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Sustainability Competencies and Skills in Software Engineering: An Industry Perspective

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arxiv 2305.00436 v2 pith:3YBKAWNV submitted 2023-04-30 cs.SE

classification cs.SE
keywords sustainabilityskillssoftwarecompetenciesgoalsdevelopmentsystemstraining
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Achieving the UN Sustainable Development Goals (SDGs) demands adequate levels of awareness and actions to address sustainability challenges. Software systems will play an important role in moving towards these targets. Sustainability skills are necessary to support the development of software systems and to provide sustainable IT-supported services for citizens. While there is a growing number of academic bodies, including sustainability education in engineering and computer science curricula, there is not yet comprehensive research on the competencies and skills required by IT professionals to develop such systems. This study aims to identify the industrial sustainability needs for education and training from software engineers' perspective. We conducted interviews and focus groups with experts from twenty-eight organisations with an IT division from nine countries to understand their interests, goals and achievements related to sustainability, and the skills and competencies needed to achieve their goals. Our findings show that organisations are interested in sustainability, both idealistically and increasingly for core business reasons. They seek to improve the sustainability of processes and products but encounter difficulties, like the trade-off between short-term financial profitability and long-term sustainability goals. To fill the gaps, they have promoted in-house training courses, collaborated with universities, and sent employees to external training. The acquired competencies make sustainability an integral part of software development. We conclude that educational programs should include knowledge and skills on core sustainability concepts, system thinking, soft skills, technical sustainability, sustainability impact and measurements, values and ethics, standards and legal aspects, and advocacy and lobbying.

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    Practitioners in AI software development report that ethical guidelines are rarely operationalized, and decision-making is driven more by personal values and organizational culture than by formal frameworks.

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