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Tony Gorschek

Publications and source records attributed to Tony Gorschek.

At least 37 records · Page 2Linked to original sources
arXiv2023

Exploration of technical debt in start-ups

Context: Software start-ups are young companies aiming to build and market software-intensive products fast with little resources. Aiming to accelerate time-to-market, start-ups often opt for ad-hoc engineering practices, make shortcuts in product engineering, and accumulate technical debt. Objective: In this paper we explore to what extent precedents, dimensions and outcomes associated with technical debt are prevalent in start-ups. Method: We apply a case survey method to identify aspects of technical debt and contextual information characterizing the engineering context in start-ups. Results: By analyzing responses from 86 start-up cases we found that start-ups accumulate most technical debt in the testing dimension, despite attempts to automate testing. Furthermore, we found that start-up team size and experience is a leading precedent for accumulating technical debt: larger teams face more challenges in keeping the debt under control. Conclusions: This study highlights the necessity to monitor levels of technical debt and to preemptively introduce practices to keep the debt under control. Adding more people to an already difficult to maintain product could amplify other precedents, such as resource shortages, communication issues and negatively affect decisions pertaining to the use of good engineering practices.

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arXiv2023

Which Requirements Artifact Quality Defects are Automatically Detectable? A Case Study

[Context] The quality of requirements engineering artifacts, e.g. requirements specifications, is acknowledged to be an important success factor for projects. Therefore, many companies spend significant amounts of money to control the quality of their RE artifacts. To reduce spending and improve the RE artifact quality, methods were proposed that combine manual quality control, i.e. reviews, with automated approaches. [Problem] So far, we have seen various approaches to automatically detect certain aspects in RE artifacts. However, we still lack an overview what can and cannot be automatically detected. [Approach] Starting from an industry guideline for RE artifacts, we classify 166 existing rules for RE artifacts along various categories to discuss the share and the characteristics of those rules that can be automated. For those rules, that cannot be automated, we discuss the main reasons. [Contribution] We estimate that 53% of the 166 rules can be checked automatically either perfectly or with a good heuristic. Most rules need only simple techniques for checking. The main reason why some rules resist automation is due to imprecise definition. [Impact] By giving first estimates and analyses of automatically detectable and not automatically detectable rule violations, we aim to provide an overview of the potential of automated methods in requirements quality control.

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arXiv2023

Requirements Quality Assurance in Industry: Why, What and How?

Context and Motivation: Natural language is the most common form to specify requirements in industry. The quality of the specification depends on the capability of the writer to formulate requirements aimed at different stakeholders: they are an expression of the customer's needs that are used by analysts, designers and testers. Given this central role of requirements as a mean to communicate intention, assuring their quality is essential to reduce misunderstandings that lead to potential waste. Problem: Quality assurance of requirement specifications is largely a manual effort that requires expertise and domain knowledge. However, this demanding cognitive process is also congested by trivial quality issues that should not occur in the first place. Principal ideas: We propose a taxonomy of requirements quality assurance complexity that characterizes cognitive load of verifying a quality aspect from the human perspective, and automation complexity and accuracy from the machine perspective. Contribution: Once this taxonomy is realized and validated, it can serve as the basis for a decision framework of automated requirements quality assurance support.

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arXiv2023

Software Startups -- A Research Agenda

Software startup companies develop innovative, software-intensive products within limited time frames and with few resources, searching for sustainable and scalable business models. Software startups are quite distinct from traditional mature software companies, but also from micro-, small-, and medium-sized enterprises, introducing new challenges relevant for software engineering research. This paper's research agenda focuses on software engineering in startups, identifying, in particular, 70+ research questions in the areas of supporting startup engineering activities, startup evolution models and patterns, ecosystems and innovation hubs, human aspects in software startups, applying startup concepts in non-startup environments, and methodologies and theories for startup research. We connect and motivate this research agenda with past studies in software startup research, while pointing out possible future directions. While all authors of this research agenda have their main background in Software Engineering or Computer Science, their interest in software startups broadens the perspective to the challenges, but also to the opportunities that emerge from multi-disciplinary research. Our audience is therefore primarily software engineering researchers, even though we aim at stimulating collaborations and research that crosses disciplinary boundaries. We believe that with this research agenda we cover a wide spectrum of the software startup industry current needs.

