May 2016· International Conference on Agile Software Development· pp. 169-182· 62 citations· ⚡ 6 influential· 11 references
Computer Science
TL;DR
It is found that what perceived as biggest challenges by software startups do vary across different life cycle stages, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature.
Abstract
Software startups are challenging endeavours, with various road blocks on their path to success. The current understanding of the challenges that software startups may encounter is very limited. In this paper, we use the research framework of learning and product development stages to analyse the key challenges that software startups have to deal with at different life cycle stages, from problem definition to solution validation and from concept to mature product. Based on an analysis of the empirical data collected by a large survey of 4100 startups, we find out that what perceived as biggest challenges by software startups do vary across different life cycle stages. Building product is the biggest obstacle for software startups, even though its significance decreases when the learning focuses of the startups move from problem to solution and their products mature. Business related challenges such as customer acquisition and scaling are more noticeable at the later stages. Our study raises the awareness of these challenges and suggests to tackle right challenges at the right time.
This publication proposes a definition and a classification of agile software development approaches and analyses ten software development methods that can be characterized as being "agile" against the defined criterion.
P. Abrahamsson, O. Salo, Jussi Ronkainen et al.· arXiv.org· 727 citations· ⚡54
The study shows that agile practices improve both informal and formal communication, but indicates that, in larger development situations involving multiple external stakeholders, a mismatch of adequate communication mechanisms can sometimes even hinder the communication.
M. Pikkarainen, Jukka Haikara, O. Salo et al.· Empirical Software Engineeri...· 401 citations· ⚡48
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.
Nicolò Paternoster, Carmine Giardino, M. Unterkalmsteiner et al.· Information and Software Tec...· 394 citations· ⚡54
The possibility of inferring high-dimensional data inference in a model that consists of a prior and an auxiliary differentiable constraint given some additional information is considered, thereby allowing a range of potential applications in adapting models to new domains and tasks.
Alexandros Graikos, Esmeralda S. Whitammer, N. Jojic et al.· Neural Information Processin...· 316 citations· ⚡15
It is proved that any global minimizer of the trajectory balance objective can define a policy that samples exactly from the target distribution, and empirically demonstrate the benefits of the trajectories balance objective for GFlowNet convergence, diversity of generated samples, and robustness to long action sequences and large action spaces.
Esmeralda S. Whitammer, Moksh Jain, Emmanuel Bengio et al.· Neural Information Processin...· 302 citations· ⚡60
Related blog posts
MIT News · Artificial Intelligence· news.mit.eduAug 3, 2026
A weeklong summer workshop brought higher education faculty to campus to explore how AI and machine learning materials can be adapted for their classrooms.