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| 2. |
- Iftikhar, Umar
(författare)
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Towards Measuring & Improving Source Code Quality
- 2024
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- Context: Software quality has a multi-faceted description encompassing several quality attributes. Central to our efforts to enhance software quality is to improve the quality of the source code. Poor source code quality impacts the quality of the delivered product. Empirical studies have investigated how to improve source code quality and how to quantify the source code improvement. However, the reported evidence linking internal code structure information and quality attributes observed by users is varied and, at times, conflicting. Furthermore, there is a further need for research to improve source code quality by understanding trends in feedback from code review comments.Objective: This thesis contributes towards improving source code quality and synthesizes metrics to measure improvement in source code quality. Hence, our objectives are 1) To synthesize evidence of links between source code metrics and external quality attributes, & identify source code metrics, and 2) To identify areas to improve source code quality by identifying recurring code quality issues using the analysis of code review comments.Method: We conducted a tertiary study to achieve the first objective, an archival analysis and a case study to investigate the latter two objectives.Results: To quantify source code quality improvement, we reported a comprehensive catalog of source code metrics and a small set of source code metrics consistently linked with maintainability, reliability, and security. To improve source code quality using analysis of code review comments, our explored methodology improves the state-of-the-art with interesting results.Conclusions: The thesis provides a promising way to analyze themes in code review comments. Researchers can use the source code metrics provided to estimate these quality attributes reliably. In future work, we aim to derive a software improvement checklist based on the analysis of trends in code review comments.
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| 3. |
- Ali, Nauman bin, Dr., et al.
(författare)
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A Comparison of Citation Sources for Reference and Citation-Based Search in Systematic Literature Reviews
- 2022
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Ingår i: e-Informatica Software Engineering Journal. - : Wroclaw University of Technology. - 1897-7979 .- 2084-4840. ; 16:1
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Forskningsöversikt (refereegranskat)abstract
- Context: In software engineering, snowball sampling has been used as a supplementary and primary search strategy. The current guidelines recommend using Google Scholar (GS) for snowball sampling. However, the use of GS presents several challenges when using it as a source for citations and references. Objective: To compare the effectiveness and usefulness of two leading citation databases (GS and Scopus) for use in snowball sampling search. Method: We relied on a published study that has used snowball sampling as a search strategy and GS as the citation source. We used its primary studies to compute precision and recall for Scopus. Results: In this particular case, Scopus was highly effective with 95% recall and had better precision of 5.1% compared to GS’s 2.8%. Moreover, Scopus found nine additional relevant papers. On average, one would read approximately 15 extra papers in GS than Scopus to identify one additional relevant paper. Furthermore, Scopus supports batch downloading of both citations and papers’ references, has better quality metadata, and does better source filtering. Conclusion: This study suggests that Scopus seems to be more effective and useful for snowball sampling than GS for systematic secondary studies attempting to identify peer-reviewed literature. EVIE © 2022 The Authors.
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| 4. |
- Bjarnason, Elizabeth, et al.
(författare)
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Software selection in large-scale software engineering : A model and criteria based on interactive rapid reviews
- 2023
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Ingår i: Empirical Software Engineering. - : Springer. - 1382-3256 .- 1573-7616. ; 28:2
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Tidskriftsartikel (refereegranskat)abstract
- Context: Software selection in large-scale software development continues to be ad hoc and ill-structured. Previous proposals for software component selection tend to be technology-specific and/or do not consider business or ecosystem concerns. Objective: Our main aim is to develop an industrially relevant technology-agnostic method that can support practitioners in making informed decisions when selecting software components for use in tools or in products based on a holistic perspective of the overall environment. Method: We used method engineering to iteratively develop a software selection method for Ericsson AB based on a combination of published research and practitioner insights. We used interactive rapid reviews to systematically identify and analyse scientific literature and to support close cooperation and co-design with practitioners from Ericsson. The model has been validated through a focus group and by practical use at the case company. Results: The model consists of a high-level selection process and a wide range of criteria for assessing and for evaluating software to include in business products and tools. Conclusions: We have developed an industrially relevant model for component selection through active engagement from a company. Co-designing the model based on previous knowledge demonstrates a viable approach to industry-academia collaboration and provides a practical solution that can support practitioners in making informed decisions based on a holistic analysis of business, organisation and technical factors. © 2023, The Author(s).