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arXiv2023

Large-scale information retrieval in software engineering -- an experience report from industrial application

Software Engineering activities are information intensive. Research proposes Information Retrieval (IR) techniques to support engineers in their daily tasks, such as establishing and maintaining traceability links, fault identification, and software maintenance. We describe an engineering task, test case selection, and illustrate our problem analysis and solution discovery process. The objective of the study is to gain an understanding of to what extent IR techniques (one potential solution) can be applied to test case selection and provide decision support in a large-scale, industrial setting. We analyze, in the context of the studied company, how test case selection is performed and design a series of experiments evaluating the performance of different IR techniques. Each experiment provides lessons learned from implementation, execution, and results, feeding to its successor. The three experiments led to the following observations: 1) there is a lack of research on scalable parameter optimization of IR techniques for software engineering problems; 2) scaling IR techniques to industry data is challenging, in particular for latent semantic analysis; 3) the IR context poses constraints on the empirical evaluation of IR techniques, requiring more research on developing valid statistical approaches. We believe that our experiences in conducting a series of IR experiments with industry grade data are valuable for peer researchers so that they can avoid the pitfalls that we have encountered. Furthermore, we identified challenges that need to be addressed in order to bridge the gap between laboratory IR experiments and real applications of IR in the industry.

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arXiv2023

Software Development in Startup Companies: The Greenfield Startup Model

Software startups are newly created companies with no operating history and oriented towards producing cutting-edge products. However, despite the increasing importance of startups in the economy, few scientific studies attempt to address software engineering issues, especially for early-stage startups. If anything, startups need engineering practices of the same level or better than those of larger companies, as their time and resources are more scarce, and one failed project can put them out of business. In this study we aim to improve understanding of the software development strategies employed by startups. We performed this state-of-practice investigation using a grounded theory approach. We packaged the results in the Greenfield Startup Model (GSM), which explains the priority of startups to release the product as quickly as possible. This strategy allows startups to verify product and market fit, and to adjust the product trajectory according to early collected user feedback. The need to shorten time-to-market, by speeding up the development through low-precision engineering activities, is counterbalanced by the need to restructure the product before targeting further growth. The resulting implications of the GSM outline challenges and gaps, pointing out opportunities for future research to develop and validate engineering practices in the startup context.

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arXiv2023

Assessing requirements engineering and software test alignment -- Five case studies

The development of large, software-intensive systems is a complex undertaking that we generally tackle by a divide and conquer strategy. Companies thereby face the challenge of coordinating individual aspects of software development, in particular between requirements engineering (RE) and software testing (ST). A lack of REST alignment can not only lead to wasted effort but also to defective software. However, before a company can improve the mechanisms of coordination they need to be understood first. With REST-bench we aim at providing an assessment tool that illustrates the coordination in software development projects and identify concrete improvement opportunities. We have developed REST-bench on the sound fundamentals of a taxonomy on REST alignment methods and validated the method in five case studies. Following the principles of technical action research, we collaborated with five companies, applying REST-bench and iteratively improving the method based on the lessons we learned. We applied REST-bench both in Agile and plan-driven environments, in projects lasting from weeks to years, and staffed as large as 1000 employees. The improvement opportunities we identified and the feedback we received indicate that the assessment was effective and efficient. Furthermore, participants confirmed that their understanding on the coordination between RE and ST improved.

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arXiv2023

An Industrial Case Study on Test Cases as Requirements

It is a conundrum that agile projects can succeed 'without requirements' when weak requirements engineering is a known cause for project failures. While Agile development projects often manage well without extensive requirements documentation, test cases are commonly used as requirements. We have investigated this agile practice at three companies in order to understand how test cases can fill the role of requirements. We performed a case study based on twelve interviews performed in a previous study. The findings include a range of benefits and challenges in using test cases for eliciting, validating, verifying, tracing and managing requirements. In addition, we identified three scenarios for applying the practice, namely as a mature practice, as a de facto practice and as part of an agile transition. The findings provide insights into how the role of requirements may be met in agile development including challenges to consider.

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arXiv2023

A conceptual framework for SPI evaluation

Software Process Improvement (SPI) encompasses the analysis and modification of the processes within software development, aimed at improving key areas that contribute to the organizations' goals. The task of evaluating whether the selected improvement path meets these goals is challenging. On the basis of the results of a systematic literature review on SPI measurement and evaluation practices, we developed a framework (SPI Measurement and Evaluation Framework (SPI-MEF)) that supports the planning and implementation of SPI evaluations. SPI-MEF guides the practitioner in scoping the evaluation, determining measures, and performing the assessment. SPI-MEF does not assume a specific approach to process improvement and can be integrated in existing measurement programs, refocusing the assessment on evaluating the improvement initiative's outcome. Sixteen industry and academic experts evaluated the framework's usability and capability to support practitioners, providing additional insights that were integrated in the application guidelines of the framework.

