Agile programming – Introduction and current legal challenges

Hoeren, Thomas; Pinelli, Stefan

doi:10.1016/j.clsr.2018.04.004

Cited by 5 publications

(4 citation statements)

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“…Unfortunately, in this case, agile developers require further training about developing secure software [19] where security practices are often neglected in favour of functional requirements. This argument was supported by Wayrynen et al [33], Hoeren [38], and Alnatheer et al [39].…”

Section: D)mentioning

confidence: 63%

“…Security assurance challenges ASD methods support the use of light documentations and hence resulting in conflicts with the use of documentation for security assessment, claimed by Beznosov and Kruchten [37], Hoeren [38], and Alnatheer et. al.…”

Section: C)mentioning

confidence: 99%

“…Security management challenges The relationship between a security in a software and its products' cost are directly proportional due to an increased development effort [39]. Additionally, organizations also neglect security activities to accelerate the release scheduling and to support this, it was reported that no incentives were given for organizations to develop security features in the early increments, claimed by Bartsch [19] and Hoeren et al [38].…”

Section: E)mentioning

confidence: 99%

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Secure Software Development Best Practices

Fauzi,

Mohan,

et al. 2023

IJEMD-CSAI

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This research aims to explore optimal strategies for fortified software, enhancing the implementation of secure software development practices. Software security involves crafting and designing software that guarantees the integrity, confidentiality, and availability of its code, data, and functionalities. Often, in prioritizing functionality, security takes a back seat when organizations embark on system development. Yet, it's imperative to embed security at every phase of the Software Development Life Cycle (SDLC). Numerous methodologies and models exist for addressing software security, but only a few substantiate creating secure software applications effectively. Despite advancements, software security remains inadequately addressed, posing a challenge to integrating security protocols into the SDLC seamlessly. This review advocates specific security measures to be integrated at each SDLC level, fostering a secure SDLC. Efficient amalgamation of these processes ensures the delivery of secure software systems with minimized resource expenditure. Additionally, it highlights hurdles encountered in employing agile development methodologies for crafting secure software. These challenges stem from assessing agile ideals, principles, and security assurance procedures. These findings underscore the urgency for research facilitating safe software development, addressing barriers inhibiting its adoption. The paper serves as a valuable reference, shedding light on the significance of establishing secure software development processes.

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Section: D)mentioning

confidence: 63%

Section: C)mentioning

confidence: 99%

Section: E)mentioning

confidence: 99%

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Secure Software Development Best Practices

Fauzi,

Mohan,

et al. 2023

IJEMD-CSAI

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“…In practice, activities to create an intangible asset might not be so easily distinguished and classified into either research or development (KPMG, 2020) and usage. Such sequential processes, based on old, linear thinking, will hardly have any significance for data in an agile business world (Hoeren and Pinelli, 2018). As shown in the data value chain, AI-powered information might be in a constant state of change, as new data will constantly refine and update itself with the help of self-learning, deep-state AI-powered algorithms; this will lead to a constant shifting between the planning, research and development, and usage phases.…”

Section: Jaar 242mentioning

confidence: 99%

AI-powered information and Big Data: current regulations and ways forward in IFRS reporting

Leitner-Hanetseder

Lehner²

2022

JAAR

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PurposeWith the help of “self-learning” algorithms and high computing power, companies are transforming Big Data into artificial intelligence (AI)-powered information and gaining economic benefits. AI-powered information and Big Data (simply data henceforth) have quickly become some of the most important strategic resources in the global economy. However, their value is not (yet) formally recognized in financial statements, which leads to a growing gap between book and market values and thus limited decision usefulness of the underlying financial statements. The objective of this paper is to identify ways in which the value of data can be reported to improve decision usefulness.Design/methodology/approachBased on the authors' experience as both long-term practitioners and theoretical accounting scholars, the authors conceptualize and draw up a potential data value chain and show the transformation from raw Big Data to business-relevant AI-powered information during its process.FindingsAnalyzing current International Financial Reporting Standards (IFRS) regulations and their applicability, the authors show that current regulations are insufficient to provide useful information on the value of data. Following this, the authors propose a Framework for AI-powered Information and Big Data (FAIIBD) Reporting. This framework also provides insights on the (good) governance of data with the purpose of increasing decision usefulness and connecting to existing frameworks even further. In the conclusion, the authors raise questions concerning this framework that may be worthy of discussion in the scholarly community.Research limitations/implicationsScholars and practitioners alike are invited to follow up on the conceptual framework from many perspectives.Practical implicationsThe framework can serve as a guide towards a better understanding of how to recognize and report AI-powered information and by that (a) limit the valuation gap between book and market value and (b) enhance decision usefulness of financial reporting.Originality/valueThis article proposes a conceptual framework in IFRS to regulators to better deal with the value of AI-powered information and improve the good governance of (Big)data.

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