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| 5. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Acceptance behavior theories and models in software engineering — A mapping study
- 2024
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 172
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Tidskriftsartikel (refereegranskat)abstract
- Context: The adoption or acceptance of new technologies or ways of working in software development activities is a recurrent topic in the software engineering literature. The topic has, therefore, been empirically investigated extensively. It is, however, unclear which theoretical frames of reference are used in this research to explain acceptance behaviors. Objective: In this study, we explore how major theories and models of acceptance behavior have been used in the software engineering literature to empirically investigate acceptance behavior.Method: We conduct a systematic mapping study of empirical studies using acceptance behavior theories in software engineering.Results: We identified 47 primary studies covering 56 theory uses. The theories were categorized into six groups. Technology acceptance models (TAM and its extensions) were used in 29 of the 47 primary studies, innovation theories in 10, and the theories of planned behavior/ reasoned action (TPB/TRA) in six. All other theories were used in at most two of the primary studies. The usage and operationalization of the theories were, in many cases, inconsistent with the underlying theories. Furthermore, we identified 77 constructs used by these studies of which many lack clear definitions. Conclusions: Our results show that software engineering researchers are aware of some of the leading theories and models of acceptance behavior, which indicates an attempt to have more theoretical foundations. However, we identified issues related to theory usage that make it difficult to aggregate and synthesize results across studies. We propose mitigation actions that encourage the consistent use of theories and emphasize the measurement of key constructs.
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| 6. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Double-counting in software engineering tertiary studies — An overlooked threat to validity
- 2023
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 158
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Forskningsöversikt (refereegranskat)abstract
- Context: Double-counting in a literature review occurs when the same data, population, or evidence is erroneously counted multiple times during synthesis. Detecting and mitigating the threat of double-counting is particularly challenging in tertiary studies. Although this topic has received much attention in the health sciences, it seems to have been overlooked in software engineering. Objective: We describe issues with double-counting in tertiary studies, investigate the prevalence of the issue in software engineering, and propose ways to identify and address the issue. Method: We analyze 47 tertiary studies in software engineering to investigate in which ways they address double-counting and whether double-counting might be a threat to validity in them. Results: In 19 of the 47 tertiary studies, double-counting might bias their results. Of those 19 tertiary studies, only 5 consider double-counting a threat to their validity, and 7 suggest strategies to address the issue. Overall, only 9 of the 47 tertiary studies, acknowledge double-counting as a potential general threat to validity for tertiary studies. Conclusions: Double-counting is an overlooked issue in tertiary studies in software engineering, and existing design and evaluation guidelines do not address it sufficiently. Therefore, we propose recommendations that may help to identify and mitigate double-counting in tertiary studies. © 2023 The Author(s)
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| 7. |
- Börstler, Jürgen, 1960-, et al.
(författare)
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Investigating Acceptance Behavior in Software Engineering – Theoretical Perspectives
- 2023
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Ingår i: Journal of Systems and Software. - : Elsevier. - 0164-1212 .- 1873-1228. ; 198
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Tidskriftsartikel (refereegranskat)abstract
- Background: Software engineering research aims to establish software development practice on a scientific basis. However, the evidence of the efficacy of technology is insufficient to ensure its uptake in industry. In the absence of a theoretical frame of reference, we mainly rely on best practices and expert judgment from industry-academia collaboration and software process improvement research to improve the acceptance of the proposed technology. Objective: To identify acceptance models and theories and discuss their applicability in the research of acceptance behavior related to software development.Method: We analyzed literature reviews within an interdisciplinary team to identify models and theories relevant to software engineering research. We further discuss acceptance behavior from the human information processing perspective of automatic and affect-driven processes (“fast” system 1 thinking) and rational and rule-governed processes (“slow” system 2 thinking). Results: We identified 30 potentially relevant models and theories. Several of them have been used in researching acceptance behavior in contexts related to software development, but few have been validated in such contexts. They use constructs that capture aspects of (automatic) system 1 and (rational) system 2 oriented processes. However, their operationalizations focus on system 2-oriented processes indicating a rational view of behavior, thus overlooking important psychological processes underpinning behavior. Conclusions: Software engineering research may use acceptance behavior models and theories more extensively to understand and predict practice adoption in the industry. Such theoretical foundations will help improve the impact of software engineering research. However, more consideration should be given to their validation, overlap, construct operationalization, and employed data collection mechanisms when using these models and theories.
