ICALEPCS2023 - List of Authors (Giani, E.)

Paper	Title	Page
MO2BCO03	Strategy and Tools to Test Software in the SKA Project: The CSP. LMC Case	34
	G. Marotta, C. Baffa, E. Giani INAF - OA Arcetri, Firenze, Italy G. Brajnik IDS, Udine, Italy M. Colciago, I. Novak Cosylab Switzerland, Brugg, Switzerland
	The Square Kilometre Array (SKA) Telescope will be one of the largest and most complex scientific instruments ever built. The development of a reliable software for monitoring and controlling its operations is critical to the success of the entire SKA project. The Local Monitoring and Control of the Central Signal Processor (CSP. LMC) is a software responsible for controlling a key subsystem of the telescope, i.e. the Central Signal Processor (CSP). The software is implemented as a "device" within the TANGO framework, written in Python. In this paper we describe a testing strategy that addresses some typical problems of such a large and complex instrument. It is a multi-level strategy, based on a combination of automated tests (unit/component/integration), in the context of CI/CD practices. Software is also tested against errors and anomalous conditions that can occur while the CSP. LMC is interacting with external subsystems, which can be simulated. The paper also discusses needs and solutions based on data mining test results. This allows us to obtain statistics of unexpected failures and to investigate their causes. Furthermore, a database containing test results supports discovery of interesting and unexpected patterns of behaviors of the tests based on correlations about different test-related events and data. This helps us to develop a deeper understanding of the code’s functioning and to find suitable solutions to minimize unexpected behaviors. In addition it can be used also to support reliability testing.
	Slides MO2BCO03 [2.336 MB]
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO2BCO03
About •	Received ※ 06 October 2023 — Revised ※ 08 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 13 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

FR2BCO02	A Lean UX Approach for Developing Effective Monitoring and Control User Interfaces: A Case Study for the SKA CSP. LMC Subsystem	1650
	V. Alberti INAF-OAT, Trieste, Italy C. Baffa, E. Giani, G. Marotta INAF - OA Arcetri, Firenze, Italy G. Brajnik IDS, Udine, Italy M. Colciago, I. Novak Cosylab Switzerland, Brugg, Switzerland
	The Central Signal Processor Local Monitor and Control (CSP. LMC) is a software component that allows the flow of information and commands between the Telescope Manager (TM) and the subsystems dedicated to signal processing, namely the correlator and beamformer, the pulsar search and the pulsar timing engines. It acts as an adapter by specialising the commands and associated data from the TM to the subsystems and by exposing the subsystems as a unified entity while monitoring their status. In this paper, we approach the problem of creating a User Interface (UI) for such a component. Through a series of short learning cycles, we want to explore different ways of looking at the system and build an initial set of UIs that can be refined to be used as engineering UIs in the first Array Assembly of the Square Kilometre Array. The process heavily involves some of the developers of the CSP. LMC in creating the dashboards, and other ones as participants in informal evaluations. In fact, the opportunities offered by Taranta, a tool to develop web UIs without needing web-development skills, make it possible to quickly realise a working dashboard that can be promptly tested. This also supports the short feedback cycle advocated by a Lean UX approach and maps well in a bi-weekly sprint cadence. In this paper, we will describe the method and present the results highlighting strengths and pain points where faced.
DOI •	reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-FR2BCO02
About •	Received ※ 06 October 2023 — Revised ※ 20 November 2023 — Accepted ※ 05 December 2023 — Issued ※ 13 December 2023
Cite •	reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

Paper

Title

Page

Strategy and Tools to Test Software in the SKA Project: The CSP. LMC Case

34

G. Marotta, C. Baffa, E. Giani
INAF - OA Arcetri, Firenze, Italy
G. Brajnik
IDS, Udine, Italy
M. Colciago, I. Novak
Cosylab Switzerland, Brugg, Switzerland

The Square Kilometre Array (SKA) Telescope will be one of the largest and most complex scientific instruments ever built. The development of a reliable software for monitoring and controlling its operations is critical to the success of the entire SKA project. The Local Monitoring and Control of the Central Signal Processor (CSP. LMC) is a software responsible for controlling a key subsystem of the telescope, i.e. the Central Signal Processor (CSP). The software is implemented as a "device" within the TANGO framework, written in Python. In this paper we describe a testing strategy that addresses some typical problems of such a large and complex instrument. It is a multi-level strategy, based on a combination of automated tests (unit/component/integration), in the context of CI/CD practices. Software is also tested against errors and anomalous conditions that can occur while the CSP. LMC is interacting with external subsystems, which can be simulated. The paper also discusses needs and solutions based on data mining test results. This allows us to obtain statistics of unexpected failures and to investigate their causes. Furthermore, a database containing test results supports discovery of interesting and unexpected patterns of behaviors of the tests based on correlations about different test-related events and data. This helps us to develop a deeper understanding of the code’s functioning and to find suitable solutions to minimize unexpected behaviors. In addition it can be used also to support reliability testing.

Slides MO2BCO03 [2.336 MB]

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-MO2BCO03

About •

Received ※ 06 October 2023 — Revised ※ 08 October 2023 — Accepted ※ 14 November 2023 — Issued ※ 13 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)

FR2BCO02

A Lean UX Approach for Developing Effective Monitoring and Control User Interfaces: A Case Study for the SKA CSP. LMC Subsystem

1650

V. Alberti
INAF-OAT, Trieste, Italy
C. Baffa, E. Giani, G. Marotta
INAF - OA Arcetri, Firenze, Italy
G. Brajnik
IDS, Udine, Italy
M. Colciago, I. Novak
Cosylab Switzerland, Brugg, Switzerland

The Central Signal Processor Local Monitor and Control (CSP. LMC) is a software component that allows the flow of information and commands between the Telescope Manager (TM) and the subsystems dedicated to signal processing, namely the correlator and beamformer, the pulsar search and the pulsar timing engines. It acts as an adapter by specialising the commands and associated data from the TM to the subsystems and by exposing the subsystems as a unified entity while monitoring their status. In this paper, we approach the problem of creating a User Interface (UI) for such a component. Through a series of short learning cycles, we want to explore different ways of looking at the system and build an initial set of UIs that can be refined to be used as engineering UIs in the first Array Assembly of the Square Kilometre Array. The process heavily involves some of the developers of the CSP. LMC in creating the dashboards, and other ones as participants in informal evaluations. In fact, the opportunities offered by Taranta, a tool to develop web UIs without needing web-development skills, make it possible to quickly realise a working dashboard that can be promptly tested. This also supports the short feedback cycle advocated by a Lean UX approach and maps well in a bi-weekly sprint cadence. In this paper, we will describe the method and present the results highlighting strengths and pain points where faced.

DOI •

reference for this paper ※ doi:10.18429/JACoW-ICALEPCS2023-FR2BCO02

About •

Received ※ 06 October 2023 — Revised ※ 20 November 2023 — Accepted ※ 05 December 2023 — Issued ※ 13 December 2023

Cite •

reference for this paper using ※ BibTeX, ※ LaTeX, ※ Text/Word, ※ RIS, ※ EndNote (xml)