Sökning: "Technology Debt"
Visar resultat 11 - 15 av 145 uppsatser innehållade orden Technology Debt.
11. Exploring the Swedish Credit Market Ecosystem : A study of loan intermediaries’ contribution to a more efficient consumer credit market
Master-uppsats, KTH/Fastighetsföretagande och finansiella systemSammanfattning : A long period of low interest rates, economic growth and a booming housing market hasresulted in an increase in the debt level of Swedish households. New digital ways of providingfinancial services are changing the traditional banking world and are often praised for beingefficient and inclusive. LÄS MER
12. The Impact of the Recession on Swedish Real Estate Companies : A Study of Financial Strategy and Risk Management of Companies with Different Credit Ratings
Master-uppsats, KTH/Fastighetsföretagande och finansiella systemSammanfattning : The world's economies are in a turbulent phase where rising inflation has hit the global and Swedish economy hard. The Central Bank of Sweden has raised the policy rate expansively in recent months, with the intention of curbing inflation. LÄS MER
13. Konsekvenser av hushållens höga skuldsättning : Bostadslån ur banktjänstemäns perspektiv
Kandidat-uppsats, KTH/Fastighetsföretagande och finansiella systemSammanfattning : Bostadspriserna har stigit markant under de senaste åren och till följd av detta har hushållen varit tvungna att ta på sig stora skulder. Svenska hushåll tar därför ständigt större lån och fler bostadslåntagare uppvisar högre skuldkvot och belåningsgrad än tidigare. LÄS MER
14. Technical Debt in Swedish Tech Startups: Uncovering its Emergence, and Management Processes
Master-uppsats, KTH/Skolan för industriell teknik och management (ITM)Sammanfattning : Technical Debt (TD) is a concept referring to technical deficiencies and sub-optimal decisions made in software development that may save time in the short term but lead to long-term obstacles. The concept also implies increased future costs, often growing with interest, caused by slower development rates and the need for refactorings. LÄS MER
15. MLpylint: Automating the Identification of Machine Learning-Specific Code Smells
Master-uppsats, Blekinge Tekniska Högskola/Institutionen för programvaruteknikSammanfattning : Background. Machine learning (ML) has rapidly grown in popularity, becoming a vital part of many industries. This swift expansion has brought about new challenges to technical debt, maintainability and the general software quality of ML systems. LÄS MER