Software Engineering Radio - the podcast for professional software developers

Rishi Singh, founder and CEO at Sapient.ai, speaks with SE radio's Kanchan Shringi about using generative AI to help developers automate test code generation. They start by identifying key problems that developers are looking for in an automated test-generation solution. The discussion explores the capabilities and limitations of today's large language models in achieving that goal, and then delves into how Sapient.ai has built wrappers around LLMs in an effort to improve the quality of the generated tests. Rishi also suggests how to validate the generated tests and outlines his vision of the future for this rapidly evolving area. Brought to you by IEEE Computer Society and IEEE Software magazine. This episode is sponsored by WorkOS.

Nicolas Carlo talks with host Sam Taggart about Nicolas's recent book, Legacy Code First Aid Kit. They start by defining legacy code and the general issues that developers face when dealing with it. Nicolas describes some of the tools in his book and provides examples of where he has found them useful. The episode also touches briefly on the role of AI and some other tools Nicolas has discovered since writing the book. This episode sponsored by WorkOS.

Han Yuan, an accomplished Chief Product and Technology Officer, joins host Priyanka Raghavan to discuss reorganizations. The conversation starts with a broad discussion of reorganizations and reasons that companies choose to undertake them. They then consider organizational behavior and topics such as Conway's law and the theory of constraints. Han offers some advice on key steps to take when planning for a reorg, including how software teams could organize themselves based on technology, frameworks, or user journeys. The episode ends with some discussion of metrics and lessons learned. Brought to you by IEEE Computer Society and IEEE Software magazine.

William Morgan, founder of the Linkerd service mesh and CEO of Bouyant, joins SE Radio's Robert Blumen for a discussion of sidecars, service mesh, and a forthcoming enhancement to kubernetes to support sidecars natively. The conversation explores the origin of sidecars, sidecars and service mesh, and migrating service mesh to kubernetes. They take a deep dive into some aspects of running service mesh on kubernetes, the difficulties in running a sidecar container in a pod, and Kubernetes Enhancement Proposal (KEP) 753, which is intended to provide better native support for sidecar containers. William also gives some thoughts on the continuing relevance of service mesh.

Jason C. McDonald, author of the book Dead Simple Python, speaks with host Samuel Taggart about leveraging quantified tasks to improve estimation, particularly across projects. They discuss the origin of the concept and its relationship with story points, and Jason offers examples to show how quantified tasks can capture nuances in software tasks that are often lost with story points. He also points to the ability to compare them across projects as a major advantage of quantified tasks. Among other topics, they consider also how to use quantified tasks to analyze the stability of a codebase. Brought to you by IEEE Computer Society and IEEE Software magazine.

Jonathan Crossland, software architect, author, and business owner, joins host Jeff Doolittle for a conversation about the AMMERSE framework of design principles. They start by discussing the agile manifesto as a statement of values, and Jonathan shares his perspective based on his experience as a software developer and business owner. They then explore the three layers of the AMMERSE framework and how they help business and engineering leaders to align their values, thereby improving their ability to collaborate and reach common goals. Brought to you by IEEE Computer Society and IEEE Software magazine.

Coral Calero Muñoz and Felix Garcia, professors at the University of Castilla-La Mancha, speak with host Giovanni Asproni about green and sustainable software—an approach to software development aimed at creating software systems that consume less energy and produce less CO2 during their entire lifetimes with minimal impact on their functionality and other qualities. The episode starts by describing why green software matters, particularly in the context of global warming, and introducing the key concepts. Continues discussing the current status of the field, in both academia and industry, and finishes with hints and tips that can be readily applied by development teams to make their systems greener. Brought to you by IEEE Computer Society and IEEE Software magazine.

Maxim Fateev, the CEO of Temporal, speaks with SE Radio's Philip Winston about how Temporal implements durable execution. They explore concepts including workflows, activities, timers, event histories, signals, and queries. Maxim also compares deployment using self-hosted clusters or the Temporal Cloud.

Llewelyn Falco, creator approval tests, talks with SE Radio host Sam Taggart about testing code in general and the various types of testing that developers perform. Llewelyn elaborates on how approval tests can help test code at a higher level than traditional unit tests. They also discuss using approval tests to help get legacy code under test. This episode sponsored by Data Annotation.

Sean Moriarity, creator of the Axon deep learning framework, co-creator of the Nx library, and author of Machine Learning in Elixir and Genetic Algorithms in Elixir, published by the Pragmatic Bookshelf, speaks with SE Radio host Gavin Henry about what deep learning (neural networks) means today. Using a practical example with deep learning for fraud detection, they explore what Axon is and why it was created. Moriarity describes why the Beam is ideal for machine learning, and why he dislikes the term "neural network." They discuss the need for deep learning, its history, how it offers a good fit for many of today's complex problems, where it shines and when not to use it. Moriarity goes into depth on a range of topics, including how to get datasets in shape, supervised and unsupervised learning, feed-forward neural networks, Nx.serving, decision trees, gradient descent, linear regression, logistic regression, support vector machines, and random forests. The episode considers what a model looks like, what training is, labeling, classification, regression tasks, hardware resources needed, EXGBoost, Jax, PyIgnite, and Explorer. Finally, they look at what's involved in the ongoing lifecycle or operational side of Axon once a workflow is put into production, so you can safely back it all up and feed in new data. Brought to you by IEEE Computer Society and IEEE Software magazine. This episode sponsored by Miro.