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arXiv2023

Challenges and Practices in Aligning Requirements with Verification and Validation: A Case Study of Six Companies

Weak alignment of requirements engineering (RE) with verification and validation (VV) may lead to problems in delivering the required products in time with the right quality. For example, weak communication of requirements changes to testers may result in lack of verification of new requirements and incorrect verification of old invalid requirements, leading to software quality problems, wasted effort and delays. However, despite the serious implications of weak alignment research and practice both tend to focus on one or the other of RE or VV rather than on the alignment of the two. We have performed a multi-unit case study to gain insight into issues around aligning RE and VV by interviewing 30 practitioners from 6 software developing companies, involving 10 researchers in a flexible research process for case studies. The results describe current industry challenges and practices in aligning RE with VV, ranging from quality of the individual RE and VV activities, through tracing and tools, to change control and sharing a common understanding at strategy, goal and design level. The study identified that human aspects are central, i.e. cooperation and communication, and that requirements engineering practices are a critical basis for alignment. Further, the size of an organisation and its motivation for applying alignment practices, e.g. external enforcement of traceability, are variation factors that play a key role in achieving alignment. Our results provide a strategic roadmap for practitioners improvement work to address alignment challenges. Furthermore, the study provides a foundation for continued research to improve the alignment of RE with VV.

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arXiv2023

Software development in startup companies: A systematic mapping study

Context: Software startups are newly created companies with no operating history and fast in producing cutting-edge technologies. These companies develop software under highly uncertain conditions, tackling fast-growing markets under severe lack of resources. Therefore, software startups present an unique combination of characteristics which pose several challenges to software development activities. Objective: This study aims to structure and analyze the literature on software development in startup companies, determining thereby the potential for technology transfer and identifying software development work practices reported by practitioners and researchers. Method: We conducted a systematic mapping study, developing a classification schema, ranking the selected primary studies according their rigor and relevance, and analyzing reported software development work practices in startups. Results: A total of 43 primary studies were identified and mapped, synthesizing the available evidence on software development in startups. Only 16 studies are entirely dedicated to software development in startups, of which 10 result in a weak contribution (advice and implications (6); lesson learned (3); tool (1)). Nineteen studies focus on managerial and organizational factors. Moreover, only 9 studies exhibit high scientific rigor and relevance. From the reviewed primary studies, 213 software engineering work practices were extracted, categorized and analyzed. Conclusion: This mapping study provides the first systematic exploration of the state-of-art on software startup research. The existing body of knowledge is limited to a few high quality studies. Furthermore, the results indicate that software engineering work practices are chosen opportunistically, adapted and configured to provide value under the constrains imposed by the startup context.

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arXiv2023

What do we know about software development in startups?

An impressive number of new startups are launched every day as a result of growing new markets, accessible technologies, and venture capital. New ventures such as Facebook, Supercell, Linkedin, Spotify, {WhatsApp}, and Dropbox, to name a few, are good examples of startups that evolved into successful businesses. However, despite many successful stories, the great majority of them fail prematurely. Operating in a chaotic and rapidly evolving domain conveys new uncharted challenges for startuppers. In this study, the authors characterize their context and identify common software development startup practices.

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arXiv2023

Evaluation and Measurement of Software Process Improvement -- A Systematic Literature Review

BACKGROUND: Software Process Improvement (SPI) is a systematic approach to increase the efficiency and effectiveness of a software development organization and to enhance software products. OBJECTIVE: This paper aims to identify and characterize evaluation strategies and measurements used to assess the impact of different SPI initiatives. METHOD: The systematic literature review includes 148 papers published between 1991 and 2008. The selected papers were classified according to SPI initiative, applied evaluation strategies, and measurement perspectives. Potential confounding factors interfering with the evaluation of the improvement effort were assessed. RESULTS: Seven distinct evaluation strategies were identified, wherein the most common one, "Pre-Post Comparison" was applied in 49 percent of the inspected papers. Quality was the most measured attribute (62 percent), followed by Cost (41 percent), and Schedule (18 percent). Looking at measurement perspectives, "Project" represents the majority with 66 percent. CONCLUSION: The evaluation validity of SPI initiatives is challenged by the scarce consideration of potential confounding factors, particularly given that "Pre-Post Comparison" was identified as the most common evaluation strategy, and the inaccurate descriptions of the evaluation context. Measurements to assess the short and mid-term impact of SPI initiatives prevail, whereas long-term measurements in terms of customer satisfaction and return on investment tend to be less used.

