Veli-Pekka Eloranta

Decision-Centric Architecture Reviews

Recent developments in wearable sensor technologies allow for collecting various information about the person in different conditions. This data is often of limited use without proper interpretation provided by human experts. We propose a practical platform that collects long-term data from multiple body and ambient sensors along with human-provided tagging in practical and mobile conditions. We address the platform requirements of security, privacy, and trustworthiness. Our approach will be tested in a case study focused on stress monitoring at work.

Scrum Anti-Patterns -- An Empirical Study

Wide-spread adoption of the agile movement has rapidly changed the landscape of software industry. In particular, Scrum is an agile process framework that has become extremely popular in industry. However, the practical implementation of Scrum in companies rarely follows the text book ideals. Typically, companies deviate from the proposed Scrum practices for different reasons. While some deviations may be well motivated and reasonable, companies are often tempted to adjust Scrum for the company without clearly understanding the consequences of the deviations. In this paper our aim is to identify ways of potentially harmful mishandling of Scrum in industry based on empirical data collected in a survey. The identified (mal)practices are presented in a semi-formal manner as anti-patterns. The study resulted in 10 anti-patterns that express the context of the deviation, the deviation itself, the broken core principles of Scrum, and the possible consequences of the deviation.

Aligning architecture knowledge management with Scrum

Combining agile project management approaches such as Scrum and software architecture related work has been found problematic. In this paper, we propose several models to align architecture knowledge management with Scrum, based on different architecture work practices in Scrum identified in the industry. The proposed models exploit an architectural knowledge base with a capability to generate architectural documents, and a decision-based architecture evaluation method.

Exploring ScrumBut-An empirical study of Scrum anti-patterns

Companies resort to deviations from Scrum practices, sometimes for sensible reasons.Smaller companies seem to avoid anti-patterns more than larger ones.Companies having more Scrum experience tend to use anti-patterns more.Transformation to agile methods is particularly challenging regarding to testing.Development process should not affect to the customer relationships. The wide-spread adoption of the agile movement has rapidly changed the landscape of software industry. In particular, Scrum is an agile process framework that has become extremely popular in industry. However, the practical implementation of Scrum in companies rarely follows the text book ideals, as companies often deviate from the proposed Scrum practices for various reasons. While some deviations may be well motivated and reasonable, companies can also be tempted to adjust Scrum for the company without clearly understanding the consequences of the deviations. In this paper our aim is to identify ways of potentially harmful mishandling of Scrum in industry based on empirical data collected in semi-structured interviews involving 18 teams in 11 companies. The (mal)practices that were identified at least in three different teams are presented in a semi-formal manner as anti-patterns. The study resulted in 14 anti-patterns that express the context of the deviation, the deviation itself, the broken core principles of Scrum, and the possible consequences of the deviation. In addition, where available, we have included company recommendations regarding the deviations. Furthermore, we identify potential risk areas in Scrum based on an analysis of the relationships between anti-patterns and Scrum concepts.

Chapter 8 – Lightweight Architecture Knowledge Management for Agile Software Development

Architecture knowledge management (AKM) aims to codify and maintain the architectural knowledge of a software system in a form that can be easily accessed by different stakeholders. Integrating AKM with an agile project management paradigm is a challenge because the agile philosophy downplays both plan-driven development and documentation. Yet, by integrating lightweight AKM practices with the process, agile software development could avoid maintenance and communication problems arising from scarce documentation. In this chapter, we introduce existing technologies that could be used as elements of lightweight AKM for agile software development and present possible models to integrate AKM with Scrum, which is the most popular agile approach in use today. In particular, we advocate the exploitation of architectural evaluations to collect architecturally significant information semiautomatically and the use of automated document generation to expose the contents of an architectural information repository in an easily accessible form. The proposed models are based on observed architecting work practices in industry and on interviews carried out in industry to identify the architectural information flow in real-life agile projects.

DCAR - Decision-Centric Architecture Reviews

Recent developments in wearable sensor technologies allow for collecting various information about the person in different conditions. This data is often of limited use without proper interpretation provided by human experts. We propose a practical platform that collects long-term data from multiple body and ambient sensors along with human-provided tagging in practical and mobile conditions. We address the platform requirements of security, privacy, and trustworthiness. Our approach will be tested in a case study focused on stress monitoring at work.

Towards a pattern language for software start-ups

A growing trend in industrial software engineering is that new software products and information services are developed under conditions of notable uncertainty. This is especially visible in startup enterprises which aim at new kinds of products and services in rapidly changing social web, where potential customers can quickly adopt new behavior. Special characteristics of the startups are lack of resources and funds, and start-ups may need to change direction fast. All these affect the software engineering practices used in the start-ups. Unfortunately almost 90 percent of all start-ups fail. There are probably indefinite numbers of reasons why start-ups fail. Failure might be caused by wrongly chosen software engineering practices or inconsiderate decision making. While there is no recipe for success, we argue that good practices that can help on the way to success can be identified from successful start-ups. In this paper, we present three central patterns that could help start-ups to be successful and grow. The three patters presented in the paper are a part of larger set of patterns which was mined from successful start-ups in Finland and Switzerland.

TopDocs: Using Software Architecture Knowledge Base for Generating Topical Documents

A metamodel-based approach is proposed to filter the information in an architectural knowledge base and present that information in a convenient form for a stakeholder, as a dynamically generated just-in-time document targeted for a specific need.

Using domain knowledge to boost software architecture evaluation

Benefits of scenario-based software architecture evaluation such as ATAM are widely recognized. However, full-scale software architecture evaluation is resource and time consuming. In this paper we propose a technique to facilitate the creation of scenarios in a particular domain using a conceptual model especially targeted for architecture evaluation. The technique supports the finding of general, system-independent scenarios and the use of general scenarios in new evaluations. If the model is annotated with a (domain-specific) pattern language, the approach also supports the identification of solutions and the analysis of the architecture. The potential benefits of the technique in terms of semi-automatically produced scenarios are analyzed in the context of an industrial architecture evaluation.

Patterns for Controlling Chaos in a Startup

A growing trend in industrial software engineering is that new software products and information services are developed under conditions of notable uncertainty. This is especially visible in startup enterprises which aim at new kinds of products and services in rapidly changing social web, where potential customers can quickly adopt new behavior. Special characteristics of the startups are lack of resources and funds, and startups may need to change direction fast. All these affect the software engineering practices used in the startups. Unfortunately almost 90 percent of all startups fail and goes bankrupt. There are probably indefinite numbers of reasons why startups fail. Failure might be caused by wrongly chosen software engineering practices or inconsiderate decision making. While there is no recipe for success, we argue that good practices that can help on the way to success can be identified from successful startups. In this paper, we present two patterns that startups can consider when entering the growth phase of the lifecycle.