It takes three to tango: Requirement, outcome/data, and AI driven development

• Today’s software-intensive organizations are experiencing a paradigm-shift with regards to how to develop software systems. With the increasing availability and access to data and with artificial intelligence (AI) and technologies such as machine learning and deep learning emerging, the traditional requirement driven approach to software development is becoming complemented with other approaches. In addition to having development teams executing on requirements specified by product management, the development of software systems is progressing towards a data driven practice where teams receive an outcome to realize and where design decisions are taken based on continuous collection and analysis of data. On top of this, and due to artificial intelligence components being introduced to more and more software systems, learning algorithms, automatically generated models and data is replacing code and the development process is no longer only a manual effort but instead a combination of human and automated processes. In this paper, and based on multi-case study research in embedded systems and online companies, we see that companies use different approaches to software development but that they often take a requirement driven approach even if they would benefit from one of the other two. Also, we see that picking the wrong approach results in a number of problems such as e.g. inefficiency and waste of development efforts. To help address these problems, we develop a holistic development framework and we provide guidelines on how to improve effectiveness in development. The contribution of this paper is two-fold. First, we identify that there are three distinct approaches to software development; (1) Requirement driven development, (2) Outcome/data driven development and (3) AI driven development and we outline the typical problems that companies experience when using the wrong approach for the wrong purpose. Second, we provide a holistic framework with guidelines for when to use what approach to software development.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Programvaruteknik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Software Engineering (hsv//eng)

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

SAMHÄLLSVETENSKAP  -- Medie- och kommunikationsvetenskap -- Systemvetenskap, informationssystem och informatik med samhällsvetenskaplig inriktning (hsv//swe)

SOCIAL SCIENCES  -- Media and Communications -- Information Systems, Social aspects (hsv//eng)

Nyckelord

Outcome/data driven development

Requirement driven development

AI driven development

Holistic development framework

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