Discovering the Chimera of (Un)Happiness in Agile Software Development Communities: A Systematic Literature Review

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The manuscript primarily catalogues a significant number of causes and consequences of happiness and unhappiness in Agile teams. However, it does not delve into how these factors interact or influence broader Agile processes, such as team performance or project success. For instance, while “workload imbalance” is identified as a cause of unhappiness, the manuscript does not explore how this might lead to team conflicts or decreased productivity. This lack of deeper analysis limits the theoretical contribution of the study and fails to uncover actionable insights for practitioners. By incorporating techniques such as causal modeling or inferential statistics, the study could provide a clearer picture of the relationships between identified factors and their real-world implications.

Section 4.4 now includes a paragraph describing the main effects and consequences of happiness and unhappiness on organizational culture, processes, social interactions, and software technical quality.

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The study relies on data from existing literature, which inherently limits its applicability across diverse industries and cultural contexts. Agile practices vary widely depending on organizational structure, industry type, and team composition, and these variations are not fully captured in the analysis.

A paragraph has been added to the discussion section highlighting the most relevant aspects of task development by team members when they are geographically distributed and operating in different cultural contexts.

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While the manuscript frequently discusses happiness, unhappiness, and social debt, these terms are not consistently defined, leaving their interpretation open to ambiguity. This lack of clarity creates challenges for both academic readers seeking theoretical precision and practitioners trying to apply the findings. Establishing standardized definitions and providing examples for each concept would greatly enhance the study’s clarity and applicability.

The Introduction now includes the concept of happiness and unhappiness, as well as the importance of positive emotions in individuals, referencing contributions from various authors.

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Although the manuscript acknowledges diversity as a factor, it does not explore its influence in detail, particularly regarding gender dynamics and inclusivity. Gender-related issues, such as unconscious bias or unequal opportunities for leadership, can significantly impact team happiness and cohesion. The bias issue regarding relevant data should be well-addressed.

A paragraph has been included in the discussion section referencing the perspectives of various authors on gender diversity and its positive and negative impact on agile software development teams.

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The authors used the Goal-Question-Metric paradigm to define the research question. What is the difference between the objectives they listed compared to the research questions and the table? What is the OB column in Table 1? I did not see the significance of that column. In fact, there is no OB1.

The GQM approach has three levels: conceptual, operational, and quantitative. This model was adapted to the SLR using GQ, which consists of formulating search objectives and research questions. The search objectives enable a rigorous and detailed review, facilitating the identification, evaluation, and synthesis of existing literature on a specific topic. On the other hand, the research questions help define, organize, and guide the search and analysis of information, focusing on specific aspects of the research problem. The OB column in Table 1 is related to the search objectives (SO). The corresponding adjustment was made to ensure that each formulated question contributes to achieving the established search objectives.

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What is the definition of happiness or unhappiness in the context of this research? Authors need to mention it explicitly in the paper.

The Introduction now includes the concept of happiness and unhappiness, as well as the importance of positive emotions in individuals, referencing contributions from various authors.

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Overall, the text in the tables looks weird, particularly spacing, etc.

All tables were redesigned, adjusting the spacing and adding borders to enhance readability and comprehension.

All tables

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The authors need to explain the data collection process. In other words, how did the authors extract data from the papers? What tools are they using? Also, what data attributes are they extracting and why?

In Section No. 2, the protocol used for the identification, review, and analysis of scientific articles is explained. Likewise, Section 2.3: Inclusion and Exclusion Criteria details the aspects considered for the selection of articles. However, Table No. 5 in the document presents the attributes used for data extraction. Additionally, a paragraph has been added highlighting the importance of the data collection sheet and the reason why the data extraction process is carried out.

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What is “Through a systematic 18 literature review guided by five research questions, 27 primary studies were selected from a total of 1.713 identified.”

The document's writing was reviewed, and the necessary adjustments were made to the abstract, improving its clarity, coherence, and precision to ensure a more concise presentation aligned with the study's objectives.

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What are these numbers cause for what? Do they mean 62 papers or 62 different causes? If they are causes, they need to present them in a taxonomy. “The analysis revealed 188 causes (62 related to happiness and 126 to unhappiness) 20 and 96 consequences (35 related to happiness and 61 to unhappiness).”

In the abstract, the paragraphs were reviewed and adjusted, highlighting the classification of the identified causes and consequences, considering their type: social, procedural, and technical.

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I would like to see the different causes of happiness or unhappiness in a taxonomy after careful data synthesis.

The causes of happiness and unhappiness are organized by type (procedural, technical, and social) in Section 4.3 and are presented in Figure 11, Figure 12, Table 11, and Table 12.

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I would like to see the various consequences for the happiness and unhappiness.

The consequences are presented in Figure 11, Figure 12, Table 14, and Table 15, and are organized by type (social, procedural, and technical).

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I also would like to see what its impacts of happiness or unhappiness on the software are.

A paragraph has been added in Section 4.4 highlighting the negative impact of unhappiness on the technical quality of the software, spanning from requirements specification to implementation.

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he word " Chimera " is not very well used for the software engineering research.

With this title, we aim to convey that happiness and unhappiness among software development team members can become a terrifying entity that, if not properly addressed and managed, leads to consequences and effects that result in social debt within the teams.

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Once an abbreviation is introduced with its full form (e.g., Page 2, line 50: social debt (SD)), it is expected that only the abbreviation is used consistently throughout the text (e.g., Page 2, line 65). The authors are encouraged to carefully review the manuscript for consistency in abbreviation usage.

The term "social debt" has been replaced with its corresponding abbreviation SD, throughout the document.

The entire document

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It would be beneficial to include details of the searching and filtering tools or software employed in the study within Section 2: Materials and Methods, to provide greater clarity on the research process.

 A paragraph was included describing the manual search process carried out in each of the scientific databases.

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The manuscript could be further strengthened by incorporating an analysis of software development fields related to the identified causes, offering a more comprehensive perspective.

 In the discussion, two of the additional possible causes identified were detailed.

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A visual representation of the software development process (both vertical and horizontal) along with a relevant discussion could be added. Including key components related to the major causes would help readers better understand and correlate the analyzed findings of the study.

 Thank you for the recommendation. It will be considered for future studies where the consequences of happiness and unhappiness in each stage of the software development process can be analyzed in more detail. However, in the present study, some aspects have been highlighted in the analysis, design, and coding phases of the software. At this moment, carrying out such a classification would be challenging, as it would require a thorough reorganization of the information. However, we will take this proposal into account for future studies.