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arXiv2023

A Taxonomy for Requirements Engineering and Software Test Alignment

Requirements Engineering and Software Testing are mature areas and have seen a lot of research. Nevertheless, their interactions have been sparsely explored beyond the concept of traceability. To fill this gap, we propose a definition of requirements engineering and software test (REST) alignment, a taxonomy that characterizes the methods linking the respective areas, and a process to assess alignment. The taxonomy can support researchers to identify new opportunities for investigation, as well as practitioners to compare alignment methods and evaluate alignment, or lack thereof. We constructed the REST taxonomy by analyzing alignment methods published in literature, iteratively validating the emerging dimensions. The resulting concept of an information dyad characterizes the exchange of information required for any alignment to take place. We demonstrate use of the taxonomy by applying it on five in-depth cases and illustrate angles of analysis on a set of thirteen alignment methods. In addition, we developed an assessment framework (REST-bench), applied it in an industrial assessment, and showed that it, with a low effort, can identify opportunities to improve REST alignment. Although we expect that the taxonomy can be further refined, we believe that the information dyad is a valid and useful construct to understand alignment.

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arXiv2023

Challenges in aligning requirements engineering and verification in a large-scale industrial context

[Context and motivation] When developing software, coordination between different organizational units is essential in order to develop a good quality product, on time and within budget. Particularly, the synchronization between requirements and verification processes is crucial in order to assure that the developed software product satisfies customer requirements. [Question/problem] Our research question is: what are the current challenges in aligning the requirements and verification processes? [Principal ideas/results] We conducted an interview study at a large software development company. This paper presents preliminary findings of these interviews that identify key challenges in aligning requirements and verification processes. [Contribution] The result of this study includes a range of challenges faced by the studied organization grouped into the categories: organization and processes, people, tools, requirements process, testing process, change management, traceability, and measurement. The findings of this study can be used by practitioners as a basis for investigating alignment in their organizations, and by scientists in developing approaches for more efficient and effective management of the alignment between requirements and verification.

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arXiv2023

Connecting the Dots of Knowledge in Agile Software Development

This article discusses the importance of managing knowledge as a resource due to its great potential to create economic value. We detail the types of knowledge resources, the challenges associated with their management, and potential solutions to maximise their utility. Our contribution is based on empirical studies performed in an industry context.

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arXiv2023

Preliminary Guideline for Creating Boundary Artefacts in Software Engineering

Context: Software development benefits from having Boundary Artefacts (BAs), as a single artefact can supply stakeholders with different boundaries, facilitating collaboration among social worlds. When those artefacts display inconsistencies, such as incorrect information, the practitioners have decreased trust in the BA. As trust is an essential factor guiding the utilisation of BAs in software projects, it is necessary to understand which principles should be observed when creating them. Objective: This study aimed at develop and validate a preliminary guideline support the creation of trustworthy BAs. Method: We followed a multi-step approach. We developed our guideline through a literature review and previous results from our case study. Second, we submitted the guideline for an expert evaluation via two workshops and a survey. At last, we adjusted our guideline by incorporating the feedback obtained during the workshops. Results: We grouped the principles collected from a literature review into three categories. The first category (Scope) focuses on the scope, displaying principles referring to defining each boundary's target audience, needs, and terminology. The second category (Structure) relates to how the artefact's content is structured to meet stakeholders' needs. The third (Management) refers to principles that can guide the establishment of practices to manage the artefact throughout time. The expert validation revealed that the principles contribute to creating trustworthy BAs at different levels. Also, the relevance of the guideline and its usefulness. Conclusions: The guideline strengthen BA traits such as shared understanding, plasticity and ability to transfer. Practitioners can utilise the guideline to guide the creation or even evaluate current practices for existing BAs.

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arXiv2022

A Taxonomy of Assets for the Development of Software-Intensive Products and Services

Context: Developing software-intensive products or services usually involves a plethora of software artefacts. Assets are artefacts intended to be used more than once and have value for organisations; examples include test cases, code, requirements, and documentation. During the development process, assets might degrade, affecting the effectiveness and efficiency of the development process. Therefore, assets are an investment that requires continuous management. Identifying assets is the first step for their effective management. However, there is a lack of awareness of what assets and types of assets are common in software-developing organisations. Most types of assets are understudied, and their state of quality and how they degrade over time have not been well-understood. Method: We perform a systematic literature review and a field study at five companies to study and identify assets to fill the gap in research. The results were analysed qualitatively and summarised in a taxonomy. Results: We create the first comprehensive, structured, yet extendable taxonomy of assets, containing 57 types of assets. Conclusions: The taxonomy serves as a foundation for identifying assets that are relevant for an organisation and enables the study of asset management and asset degradation concepts.

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