies have appeared in the field of SE, this article aims to be the most comprehensive bibliometrics assessments in this vibrant field.Method: To achieve the above objective, we report in this paper a bibliometrics study with data collected from Scopus database consisting of over 70,000 articles. For thematic analysis, we used topic modeling to automatically generate the most probable topic distributions given the data.Results: We found that number of papers published per year has grown tremendously and currently 6000-7000 papers are published every year. At the same time, nearly half of the papers are not cited at all. Using text mining of articles titles, we found that currently the hot research topics in software engineering are: (1) web services, (2) mobile and cloud computing, (3) industrial (case) studies, (4) source code and (5) test generation. Finally, we found that a small share of large countries produce the majority of the papers in SE while small European countries are proportionally the most active in the area of SE, based on the number of papers.Conclusion: Due to large volumes of research in SE, we suggest using the automated analysis of bibliometrics as we have done in this paper. By picking out the most cited papers, we can present the land marks of SE and, with thematic analysis, we can characterize the entire field. This can be useful for students and other new comers to SE and for presenting our achievements to other disciplines. In particular, we see and report the value of such an analysis in situations where performing a full scale SLR is not feasible due to restrictions on time or to lack of exact research questions.

Industry–academia collaborations in software testing: experience and success stories from Canada and Turkey

Collaboration between industry and academia supports improvement and innovation in industry and helps to ensure industrial relevance in academic research. However, many researchers and practitioners believe that the level of joint industry–academia collaborations (IAC) in software engineering (SE) is still relatively very low, compared to the amount of activity in each of the two communities. The goal of the empirical study reported in this paper is to characterize a set of collaborative industry–academia R&D projects in the area of software testing conducted by the authors (based in Canada and Turkey) with respect to a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review study, with the aim of contributing to the body of evidence in the area of IAC, for the benefit of SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general. To address the above goal, a pool of ten IAC projects (six completed, two failed and two ongoing) all in the area of software testing, which the authors have led or have had active roles in, were selected as objects of study and were analyzed (both quantitatively and qualitatively) with respect to the set of selected challenges, patterns and anti-patterns. As outputs, the study presents a set of empirical findings and evidence-based recommendations, e.g.: it has been observed that even if an IAC project may seem perfect from many aspects, one single major challenge (e.g., disagreement in confidentiality agreements) can lead to its failure. Thus, we recommend that both parties (academics and practitioners) consider all the challenges early on and proactively work together to eliminate the risk of challenges in IAC projects. We furthermore report correlation and interrelationship of challenges, patterns and anti-patterns with project success measures. This study hopes to encourage and benefit other SE researchers and practitioners in conducting successful IAC projects in software testing and in software engineering in general in the future.

Software test maturity assessment and test process improvement

ContextSoftware testing practices and processes in many companies are far from being mature and are usually conducted in ad-hoc fashions. Such immature practices lead to various negative outcomes, e.g., ineffectiveness of testing practices in detecting all the defects, and cost and schedule overruns of testing activities. To conduct test maturity assessment (TMA) and test process improvement (TPI) in a systematic manner, various TMA/TPI models and approaches have been proposed. ObjectiveIt is important to identify the state-of-the-art and the practice in this area to consolidate the list of all various test maturity models proposed by practitioners and researchers, the drivers of TMA/TPI, the associated challenges and the benefits and results of TMA/TPI. Our article aims to benefit the readers (both practitioners and researchers) by providing the most comprehensive survey of the area, to this date, in assessing and improving the maturity of test processes. MethodTo achieve the above objective, we have performed a Multivocal Literature Review (MLR) study to find out what we know about TMA/TPI. A MLR is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). We searched the academic literature using the Google Scholar and the grey literature using the regular Google search engine. ResultsOur MLR and its results are based on 181 sources, 51 (29%) of which were grey literature and 130 (71%) were formally published sources. By summarizing what we know about TMA/TPI, our review identified 58 different test maturity models and a large number of sources with varying degrees of empirical evidence on this topic. We also conducted qualitative analysis (coding) to synthesize the drivers, challenges and benefits of TMA/TPI from the primary sources. ConclusionWe show that current maturity models and techniques in TMA/TPI provides reasonable advice for industry and the research community. We suggest directions for follow-up work, e.g., using the findings of this MLR in industry-academia collaborative projects and empirical evaluation of models and techniques in the area of TMA/TPI as reported in this article.