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| 8. |
- de Franca, Breno Bernard Nicolau, et al.
(författare)
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The Role of Simulation-Based Studies in Software Engineering Research
- 2020
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Ingår i: Contemporary Empirical Methods in Software Engineering. - Cham : Springer Nature. - 9783030324889 ; , s. 263-287
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Bokkapitel (refereegranskat)abstract
- Several decades ago, inspired by other knowledge areas, simulation was introduced as a research method to Software Engineering. Motivated by potential benefits achieved in other areas, the software engineering community has used simulation-based studies for planning, controlling, and improving software development. However, unclear expectations from simulation-based studies, a lack of methodological support, as well as dispersed knowledge to support model building and calibration have hindered widespread adoption of simulation-based investigations. In this chapter, we delineate the role of simulation in software engineering research and compile processes and guidelines into a comprehensive life cycle. This chapter aims to guide software engineering researchers to conduct effective simulation-based studies in real-world settings.
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| 9. |
- Iftikhar, Umar, et al.
(författare)
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A catalog of source code metrics – a tertiary study
- 2023
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Ingår i: Software Quality. - : Springer. - 9783031314872 - 9783031314889 ; , s. 87-106
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Konferensbidrag (refereegranskat)abstract
- Context: A large number of source code metrics are reported in the literature. It is necessary to systematically collect, describe and classify source code metrics to support research and practice.Objective: We aim to utilize existing secondary studies to develop a cat- alog of source code metrics together with their descriptions. The catalog will also provide information about which units of code (e.g., operators, operands, lines of code, variables, parameters, code blocks, or functions) are used to measure the internal quality attributes and the scope on which they are collected. Method: We conducted a tertiary study to identify secondary studies re- porting source code metrics. We have classified the source code metrics according to the measured internal quality attributes, the units of code used in the measures, and the scope at which the source code metrics are collected. Results: From 711 secondary studies, we identified 52 relevant secondary studies. We reported 423 source code metrics together with their de- scriptions and the internal quality attributes they measure. Source code metrics predominantly incorporate function as a unit of code to measure internal quality attributes. In contrast, several source code metrics use more than one unit of code when measuring internal quality attributes. Nearly 51% of the source code metrics are collected at the class scope, while almost 12% and 15% of source code metrics are collected at module and application levels, respectively. Conclusions: Researchers and practitioners can use the extensive catalog to assess which source code metrics meet their individual needs based on the description and classification scheme presented.
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| 10. |
- Iftikhar, Umar, et al.
(författare)
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A tertiary study on links between source code metrics and external quality attributes
- 2024
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Ingår i: Information and Software Technology. - : Elsevier. - 0950-5849 .- 1873-6025. ; 165
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Forskningsöversikt (refereegranskat)abstract
- Context: Several secondary studies have investigated the relationship between internal quality attributes, source code metrics and external quality attributes. Sometimes they have contradictory results. Objective: We synthesize evidence of the link between internal quality attributes, source code metrics and external quality attributes along with the efficacy of the prediction models used. Method: We conducted a tertiary review to identify, evaluate and synthesize secondary studies. We used several characteristics of secondary studies as indicators for the strength of evidence and considered them when synthesizing the results. Results: From 711 secondary studies, we identified 15 secondary studies that have investigated the link between source code and external quality. Our results show : (1) primarily, the focus has been on object-oriented systems, (2) maintainability and reliability are most often linked to internal quality attributes and source code metrics, with only one secondary study reporting evidence for security, (3) only a small set of complexity, coupling, and size-related source code metrics report a consistent positive link with maintainability and reliability, and (4) group method of data handling (GMDH) based prediction models have performed better than other prediction models for maintainability prediction. Conclusions: Based on our results, lines of code, coupling, complexity and the cohesion metrics from Chidamber & Kemerer (CK) metrics are good indicators of maintainability with consistent evidence from high and moderate-quality secondary studies. Similarly, four CK metrics related to coupling, complexity and cohesion are good indicators of reliability, while inheritance and certain cohesion metrics show no consistent evidence of links to maintainability and reliability. Further empirical studies are needed to explore the link between internal quality attributes, source code metrics and other external quality attributes, including functionality, portability, and usability. The results will help researchers and practitioners understand the body of knowledge on the subject and identify future research directions. © 2023 The Author(s)
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