Developing, Verifying, and Maintaining High-Quality Automated Test Scripts

With the increasing importance, size, and complexity of automated test suites, the need exists for suitable methods and tools to develop, assess the quality of, and maintain test code (scripts) in parallel with regular production (application) code. A recent review paper called this subarea of software testing software test code engineering (STCE). This article summarizes STCE tools, techniques, and guidelines. It also presents specific quantitative examples in this area based on experience in projects and raises important issues practitioners and researchers must address to further advance this field.

When to automate software testing? A decision-support approach based on process simulation

Software test processes are complex and costly. To reduce testing effort without compromising effectiveness and product quality, automation of test activities has been adopted as a popular approach in software industry. However, because test automation usually requires substantial upfront investments, automation is not always more cost‐effective than manual testing. To support decision‐makers in finding the optimal degree of test automation in a given project, we recently proposed a process simulation model using the System Dynamics modeling technique and used the simulation model in the context of a case study with a software company in Calgary, Canada. With the help of the simulation model, we were able to evaluate the performance of test processes with varying degrees of automation of test activities and help testers choose the most optimal cases. The goal of the earlier study was to investigate how the simulation model can help decision‐makers decide whether and to what degree the company should automate their test processes. In this article, we present further details of the System Dynamics model, its usage scenarios and examples of simulation experiments independent from a specific company context. Copyright

An empirical investigation of single-objective and multiobjective evolutionary algorithms for developer's assignment to bugs

In this paper, the modeling of developers’ assignment to bugs (DAB) is studied. The problem is modeled both as a single objective (minimize bug fix time) and as a bi‐objective (minimize bug fix time and cost) combinatorial optimization problem. Two models of developer assignment are considered where in the first model a single developer is assigned per bug (single developer model), while in the second model a single developer is assigned for each competency area of a bug (individual competency model). The latter model is proposed in this paper. For the single developer model, GA@DAB, an existing genetic algorithm‐based approach, is extended to support precedence among bugs. For the individual competency model of DAB, one genetic algorithm‐based approach (Competence@DAB) and one nondominated sorting genetic algorithm II‐based approach (CompetenceMulti2@DAB ) are proposed to generate solutions minimizing time and minimizing both time and cost, respectively. The performance of the proposed approaches was evaluated for 2040 bugs of 19 open‐source milestone projects from the Eclipse platform. Our results and analysis show that the proposed individual competency model is far better than the single developer model, with average bug fix time reduction of 39.7% across all projects. Copyright

Quantity versus impact of software engineering papers: a quantitative study

According to the data from the Scopus publication database, as analyzed in several recent studies, more than 70,000 papers have been published in the area of Software Engineering (SE) since late 1960’s. According to our recent work, 43% of those papers have received no citations at all. Since citations are the most commonly used metric for measuring research (academic) impact, these figures raise questions (doubts) about the (non-existing) impact of such a large set of papers. It is a reality that typical academic reward systems encourage researchers to publish more papers and do not place a major emphasis on research impact. To shed light on the issue of volume (quantity) versus citation-based impact of SE research papers, we conduct and report in this paper a quantitative bibliometrics assessment in four aspects: (1) quantity versus impact of different paper types (e.g., conference versus journal papers), (2) ratios of uncited (non-impactful) papers, (3) quantity versus impact of papers originating from different countries, and (4) quantity versus impact of papers by each of the top-10 authors (in terms of number of papers). To achieve the above objective, we conducted a quantitative exploratory bibliometrics assessment, comprised of four research questions, to assess quantity versus impact of SE papers with respect to the aspects discussed above. We extracted the data through a systematic, automated and repeatable process from the Scopus paper database, which we also used in two previous papers. Our results show that the distribution of SE publications has a major inequality in terms of impact overall, and also when categorized in terms of the above four aspects. The situation in the SE literature is similar to the other areas of science as studied by previous bibliometrics studies. Also, among our results is the fact that journal articles and conference papers have been cited 12.6 and 3.6 times on average, confirming the expectation that journal articles have more impact, in general, than conference papers. Also, papers originated from English-speaking countries have in general more visibility and impact (and consequently citations) when compared to papers originated from non-English-speaking countries. Our results have implications for improvement of academic reward systems, which nowadays mainly encourage researchers to publish more papers and usually neglect research impact. Also, our results can help researchers in non-English-speaking countries to consider improvements to increase their research impact of their upcoming papers.

Worlds Apart: Industrial and Academic Focus Areas in Software Testing

To determine how industry and academia approach software testing, researchers compared the titles of presentations from selected conferences in each of the two communities. The results shed light on the root cause of low industry–academia collaboration and led to suggestions on how to improve this situation.